a c -u a s t /a a o · medicine with industrial specialisation, medical market access master thesis...

A Cost-Utility Analysis of Sequential Treatment

with Teriparatide/Alendronate Compared to

Alendronate Alone in Danish Women Suffering from

Osteoporosis

Medicine with Industrial Specialisation, Medical Market Access

Master Thesis

Aalborg University

29th of May 2020

Conducted by

Louise Borup and Maria Hahn Holst

Group 10022

Supervisor

Anne Sig Sørensen

Abstract

Background: Osteoporosis and fragility fractures cause patients to utilise more

healthcare services and thereby impose an increasingly great economic burden on

society. An obvious opportunity of lowering the burden is for osteoporosis patients to

avoid sustaining fractures which increases the demand for cost-effective treatments.

Currently, the most frequently sold drug for treating osteoporosis in Denmark is the

bisphosphonate, alendronate. However, studies have shown promising results of the

effects of the bone anabolic drug, teriparatide. The patent of teriparatide expired in

August 2019, resulting in lowered prices of the compound, which has increased the

relevancy of more recent cost-effectiveness analyses.

Methods: A cost-utility analysis was carried out to investigate the health-economic

consequences of treating Danish women above the age of 50 with sequential

teriparatide/alendronate treatment compared to alendronate alone in terms of costs

and QALYs over a lifetime horizon using Markov modelling.

Results: For the base case analysis the cost of teriparatide/alendronate treatment was

DKK 761,057 per QALY when compared to alendronate alone. A WTP threshold of

DKK 250,000 per QALY was employed, meaning teriparatide/alendronate was not

considered cost-effective when compared to alendronate alone in the base case. This

result was robust to all sensitivity analyses performed except when no discounting

was applied as, in this sensitivity analysis, the ICER was DKK 241,191 per QALY.

Conclusion: This study indicated treating Danish women above the age of

50 suffering from osteoporosis with teriparatide was slightly more effective yet

more expensive when compared to alendronate, and teriparatide/alendronate was

therefore not considered cost-effective when compared to alendronate alone.

ii

Contents

1 Problem Analysis 1

2 Introduction 2

2.1 Osteoporosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2.2 Treatment of Osteoporosis . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2.2.1 Bisphosphonates . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.2.2 Teriparatide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.3 Aim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

3 Methods 10

3.1 Information Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

3.1.1 Fracture Incidence Rates . . . . . . . . . . . . . . . . . . . . . . . . 10

3.1.2 Effects of the Compounds . . . . . . . . . . . . . . . . . . . . . . . 11

3.1.3 Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3.1.4 Obtainment of Cost Estimates . . . . . . . . . . . . . . . . . . . . . 12

3.1.5 Utility Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

3.2 Markov Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3.3 The Markov Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3.3.1 Model Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.3.2 Model Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

3.4 Sensitivity Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

4 Results 27

4.1 Base Case Cost-Utility Analysis . . . . . . . . . . . . . . . . . . . . . . . . 27

4.2 Sensitivity Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

4.2.1 Deterministic Sensitivity Analyses . . . . . . . . . . . . . . . . . . 27

4.2.2 Probabilistic Sensitivity Analysis . . . . . . . . . . . . . . . . . . . 29

4.2.3 Scenario Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

4.3 State Probability Charts for Teriparatide and Alendronate . . . . . . . . 31

5 Discussion 34

5.1 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

5.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

5.2.1 The Included Estimates of the Effects of Teriparatide and

Alendronate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

5.2.2 The Inclusion of Forearm and "Other" Fractures in the Markov

Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

iii

Aalborg University

5.2.3 Half-Cycle Correction . . . . . . . . . . . . . . . . . . . . . . . . . 38

5.2.4 Ethical Considerations . . . . . . . . . . . . . . . . . . . . . . . . . 38

5.2.5 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

5.3 What’s Next? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

5.3.1 Restricted Prescription of Teriparatide in Denmark . . . . . . . . 41

6 Conclusion 42

References 43

A Appendix 50

A.1 Cost Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

A.1.1 Costs of Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

A.1.2 Costs of a Hip Fracture . . . . . . . . . . . . . . . . . . . . . . . . . 50

A.1.3 Costs of a Vertebral Fracture . . . . . . . . . . . . . . . . . . . . . 51

A.1.4 Costs of a Forearm Fracture . . . . . . . . . . . . . . . . . . . . . . 51

A.1.5 Cost of an "Other" Fracture . . . . . . . . . . . . . . . . . . . . . . 53

A.2 The Markov Model - The Teriparatide Branch . . . . . . . . . . . . . . . 54

A.3 The Markov Model - The Alendronate Branch . . . . . . . . . . . . . . . 55

A.4 Full Tornado Diagram - CUA . . . . . . . . . . . . . . . . . . . . . . . . . 56

A.5 Summary Reports - Base Case . . . . . . . . . . . . . . . . . . . . . . . . . 57

A.6 Tables Used in TreeAge When Altering the Durations of the Effects of

the Two Drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

A.7 Tables Used in TreeAge Containing the Baseline Probabilities of Dying

and Baseline Utility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

A.8 Tables Used in TreeAge Containing Fracture Incidence Probabilities for

Hip, Vertebral, Forearm, And Other Fractures . . . . . . . . . . . . . . . 61

A.9 Tables Used in TreeAge for Excess Mortality Following Hip and

Vertebral in First and Subsequent Years . . . . . . . . . . . . . . . . . . . 63

iv

1. Problem Analysis

Osteoporosis is a systemic skeletal disorder causing an increased risk of sustaining

fractures [1, 2, 3] leading to patients utilising more healthcare services which

ultimately causes them to impose increased healthcare costs [4]. The condition is

most prevalent among women [5] above the age of 50 due to menopause [6]. In fact,

about 30% of all European postmenopausal women suffer from the condition [7]. The

economic burden of osteoporosis is substantial and is expected to keep increasing in

the following years due to the ageing population [1]. Burge et al. [5] has estimated

that the fracture-associated costs will increase by 50% from 2005 to 2025 causing the

burden on healthcare systems to increase further, necessitating the need for effective

treatment methods with the ability to lower the occurrence of fractures provided at

low costs. The costs of osteoporotic fractures in Denmark were estimated at DKK

11.638 billion in 2011 [4] and, in a US study, it has been estimated that women account

for 75% of cost related to osteoporosis related fractures [5].

Currently, the most frequently sold pharmacological treatment in Denmark is

the antiresorptive bisphosphonate, alendronate [8], however, studies have shown

promising results of the effects of anabolic compounds such as teriparatide [9, 10, 11].

Unfortunately, treating patients with teriparatide during the patented period was

quite expensive, and therapy with teriparatide was previously not proven to be cost-

effective when compared to the most frequently used bisphosphonate, alendronate

[12], resulting in the use of teriparatide being restricted [13]. In August 2019, Eli

Lilly’s patent on teriparatide expired resulting in biosimilars entering the market

carrying lower prices for the highly effective treatment [14]. Taking into account the

promising effects of teriparatide and the lowered price of the treatment, a need for

more recent investigations of the cost-effectiveness of treating osteoporotic patients

with teriparatide has arised.

1

2. Introduction

2.1. Osteoporosis

Osteoporosis is characterised by an imbalance in bone remodelling leading to low

bone mineral density (BMD) and skeletal fragility which increases the risk of

sustaining fractures [1, 2, 3]. The employed diagnostic criteria for being diagnosed

with osteoporosis in Denmark mean an individual with a fragility fracture to the

vertebra or hip or a T-score of less than -2.5 in the back or hip can be diagnosed

with osteoporosis [15]. The T-score used in the definition correlates to the number of

standard deviations by which the BMD differs from the mean value in healthy young

individuals [3, 16] Approximately 3% of the Danish population has been diagnosed

with osteoporosis, corresponding to roughly 172,000 individuals. However, the

prevalence is estimated to be two to three times higher than currently identified since

many people suffering from osteoporosis remain undiagnosed.[17] In Denmark, it has

been estimated that almost 500,000 undiagnosed individuals suffer from osteoporosis

[2]. As can be seen in Figure 2.1, osteoporosis is traditionally divided into primary

osteoporosis, which is idiopathic, and secondary osteoporosis in which another

disease or pharmacological treatment has been contributing to the development of

osteoporosis. Primary osteoporosis includes postmenopausal osteoporosis, senile

osteoporosis, and a few more rare conditions such as juvenile osteoporosis.[18]

Figure 2.1: The flowchart depicts the criteria of being diagnosed with osteoporosis along withthe different types of osteoporosis.

Osteoporosis is a condition that is most often developed after the age of 50 [6] and out

of all postmenopausal women in Europe, about 30% suffer from osteoporosis [7]. The

occurrence of osteoporosis can be caused by a failure in achieving peak bone mass

2

2 Introduction Aalborg University

or severe bone resorption or/and decreased bone formation in remodelling [3]. It

entails having a greater risk of sustaining fractures compared to people not suffering

from osteoporosis. The characteristic of fractures related to osteoporosis is that they

occur spontaneously after low-energy trauma or from activities during everyday life.

Such fractures are termed fragility fractures and comprise fractures that a strong

skeleton would tolerate without fracturing.[19] Fracture types typically occurring

when suffering from osteoporosis are hip (ICD-10: S720, S721 and S722), vertebral

(ICD-10: M484, M485, M495, S220, S221, S320, and S327), of which compression

fractures are most common, forearm (ICD-10: S522, S525, and S526), and other

fractures such as fractures of the upper arm [20, 21, 19]. A fragility fracture of the hip

or vertebra is diagnostic for osteoporosis, whereas fragility fractures elsewhere are

signs of osteoporosis and should be further examined [19]. Fractures of the vertebra

are divided into clinical fractures, which are fractures leading to clinical attention, and

morphometric fractures, which are fractures without clinical manifestations which are

therefore rarely discovered and treated [22, 23].

Osteoporosis-related fractures impose a great burden on both the individual and

society [3]. In 2011, Hansen et al. [4] estimated the costs of osteoporotic fractures

in Denmark to be EUR 1.563 billion which equals about DKK 11.65 billion in 2020

value. Their study took into account costs regarding general practices, hospitals,

the municipalities, regions, and patients [4]. The prevalence of osteoporosis and

the number of osteoporosis-related fractures are numbers expected to increase and

become substantial public health problems. This is expected as the population is

ageing [1], and osteoporosis is more prevalent among the elderly [24]. Moreover, it

has been projected that the number of annual fractures and the associated costs were

to increase by nearly 50% from 2005 to 2025. In the same study, the division of costs

accounted for by men and women was estimated to be 25% and 75%, respectively.[5]

Patients suffering from symptomatic osteoporotic fractures experience emotionally

strong reactions to their conditions, among which the most frequently mentioned

psychological problems are depression and anxiety. Spine and hip fractures are two

of the most serious types of fractures and are associated with severe pain, disability,

decreased quality of life with an up to 50% reduction in patients who are left with a

permanent impairment, and even death.[3, 1] Osteoporotic asymptomatic individuals

are likely to have no knowledge of their condition until a fracture occurs, which often

brings both limited mobility, pain, and a feeling of helplessness [25].

As an extensive burden is related to fragility fractures, an obvious opportunity of

lowering the burden is to avoid sustaining fractures. Both non-pharmacological

3


and pharmacological initiatives can reduce the risk of fractures occurring. Non-

pharmacological initiatives include, among other things, maintaining a healthy

weight, not smoking, taking D-vitamin and calcium supplements, and being

physically active.[15, 24]

2.2. Treatment of Osteoporosis

For the time being, no national clinical guidelines for the treatment of osteoporosis

have been developed for use in Denmark. However, guidance for the treatment of

postmenopausal osteoporosis in women is available through the Danish Endocrine

Society [15]. During the conduction of this study, it is assumed most of the women

suffering from osteoporosis after the age of 50 suffer from the condition due to

menopause [26], and therefore, the guidance of treatment from the Danish Endocrine

Society will be applied as a background for the treatment recommendations presented

in this study.

Before initiating the treatment of a patient, it is advised to determine whether the

patient possesses any indications of secondary causes of osteoporosis. If secondary

osteoporosis is diagnosed, the task is often left for a specialist to take care of, since

the treatment will depend largely on the underlying cause. The goal of treating

osteoporosis is to prevent fractures for people with an increased risk of fractures,

to prevent individuals who already suffered a prior fracture from suffering another

fracture, and ease of symptoms for individuals with established osteoporosis.[15, 1]

As a basis it is recommended to choose a drug with documented effect on the

specific type of fracture one has suffered or one is at risk of suffering. Using

more than one drug in the treatment regimen has not been proven effective, and

therefore, monotherapy should be planned.[24, 15] According to the guidance, it is

recommended that patients who are suffering from osteoporosis or who are at risk of

developing osteoporosis take a daily supplement of 20 µg of vitamin D and 800-1200

mg of calcium [15]. The frequently used pharmacological treatments for osteoporosis

are bisphosphonates (BPs), denosumab, selective estrogen receptor modulators, and

parathyroid hormone/analogues [24]. However, only the BP, alendronate, and the

bone anabolic drug, teriparatide, will be included in the following description due to

the aim of this study which was to investigate the health-economic consequences of

treating patients with teriparatide compared to alendronate.

4


2.2.1. Bisphosphonates

It is well-documented that BPs are effective in treating most cases of osteoporosis in

both men and women [24]. The optimal length of treatment with antiresorptive drugs

is not known, however, it has, in all probability, the best effect during the first five

years of use, and the effects and safety of BPs have been documented for seven to ten

years [27]. After five years of use, the effects and side effects of the treatment for the

individual should be evaluated, however, in general, a treatment duration of five to

seven years is recommended for BPs [24].

BPs are part of the group antiresorptive agents [28]. They can be divided into

compounds that do not contain nitrogen, such as etidronate, and the ones that do,

such as alendronate, which is the most frequently used compound. Their affinity for

calcium is high, and within the body, they concentrate at active bone remodelling

sites. Both groups of BPs exert their effects by reducing the activity or the number of

osteoclasts resulting in osteoclastic bone resorption decrease. Since BPs are embedded

into the bone during the anabolic phase, these compounds reside in the body long

after cessation of treatment. The half-life of elimination of BPs from the skeleton is

up to ten years.[29] The BPs have in common that they decrease the activity of the

osteoclasts and bone turn over which increases BMD [30]. BPs comprise the first

group of approved drugs for the treatment of osteoporosis. The first BP, etidronate,

was approved in 1980 followed by the approval of alendronate in 1995.[3]

2.2.1.1. Alendronate

In Denmark, the recommended first choice for the treatment of postmenopausal

osteoporosis is alendronate [15], and it is the most frequently sold drug for treating

osteoporosis in Denmark [8]. Thus, in 2017, alendronate comprised 84% of the sold

amount of drugs for treating osteoporosis within the primary sector in Denmark.[19]

The patent of the active compound, alendronic acid, has expired, which has resulted

in generic versions of the drug being available in Europe since 2006 [3].

Alendronate has been approved for the treatment of postmenopausal osteoporosis

and the prevention of postmenopausal osteoporosis, and both prevention and

treatment of glucocorticoid-induced osteoporosis [13]. In Denmark, alendronate has

reached general reimbursement. Alendronate has been documented to progressively

increase bone mass in the hip, spine, and total body and decrease the progression

of deformities of the vertebra, and decrease the incidence of vertebral fractures and

height loss in women suffering from postmenopausal osteoporosis [31, 32]. It is

administered as weekly doses and requires overnight fasting and should always

be consumed 30 minutes prior to the first meal of the day or other drinks than

5


water. The patient is furthermore instructed to swallow the tablet along with a

glass of water while being in an upright position and remaining in an upright

position for 30 minutes following administration.[13] The most common side effects

of alendronate are bone pain, arthralgia, and muscle pain affecting more than ten out

of 100 individuals [33]. Both persistence and compliance rates for oral BPs have, in

general, been documented to be suboptimal and this has been proven to be associated

with the inconveniences of consuming BPs [34].

2.2.2. Teriparatide

In Denmark, parathyroid hormone and analogues, such as teriparatide, are indicated

for the treatment of patients who have suffered a spinal fracture within the last

three years which resulted in more than 25% height reduction of a vertebra with a

concurrent T-score of less than -3 in the spine or hip, or patients that have suffered

more than two spinal fractures in the past three years with a more than 25% height

reduction of each vertebra. The treatment can be prescribed for no more than

18-24 months, and after finishing treatment, antiresorptive drugs such as the BP,

alendronate, are recommended for future use to maintain the effects of teriparatide,

however, as mentioned earlier, they should not be prescribed at the same time.[24]

Teriparatide, which comprises the 34-amino acid N-terminal of the native parathyroid

hormone (PTH) [14], is the first approved anabolic agent that improves bone mass

and quality by stimulating osteoblastic bone formation [35, 9]. In Denmark, treatment

with teriparatide is only prescribed for patients suffering from severe osteoporosis

[15] and it has been granted single reimbursement. However, the drug is clinically

indicated for treating postmenopausal women at increased risk of fracture [36] and

not only for treating women suffering from severe osteoporosis. Firstly, the drug was

approved for a treatment duration of up to 18 months in postmenopausal women

suffering from osteoporosis. Later, the drug received its approval for use for up to 24

months.[37, 36] However, more than two years of use during a patient’s lifetime is not

recommended, since the efficacy and safety of the drug have not yet been evaluated

beyond two years [38].

Teriparatide requires refrigeration and is administered using a pre-filled pen

containing 28 daily doses. The drug is injected subcutaneously into the abdominal

wall or the thigh daily [38] and most patients can be taught to self-administer their

daily dose [39]. PTH has a direct effect on osteoblast lineage cells as well as it

indirectly affects the regulation of certain skeletal growth factors and growth factor

antagonists. The mitogenic properties for osteoblastic cells decrease the osteoblastic

apoptosis [40], of which the consequence is an increased number of bone-forming

6


cells [41, 42]. However, the precise mechanisms behind the anabolic effects of PTH

have yet to be fully elucidated.

The effects of teriparatide have been compared to placebo in a study by Neer et al. [10].

They found teriparatide has a good effect in terms of reducing the risk of sustaining

vertebral fractures. Furthermore, the risk of sustaining one or more new fractures

of the vertebra was reduced by 65% and the risk of sustaining at least two or more

fractures was lowered by 77% at a 20 µg dose.[10] Side effects of using teriparatide

include hypercalcemia which 1-3% of the treated patients report [10, 43], however,

the most frequently reported side effects are pain, nausea, and arthralgia which

approximately 10% of patients treated with teriparatide experience [38].

The firstly approved teriparatide, Forsteo by Eli Lilly, was granted marketing

authorisation by the European Medicines Agency in June 2003. In August 2019, the

patent expired, making way for biosimilars to enter the market. The two currently

available biosimilars of Forsteo, Terrosa and Movymia, are being used alongside

Forsteo in Denmark [44]. They were both granted marketing authorisation in January

2019 [45, 46] awaiting the expiration of the patent of Eli Lilly’s Forsteo. The price of

one package of Forsteo (item number 014094) was DKK 3,454.85 in July 2019 before

the patent expired in August 2019 [47]. The presence of biosimilars has enabled

competition between Forsteo, Terrosa, and Movymia which has resulted in varying

but lower prices of the drugs compared to when the patent had not yet expired. The

prices of Forsteo (item number (014094), Terrosa (126559), and Movymia (428393) were

DKK 2,539 per package as of the 20th of April 2020.[47] Since the price of teriparatide

was DKK 3,455 before the expiration of the patent, the price in April 2020 is 26.5%

lower compared to when the patent was still valid. For years, teriparatide has only

been prescribed for those at very high risk of sustaining especially vertebral fractures,

since the high price restricted the use of the drug [13]. In Denmark, this has meant that

in order to be prescribed teriparatide, the demands for the severity of the individuals’

osteoporosis are high, while no demands for the severity of osteoporosis are required

to be treated with alendronate. A flow-chart of the recommended treatment options

can be seen in Figure 2.2. However, the treatment guidance is not always followed

slavishly, as treatment choice is rather adapted to the individual patient and the

disease is often undiscovered until a fracture is sustained [25], and at that time the

condition might be advanced.

7


Figure 2.2: The flowchart depicts the course of treatment recommended by The DanishEndocrine Society [15], however, the figure mainly illustrates the options of relevance duringthis study i.e. several pharmacological treatment options have been omitted due to the theirlack of relevance for this study.

8


2.3. Aim

Osteoporosis among women over the age of 50 is a substantial financial problem

worldwide and the burden is expected to increase rapidly in the near future.

Moreover, the ultimate consequence of osteoporosis therapies is on the quality and

length of life [48] which enhances the importance of the availability of cost-effective

treatments since patients suffering from osteoporosis are heavily affected by their

conditions both physically and mentally.

For the time being, teriparatide has not been proven cost-effective compared to

alendronate, due to the high price of teriparatide [12]. However, after the patent

of teriparatide has expired, the price has been lowered, leaving the opportunity of

change in the cost-effectiveness of teriparatide in comparison with other treatment

options.

The study aimed to investigate the health-economic consequences of treating female

patients over the age of 50 suffering from osteoporosis with teriparatide compared to

alendronate in terms of costs and accumulation of quality-adjusted life years (QALYs).

This was done by constructing a decision-analytic model build on the occurrence of

four types of fractures (hip, vertebral, forearm, and "others") and their associated

utility decrements resulting in the conduction of a cost-utility analysis (CUA).

During the analyses, a Danish setting was applied to take a healthcare perspective

extended to include patient-paid costs of medication. A Markov model was

constructed to model the course of each individual until the age of 100 years or death.

Alendronate was chosen as comparator since it is the most frequently used drug for

treating osteoporosis in Denmark and it can be prescribed for all women suffering

from osteoporosis.

In Denmark, the use of QALYs and an explicitly stated WTP threshold for one unit

has not been established, however, UK has implemented a WTP threshold of £20.000

to £30.000 per QALY, which means if an intervention exceeds this level, likely, the

intervention will not be adopted for widespread use by the National Health Service

[49]. During this study, NICE’s upper WTP threshold of £30.000 which is about DKK

250,000 per QALY in 2020 value was adopted to evaluate the cost-effectiveness of

teriparatide compared to alendronate in terms of accumulation of costs and QALYs.

9

3. Methods

3.1. Information Search

To gather the needed background information and obtain knowledge about osteo-

porosis, pharmacological treatment options, and financial perspectives concerning

these, initial free text searches were conducted online to create an overview of the

subjects involved. Moreover, focused literature searches were conducted to collect the

needed information regarding the effects of teriparatide and alendronate, fracture in-

cidence rates in women over the age of 50, utility values, and mortality rates. These

were primarily obtained from literature found via the database, PubMed. Both free-

text and MeSH terms were included in the searches on PubMed to ensure thorough

approaches. In addition to the focused literature searches, snowballing was carried

out to expand our field of knowledge. Inclusion criteria used for assessing the ap-

plicability of the found literature were that the studies had to include women above

the age of 50 and they had to include a study population somewhat comparable to

the Danish population. In addition, the literature of a later date was preferred over

older literature. Overall, the literature was assessed based on the transparency of the

studies and descriptions of the applied methodological considerations.

3.1.1. Fracture Incidence Rates

A literature search was carried out to obtain the incidence rates for hip, vertebral,

forearm, and "other" fractures. The search was conducted on the 8th of March 2020

on PubMed and gave a total result of 4,544 articles. The terms used for the search can

be seen in Table 3.1. Only articles published within the past 15 years were considered

to ensure the data and literature were not obsolete. The main part of the articles was

screened to point out the relevant articles. After the screening, the remaining articles

were read in their full-text versions and out of these, two articles were used to obtain

the needed values for the model. The first of these was a study by Hiligsmann et al.

[50] which provided the fracture incidence rates for women, however, to represent a

population of women suffering from osteoporosis, each incidence rate was adjusted

using relative risks of sustaining fractures when having a T-score of -2.5 or less found

in another study by Hiligsmann and Reginster [51]. The majority of the excluded

studies were deselected due to missing information such as insufficient information

regarding their rates and because not all the fracture types included in our study

were included in the literature found. Moreover, a considerable portion of the located

studies was not carried out in women, specifically.

10

3 Methods Aalborg University

AND

Hip Prevalence Women Osteoporosis Fracture

Vertebral Incidence Female OsteoporoticOR

Forearm Rate Postmenopausal

Table 3.1: The table lists the search terms used for the literature search conducted with theaim of obtaining incidence rates for the Markov model.

3.1.2. Effects of the Compounds

The literature searches for the effects of both alendronate and teriparatide were

conducted collectively in one search on PubMed on the 9th of March 2020 and

provided a total result of 289 articles. The included search terms can be seen in

Table 3.2. Following the screening by titles and abstracts, 19 articles were left, and

these were read as full-text. Out of the 19, two were used for building the model

[52, 53]. Most studies were excluded because of missing information regarding

methods and references and some were excluded due to them investigating the effects

in incomparable populations regarding age and race.

AND

Hip Teriparatide Fracture Probability Osteoporosis

Vertebral Alendronate RateOR

Forearm

Table 3.2: The table shows an overview of the search terms used for the literature searchregarding the effects of the two investigated compounds, alendronate and teriparatide.

3.1.3. Mortality

To procure information on mortality related to osteoporosis, a literature search was

conducted on PubMed on the 9th of March 2020 using the terms seen in Table 3.3. The

literature search resulted in 951 articles. The articles were assessed by title and further

assessed by abstract if the title was of relevance. 90 articles were of interest, however,

only seven articles met the criteria of inclusion and were read in the full-text form.

Out of the seven articles, only one article by Johnell et al. [54] was used for including

mortality related to fragility fractures in the model. Moreover, an age-dependent

mortality baseline for Denmark was calculated from data obtained through Statistics

Denmark [55].

11


AND

Osteoporosis Mortality ProbabilityOR

Osteoporotic fracture Excess mortality Rate

Table 3.3: The table shows an overview of the search terms used for the literature searchregarding mortality data for the model.

3.1.4. Obtainment of Cost Estimates

Regarding the costs included in this study, several sources were utilised to obtain

these. When diagnosis-related group (DRG) charges were deemed appropriate and

the best and most precise available estimates of costs, these were utilised. They were

obtained through both the interactive DRG web-page and the spreadsheet containing

all DRG charges both by The Danish Health Data Authority [56]. The prices of the

drugs were obtained through The Danish Medicines Agency [47] and The Danish

Health Data Authority [8]. The specific assumptions needed regarding the estimations

of costs will be further described in section 3.3.2.3.

3.1.5. Utility Values

For the utility values needed in the model, a literature search was conducted on

PubMed on the 6th of March 2020 using the terms seen in Table 3.4. This literature

search gave a total of 60 articles. The 60 articles were initially screened by titles and

later by abstracts which resulted in 16 out of the 60 articles being read in the full-

text form. Out of the 16, one systematic review was used for obtaining utility values

for the model [57]. Two systematic reviews on utility multipliers were of interest,

however, Peasgood et al. [58] suffered from a lack of estimates in utility multipliers

for "other" and clinical vertebral fractures in the subsequent years. Therefore, the

utility multipliers from the study by Hiligsmann et al. [57] were used in the model,

as there was no inadequacy in data, though the review was of an older date than the

study by Peasgood et al. [58]. The majority of the articles that were sorted out were

deselected due to a lack of the needed estimates of utility values for both hip, clinical

vertebral, forearm, and "other" fractures, due to improper time spans for the utility

values, or due to the estimates being of an older date than other identified estimates.

Moreover, meta-analyses and systematic reviews were preferred due to their inclusion

of data from several studies producing aggregated estimates.

12


AND

Hip Utility Quality of life Osteoporosis Fracture

Vertebral Utility values QALY OsteoporoticOR

Forearm Disutility

Table 3.4: The tables gives en overview of the terms used for the literature search conductedin order to obtain utility values for the model.

3.2. Markov Modelling

Modelling has become an important tool in economic evaluations particularly when

a decision involving resource allocation must be made, as it helps decision-makers

identify the optimal intervention under conditions of uncertainty [59]. Moreover,

it enables extrapolation of results from trials, a combination of data from multiple

sources, and generalisation of results to other contexts. However, the quality of a

model will always be limited by the quality of the utilised data and assumptions.[60,

61, 62] Since osteoporosis is characterised as a chronic disease in which a recurrence

of fractures is present, a state transition model was appropriate for use to achieve the

aim of this study [63, 64]. Moreover, Markov models are very useful when significant

events may happen more than once and when the timing of each event is important,

as is the case for osteoporosis and it is furthermore the recommended approach for

modelling osteoporosis [48]. A state transition model also called a Markov model, is a

model in which a cohort of patients can be characterised based on "health states" that

are mutually exclusive [65]. Markov models do not naturally incorporate memory,

however, this can be done by creating unique health states able to capture the history

of patients [66].

3.3. The Markov Model

A model-based cost-effectiveness analysis was conducted in order to compare

teriparatide and alendronate for the treatment of osteoporosis. The modelled cohort

consisted of women with a start age of 50 years suffering from osteoporosis, as

women above the age of 50 comprise the subgroup of the general population in

which osteoporosis is most prevalent. A Danish setting, with a healthcare perspective

extended to include patient-paid costs of medication, was applied. All costs included

in the model were given in 2020 values, and a gross costing approach was applied.

A time horizon modelling the patients up to and including their 100th life year or

death was employed as has frequently been done by other authors when modelling

osteoporosis processes using Markov modelling [67, 68, 69, 70]. This approach was

deemed appropriate due to the chronic nature of osteoporosis causing it to often

project onto the lifetime of individuals. Since it was assumed people rarely experience

13


several fractures a year in line with the studies by Hiligsmann et al. [63] and Mori et al.

[53], the length of each cycle in the model was one year. Since the model ran for 51

cycles of one year each, a discount rate of 4% during the first 35 cycles in the model

and a discount rate of 3% in the remaining 16 cycles were applied to health outcomes

and costs in the model as recommended by The Danish Ministry of Finance [71]. This

economic evaluation used QALYs as the measure of effect as the mean to compare

the two methods of treatment and utilised a synthesis of evidence to perform the

model-based economic evaluation.

3.3.1. Model Structure

A decision-analytic model (DAM) was constructed in TreeAge Pro 2020 (Healthcare

Version) comprising a decision node followed by two identically constructed Markov

nodes, one for teriparatide and one for alendronate. The construction of the model

is illustrated in appendix A.2 and A.3. The model comprised six health states which

can be seen in the state transition diagram in Figure 3.1. The incorporated health

states were "well", "dead", "post-fracture hip", "post-fracture vertebral", "post-fracture

forearm", and "post-fracture "other"". The "dead" health state was the only absorbing

one.

Figure 3.1: The figure depicts the state transition diagram for the Markov model. Allindividuals start in the "well" health state. Each arrow represents the opportunity oftransitioning from one state to another or staying in the same health state (when a roundedarrow is applied).

Moreover, six events were incorporated into the model. Each patient had a probability

of either staying well, sustaining a vertebral, hip, or forearm fracture, sustaining an

"other fracture", or dying. The event comprising "other" fractures cover all other

fractures than hip, vertebral, and forearm fractures as has previously been done in

several other studies [72, 51, 68]. Moreover, only fractures of the vertebra leading

to clinical attention were included in the model. All patients began in the health

14


state "well" meaning they were not suffering from a previous fracture, however, only

patients diagnosed with osteoporosis entered into the model.

As a treatment duration of 5-7 years is recommended for BPs [24, 27], the treatment

duration of alendronate was modelled as six years. Likewise, the treatment duration

was modelled as two years for teriparatide, as the effects and safety of the drug have

only been studied for up to two years [38]. However, since maintaining the effects

of teriparatide can be done by preventing a decline in bone density and thereby

making sure to sustain the fracture efficacy, treatment with alendronate is usually

recommended following the two years of treatment with teriparatide which was

the approach modelled. It was therefore assumed that the patients in the model

maintained their effects of both the treatment with teriparatide/alendronate and

alendronate until they were 100 years old or dead. In the teriparatide/alendronate

branch, the effects of teriparatide were given for all years. The assumptions

regarding courses of treatment were made to reflect the real-life course of treatment

recommended in the treatment guideline [15].

It was assumed that all patients consume vitamin D and calcium supplements since

in Denmark the recommended approach is to use these supplements as a basis of

treatment both in conjunction with other treatments and on their own [24]. However,

the supplements are not reimbursed, the patients acquire them over the counter,

and no effects of the supplements were incorporated into the model. Moreover,

the associated costs were considered irrelevant for the aim of this study since no

difference between the two Markov nodes was assumed to be present. Therefore, the

costs of acquiring them were omitted during this study.

3.3.1.1. "Post-Fracture" Health States

Four "post-fracture" health states were incorporated into the model for hip, vertebral,

forearm, and "other" fractures. The post-fracture health states for hip and vertebral

fractures were incorporated into the model to be able to assign patients experiencing

a fracture in a previous cycle higher mortality and lower utility values since it

was found in the literature that during the year after a hip or vertebral fracture

the mortality rates were higher and the utility values were lower [54, 57]. In the

post-fracture health states for forearm and "other" fractures, individuals would be

given a decrement in utility during the first year after the fracture. In addition, no

utility decrements were given in these two post-fracture health states unless a new

fracture was sustained since a forearm or an "other" fracture does not carry any

utility decrement except in the year the fracture was sustained [57]. Moreover, in

all of the post-fracture health states in the model, patients were at higher risk of

15


suffering another fracture of any type. This method using post-fracture health states

was utilised to overcome the memoryless feature of Markov models known as the

"Markovian assumption" [73] which refers to the fact that whenever a patient has

moved on from a cycle, the model has no memory of where the patient was previously

in the model [64, 66].

A hierarchy of the included fracture types was modelled, with hip fractures being on

top followed by vertebral fractures. Forearm and "other" fractures were given equal

status and placed below vertebral fractures in the hierarchy. This construction was

modelled due to the included fracture types having diverse impacts on utility and

mortality according to the applied evidence. Further explanation will be provided in

the section regarding mortality, section 3.3.2.2, and utility, 3.3.2.4.

3.3.2. Model Inputs

In the following, the model inputs and assumptions regarding fracture risk, mortality,

costs, and utility will be presented.

3.3.2.1. Fracture Risk

Articles from Mori et al. [53] and Freemantle et al. [52] provided data on the effects

of teriparatide and alendronate on the occurrence of osteoporotic fractures and the

included estimates can be seen in Table 3.5. The data was provided in relative risks

compared to placebo, and therefore the risk of sustaining each type of fracture in a

placebo group was needed. Age-dependent rates of sustaining each type of fracture

in Belgian women above the age of 50 from Hiligsmann et al. [50] were converted

into probabilities and used for generating the data for the placebo-group. However, it

was necessary to adjust these to make them reflect the fracture risk in an osteoporotic

population accurately as low BMD is associated with increased fracture risk [51].

Therefore, estimates on the relative risks of sustaining a fracture for women with

a T-score of -2.5 or less were obtained from Hiligsmann and Reginster [51] and

multiplied onto the age-dependent probabilities of sustaining each type of fracture.

This data was used to reflect the fracture risk in a placebo group. The probabilities of

sustaining fractures when not being treated can be seen in Tables A.8, A.9, A.10, and

A.11 in appendix A.8 and, in the model, these were multiplied by the relative risks

of sustaining fractures while treated which were obtained from the studies by Mori

et al. [53] and Freemantle et al. [52]. The data obtained from Hiligsmann et al. [50]

and Hiligsmann and Reginster [51] originated from Belgium and not specifically from

Denmark, however, it has been found that the prevalence of osteoporosis in women

over the age of 50 in Belgium was the same as in Sweden and only slightly higher than

16


in Denmark [3]. Therefore, it was assumed the data was representative of a Danish

population.

It was incorporated into the model that the risk of sustaining another fracture was

increased after experiencing one of the included fracture types. This was in line with

other studies [74, 63]. The relative risks of sustaining a new fracture of each of the

four fracture types after having sustained either a hip, vertebral, forearm, or "other"

fracture, were obtained from a study by Klotzbuecher et al. [74] and can be seen

in Table 3.5. The relative risks were included in the post-fracture health states and

multiplied onto the risk of experiencing a fragility fracture for the first time while

treated with alendronate or teriparatide. Regarding the probability of experiencing

an "other" fracture in the post hip, post vertebral, or post "other" health states, pooled

estimates of the relative risks of sustaining all types of fractures from Klotzbuecher

et al. [74] were incorporated.

Relative risks1 Value 95% CI Ref

Post forearm - new hip fracture 1.9 1.6-2.2 [74]

Post forearm - new vertebral fracture 1.7 1.4-2.1 [74]

Post forearm - new forearm fracture 3.3 2.0-5.3 [74]

Post forearm - new other fracture 2 1.7-2.4 [74]

Post hip - new hip fracture 2.3 1.5-3.7 [74]

Post hip - new vertebral fracture 2.5 1.8-3.5 [74]

Post hip - new forearm fracture 2.4 1.9-3.2 [74]

Post hip - new other fracture 2.4 1.9-3.2 [74]

Post vertebral - new hip fracture 2.3 2.0-2.8 [74]

Post vertebral - new vertebral fracture 4.4 3.6-5.4 [74]

Post vertebral - new forearm fracture 1.4 1.2-1.7 [74]

Post vertebral - new other fracture 1.9 1.7-2.3 [74]

Post other - new hip fracture 2 1.7-2.3 [74]

Post other - new vertebral fracture 1.9 1.3-2.8 [74]

Post other - new forearm fracture 1.8 1.3-2.4 [74]

Post other - new other fracture 1.9 1.7-2.2 [74]

Efficacies of drugs as RRs compared to placebo

Alendronate

Effect on incidence of hip fracture 0.45 0.27-0.68 [53]

Effect on incidence of vertebral fracture 0.5 0.33-0.79 [53]

Effect on incidence of forearm fracture 0.82 0.25-1* [52]

Effect on incidence of other fracture 0.78 0.66-0.92 [53]

Teriparatide

Effect on incidence of hip fracture 0.42 0.1-1* [53]

Effect on incidence of vertebral fracture 0.3 0.16-0.55 [53]

Effect on incidence of forearm fracture 0.24 0.02-1* [52]

Effect incidence of other fracture 0.5 0.32-0.78 [53]

Table 3.5: The table lists the parameters used in the model. 1; relative risks of sustaininganother fracture when having sustained a prior fracture compared to the risk of experiencinga fracture when not having sustained a prior fracture. RRs; relative risks. The 95% CIs(confidence intervals) shown in the table were found through the literature and used whenperforming deterministic sensitivity analyses. For three parameters marked with * in the table,the CIs were cut off at an upper limit of 1, meaning the CIs were considered uncertainty rangesrather than CIs, hence an uncertainty range of ±20% of the mean was used for these threeparameters when performing deterministic sensitivity analyses.

17


3.3.2.2. Mortality

Age-specific baseline mortality probabilities for Danish women were calculated from

data obtained through Statistics Denmark [75]. The risk of dying at each age was

calculated from the total number of women dying at ages 50 through 100 in 2019

divided by the total number of women at each age in 2019. In the model, it

was assumed that women suffering from osteoporosis died at a faster rate due to

sustaining fractures and not from suffering from osteoporosis in general, which means

if they did not sustain any fractures they experienced no excess mortality in addition

to the age-dependent baseline mortality probabilities.

Only a total of the number of women dying at the age of 99 years old or older was

reported for 2019, leaving no specific number of people dying at the ages 99 and 100

years. Therefore, the likelihood of a woman at the age of 99 and 100 years dying was

modelled as the same likelihood as the probability of a 98-year-old woman dying.[76]

It is well-documented that a patient suffering a vertebral or hip fracture experiences

excess mortality compared to if that patient did not experience one of the two fracture

types [54]. Therefore, to incorporate this into the model, the probabilities of dying in

the first year after a hip or vertebral fracture were calculated from the annual rate of

mortality during the first year found in a study by Johnell et al. [54]. However, to

prepare the rates for insertion into the model they were converted into probabilities.

Since the study provided estimates of rates for individuals aged 60 and 80 years,

the rate for individuals at 60 years was used as the estimate of mortality for people

aged 50-70 years. Likewise, the 80-year estimate was used for people aged 70-100

years in the model. An assumption that excess mortality after a hip fracture lasts

lifelong was applied, as was done in another study by Mori et al. [53]. The increase in

mortality following a vertebral fracture was the same or even higher than the increase

in mortality following a hip fracture [63], and therefore, the assumption of lifelong

excess mortality was applied for vertebral fractures as well. To reflect the fact that

either a hip or vertebral fracture increases mortality for life, the annual rate of dying

from a hip or vertebral fracture in the fifth year after a fracture was added as the

mortality estimate in the post-fracture health states for hip and vertebral fractures

which will be applied for all subsequent years following the fractures [54].

Several studies have found that experiencing a forearm fracture or an "other" fracture

does not alter the risk of dying, thus the same probability of dying was used for

women who had not suffered a fracture as for women who had suffered a forearm or

an "other" fracture during each given cycle [77, 54, 63, 68]. A ranking of the fracture

types was modelled, as suffering a hip fracture was associated with the highest

18


probability of dying in the model, while the mortality associated with suffering a

vertebral fracture was the second highest. This means e.g. a patient in the post-

fracture hip health state suffering a fracture of the forearm will remain in the post-

fracture hip health state.

For patients experiencing two fractures in two consecutive cycles, only the excess

mortality related to the latest occurring fracture was incorporated in the model,

assuming more fractures would not lead to a higher rate of mortality. This was in

accordance with other studies.[63, 51]

3.3.2.3. Costs

All the estimated costs used in the model are seen from a healthcare sector perspective

with the inclusion of patient-paid medication costs and can be seen in Table 3.6.

Treatment Costs

Costs related to the acquisition of medication were included due to osteoporosis

medication being reimbursed when a patient reaches a certain limit of yearly

medication costs resulting in the costs being relevant seen from a healthcare sector

perspective.

As previously mentioned, six years of treatment with alendronate and the associated

costs were modelled. Likewise, treatment with teriparatide and the related costs

were modelled to occur in the first two cycles, followed by six subsequent cycles

of treatment with alendronate, cf. the treatment guideline.

The annual costs of the treatments with teriparatide and alendronate included in

the Markov model were obtained through The Danish Medicines Agency [47]. This

source was chosen as the information is updated continuously every two weeks. The

utilised prices of the drugs were of the 17th of March 2020. On this specific date, the

price of one package of teriparatide containing 28 doses was DKK 2,539 regardless

of brand chosen. One dosage is injected every day, which means the cost of being

treated with teriparatide was DKK 33,097 annually. More options were available for

alendronate as several companies sell drugs comprising the same active ingredient.

Alendronate "Sandoz" 70 mg and the package containing 14 units was chosen as

a reference as it is the product most frequently sold in Denmark.[8] The price of

one package containing 14 units was DKK 128.75, which corresponds to DKK 479.53

annually as each patient consumes one unit once a week [47]. All calculations related

to the cost estimates of treatments costs can be seen in appendix A.1.1.

Estimations of Mean Fracture Costs

Inpatient costs related to hip, vertebral, and forearm fractures were gathered through

19


the Danish DRG browser [78]. A DRG-charge includes all services performed and

covers charges that are associated with an inpatient stay. The DRG-charges are

based on the given care and used resources related to a typical patient within a

DRG group.[79] Patients suffering from osteoporosis are assumed to have a DXA-

scan regularly and attend one consultation at the general practitioner (GP) annually

[4]. However, the costs related to this were omitted for this study since no difference

between the two comparators was assumed to be present.

Estimation of the Mean Cost of a Hip Fracture

According to Kold et al. [80], all hip fractures require a surgical treatment approach.

It has been found that 75.4% of hip fractures are treated by internal fixation surgery

and the remaining by alloplasty [4]. Therefore, 75.4% of hip fractures were assigned

the 08MP28 2020 DRG-charge of DKK 67,991 which includes fracture surgery with

internal fixation near the hip, and the remaining 24.6% were assigned the DRG-charge

08MP20 including primary alloplasty of the hip of DKK 51,979. This resulted in an

average weighted cost of DKK 64,052 for treating a hip fracture surgically. Some

costs related to follow-up are accumulated after discharge when having suffered a

hip fracture. As the treatment course after a hip fracture varies depending on the

individual and the procedure performed, the treatment guideline for a hip alloplasty

was applied as the basis for the post-surgery activities included in the cost calculation

[81]. It was assumed that patients attend a follow-up visit 10 days after surgery, which

includes the removal of surgical staples at a GP [81]. The cost of consultation at a GP

in 2020 was found through the Danish Medical Association [82] to be DKK 146, and

an add-on service of DKK 199 was added for the first treatment of bigger wounds and

was assumed to include removal of surgical staples. Moreover, a follow-up visit at

the orthopaedic ward carried out by a doctor three months after surgery was assumed

to take place [81] and the 2020 DRG-charge 23MA04 of DKK 1,512 [78] was applied

for this follow-up. These assumptions resulted in an estimated cost for each hip

fracture of DKK 65,909 when adding up the weighted costs of surgical treatment,

follow up at a GP, removal of surgical staples, and the DRG-charge of a follow-up at

the ambulatory within the first year following the fracture. In the model, the cost of

DKK 65,908.8 was applied to the same cycle as a hip fracture was sustained in. The

full calculations of hip fracture costs can be seen in section A.1.2 in the appendix.

Estimation of the Mean Cost of a Vertebral Fracture

Only vertebral fractures leading to clinical attention were included in the model, as

the estimates of the drugs’ effects were evaluated on fractures that come to clinical

attention. This means the patients being seen at the hospital are typically the patients

with clinical manifestations requiring surgical treatment [83, 19]. Hence, the DRG-

20


charge of fracture surgery, back/neck 08MP22 of DKK 92,307 in 2020 [78] was applied.

A report by North Jutland Orthopaedic Surgery [84] was used to estimate the costs

related to post-surgery activities not included in the DRG-charge of fracture surgery

of the back or neck [84].

The surgical staples were assumed to be removed at a GP or by a nurse 10-13 days

after the surgery, for which the cost of a consultation and the add-on fee for removal

of staples of DKK 146 and DKK 199, respectively, were applied [82]. Moreover, follow-

up visits including X-rays at an orthopaedic surgical ward 3, 12, and 24 months after

the surgery were included [84], to each of which the DRG-charges of a consultation

at the ambulatory for orthopaedic surgery of DKK 1,512 and the DRG charge of a

complicated X-ray of DKK 747 were applied [78]. These costs were all added onto one

cycle due to the Markovian assumption. This resulted in an estimated average cost of

each vertebral fracture leading to clinical attention of DKK 99,429. The calculations

can be seen in appendix A.1.3.

Estimation of the Mean Cost of a Forearm Fracture

Since not all fractures of the forearm are treated surgically, the proportions of the

numbers of forearm fractures treated surgically and with a splint or plaster was

needed to estimate the mean cost of a forearm fracture. Data on the number of

fragility fractures of the forearm distributed by ICD-10 codes occurring in the general

population and people with osteoporosis in 2016 was obtained through The Danish

Health Data Authority [19] and can be seen in appendix A.1.

It was assumed that out of all forearm fractures occurring in the general population,

50%, occur in women while the rest occur in male individuals. Moreover, it was

assumed that the distribution of forearm fractures occurring due to osteoporosis

between men and women was the same as for hip fractures resulting in twice as many

fractures for women as for men [85]. When applying these assumptions it emerged

that 13.7% of forearm fractures occur in women suffering from osteoporosis. However,

as not every forearm fracture requires surgery, the proportion of patients appearing

in the emergency ward, assuming these fractures are treated non-surgically, and the

proportion of patients being hospitalised and discharged, assuming these patients

have been operated, were calculated. Data on men and women discharged from the

hospital after a forearm fracture and patients visiting the emergency ward in 2018

was obtained through the National Patient Register [86]. The 13.7% was applied to

calculate the proportion of women with osteoporosis experiencing a forearm fracture

out of the patients treated surgically and in the ward. It emerged, according to the

latest data from 2018, that women with a forearm fracture were treated 3.1 times

21


more often in the emergency ward than with surgery (the calculations can be seen

in appendix A.1.4). The cost of treatment with splint or plaster was obtained via

interactive DRG-charges 2020 and was found to be DKK 1,952 [56]. The cost of

surgery was the DRG-charge 08MP24 for surgery of the forearm which was DKK

34,854 in 2020 [78]. This resulted in an intermediate estimate of the average weighted

cost of treatment of a forearm fracture of DKK 9,957.

Moreover, for all forearm fractures, one follow-up visit at the ambulatory for

orthopaedic surgery including removal of plaster for each fracture of DKK 1,512,

was applied [78]. However, some fractures of the forearm necessitate an X-ray as well

during the follow-up to ensure the correct position of the bones [87]. Hence, it was

assumed that the patients who were treated surgically also needed an X-ray as part

of their follow-up visit at the ambulatory. The DRG-charge 30PR18 from 2020 of DKK

507 was applied as the cost of an uncomplicated X-ray, however, this was applied as

a weighted average since only the surgically treated fractures demand an X-ray. The

final weighted average cost of a forearm fracture was estimated to be DKK 11,593.

The calculations can be seen in appendix A.1.4.

Costs Value (DKK) Ref

Yearly costs of drugs

Treatment w. alendronate 479.53 [8]

Treatment w. teriparatide 33,097.68 [8]

Hip fracture 65,908.8

Internal fixation, DRG 67,991 [78]

Hip alloplasty, DRG 51,979 [78]

Average weighted cost of hip surgery 64,052

Consultation (GP) 145.46 [82]

Add-on service (treatment of wound) 199.34 [82]

Follow-up at the ambulatory, DRG 1,512 [78]

Vertebral fracture 99,428.8

Surgery, back/neck, DRG 92,307 [78]

Consultation (GP) 145.46 [82]

Add-on service (treatment of wound) 199.34 [82]

Follow-ups at the ambulatory, DRG (3 units, DKK 1,512 each) 4,536 [78]

X-ray, complicated, DRG (3 units, DKK 747 each) 2,241 [78]

Forearm fracture 11,592.91

Surgery, elbow/forearm, DRG 34,854 [78]

Treatment with splint/plaster, Interactive-DRG 1,952 [56]

Average weighted cost of forearm surgery 9,957.55

Follow-up, splint/plaster 1,512 [78]

X-ray, DRG, weighted* 123.36 [78]

Other fracture 25% of costs for a hip fracture 16,477.2

Table 3.6: The table lists the costs included in the mean cost estimates along with the meancosts used in the model (in bold). Ref; reference. GP; general practitioner. *X-rays only applyto the proportion of patients suffering a forearm fracture being treated surgically.

Estimation of the Mean Cost of an "Other" Fracture

For "other" fractures, the assumption that 25% of the costs related to a hip fracture

can be used to estimate the cost of "other" fractures, was applied as has previously

been done in a study by Hiligsmann et al. [63] based on an other study by Gabriel

22


et al. [88]. This assumption was further verified by Peter Vestergaard, professor and

chair of endocrinology, Department of Clinical Medicine and consultant MD PhD

DrMedSc at Aalborg University Hospital [89]. Therefore, 25% of the average cost of a

hip fracture of DKK 65,909 which is equal to DKK 16,477, was used as the estimated

mean cost of an "other" fracture. No extra costs were added as the mean hip fracture

cost includes both rehabilitation, wound treatment, follow-up, and surgical treatment

cost estimates.

3.3.2.4. Utility

The recommended outcome measure for osteoporosis models is QALYs [48]. To

investigate the accumulation of QALYs, utility values reflecting the health-related

quality of life were needed for incorporation into the model. This approach was

desired since fracture events are associated with decrements in health state utility

values that differ between fracture types [90].

Specific utility values can be assessed using several tools such as EQ-5D. When

assessing utility values for each health state, it results in a single value ranging

from 0 to reflect death and up to 1 which corresponds to perfect health.[91] However,

negative values from 0 to -1 can occur when health states worse than dead exist [92].

As utility is known to decrease by age and differs between men and women [93],

Danish age- and gender-specific baseline utility scores were desired, but no utility

data was available for Denmark. It was assumed, however, that applying age- and

gender-specific baseline from another country was more appropriate than assuming

a constant utility score of 1, as it would not reflect the reality and would overestimate

the effects of the treatments. It was assumed that baseline utility scores from the UK

were adequately transferable to the Danish setting, and therefore, age- and gender-

specific baseline utility values from Briggs et al. [94] were applied. Moreover, to

take into account all patients in the model are suffering from osteoporosis, which is a

chronic condition, all baseline utility values were reduced by -0.0418 which was found

in the study by Sullivan et al. [95] to reflect the disutility associated with suffering

from osteoporosis. As an example, this resulted in the baseline utility value for a 50

years-old woman being 0.7572.

A ranking of the fracture types was applied due to the different types of fractures

having various impacts on utility values. A hip fracture was ranked as the fracture

having the most extensive impact on utility values. Vertebral fractures had the second

most extensive impact followed by forearm and "other" fractures, which were given

equal status.

23


In the model, it was assumed that the incurrence of several fractures does not decrease

the utility values further than just one fracture would cause it to. The estimated

disutilities occurring in the years after a hip or vertebral fracture persisted for all years

beyond the year the fracture occurred in [57]. Moreover, as a hip fracture is known

to have the biggest impact on utility, a patient in the post-fracture hip health state

suffering for an example a new forearm fracture will remain in the post-fracture hip

health state. The patient will thereby continue to be given a utility multiplier equal to

the utility multiplier given to any patient suffering a hip fracture in subsequent years

(0.899, see Table 3.7), instead of jumping to the post-fracture forearm health state

which is associated with less disutility. Otherwise, the disutility associated with hip

fracture would be underestimated. This assumption was also applied for vertebral

fractures. This approach was chosen since the utility values associated with a fracture

of the hip or vertebra were not equal to the baseline values (which can be seen in

Table A.7 in appendix A.7) following the first year after the fracture [57]. For forearm

and "other" fractures the decrements in utility scores were only assumed to occur in

the year following the fracture [57]. All utility multipliers included in the model were

obtained from a study by Hiligsmann et al. [57] and can be seen in Table 3.7.

Utility Value 95% CI Reference

Well 1 [57]

Hip

First year 0.797 0.77-0.825 [57]

Subsequent years 0.899 0.885-0.91 [57]

Vertebral

First year 0.72 0.66-0.775 [57]

Subsequent years 0.931 0.916-0.946 [57]

Forearm

Forearm - first year 0.94 0.91-0.96 [57]

Subsequent years 1 [57]

Other

First year 0.91 0.88-0.94 [57]

Subsequent years 1 [57]

Dead 0 [57]

Table 3.7: The table lists the utility multipliers used in the model. CI; confidence interval.

3.4. Sensitivity Analyses

To test the uncertainty and sensitivity of the resulting ICER of this study, deterministic

sensitivity analyses were conducted to test the structural and methodological

uncertainties in the model and to investigate the impact each parameter has on

the base case ICER when varied one at a time. For the deterministic sensitivity

analyses, one-way analyses were performed and presented as a tornado diagram

and three additional one-way analyses, one on the annual cost of teriparatide and

two investigating the consequences of the inclusions of different discount rates (0%

and 7%), were conducted. The means, highs, and lows of the uncertainty intervals

24


provided in the literature were used in the deterministic analyses. However, for

three parameters of efficacy for which the uncertainty intervals were cut off at 1,

ranges of uncertainty characterised as their means ±20% were applied, since they

were considered uncertainty ranges rather than real CIs. Moreover, for each of the

cost estimates an uncertainty range of ±10% of the mean was applied for both the

deterministic and the probabilistic sensitivity analyses.

A probabilistic sensitivity analysis (PSA) was performed to evaluate all parameter

uncertainty included in the model simultaneously and indicate the degree of decision

uncertainty. By assigning each parameter an appropriate distribution, a PSA output

can be computed using second-order Monte Carlo simulation resulting in an expected

cost and effect for each simulation. PSA results can be presented in an incremental

cost-effectiveness (ICE) scatter plot on the cost-effectiveness plane or as a cost-

effectiveness acceptability curve (CEAC). These representations of the PSA output

can aid in assessing the uncertainty related to the decision in question.[96]

The PSA output was simulated by running 10,000 iterations and was presented as a

CEAC and ICE scatter plot. A PSA using the beta, gamma, and normal distributions

requires both means and standard errors (SEs). For the relative risks of suffering

a new fracture of any of the four types after having suffered a previous fracture

and the relative risk efficacy estimates, the SE calculations were performed by first

converting their means, lows, and highs onto a logarithmic scale to approach normal

distributions. These SEs were then calculated using absolute difference measures. In

the PSA, these relative risk estimates were provided with normal distributions using

the natural logarithm to the means and SEs which were exponentiated when used

in the model. However, as mentioned, for three of the efficacy estimates provided

along with CIs, the CIs from the literature were cut off at 1 resulting in a non-

normally distributed uncertainty interval meaning an SE could not be calculated.

Therefore, for the PSA, these estimates were included as beta distributions assuming

an uncertainty interval of±20% of their respective mean. Each of the three parameters

is marked with a in Table 3.8. A gamma distribution was applied to each cost

parameter to reflect a likely distribution of costs as they are often right-skewed and

are characterised as being fixed between zero and infinity [59, 97]. For the utility

parameters which were all provided with 95% CIs, the SEs were calculated from

the CIs using absolute difference measures. For each of the utility parameters, a

beta distribution was applied since they all range from zero to one. For the three

utility multipliers of 1 (well, forearm in subsequent years, and "other" in subsequent

years) and the utility multiplier of 0 for being dead, no distributions were included

in the PSA, since they were not expected to differ and therefore they were modelled

25


accordingly for the PSA. All parameters and their associated distributions used in the

PSA including their means and SEs can be seen in Table 3.8.

Three scenario-analyses were conducted. These three comprised one altering the

durations of effects, one investigating a shorter time-horizon of eight years, and a

scenario-analysis on the inclusion of only hip and vertebral fractures in the model.

A state probability chart along with a state probability summary report for each of the

two branches in the model will be presented to perform qualitative assessments of the

modelled progressions of the disease when treated with alendronate and teriparatide.

Parameter Mean value SE Distribution

Yearly costs (DKK)

Treatment w. alendronate 479.53 47.94∗ Gamma

Treatment w. teriparatide 33097.68 3309.77∗ Gamma

Hip fracture 65908.8 6590.88∗ Gamma

Vertebral fracture 99428.8 9942.88∗ Gamma

Forearm fracture 11592.91 1159.29∗ Gamma

Other fracture 16477.2 1647.72∗ Gamma

Utility multipliers

Hip - first year 0.797 0.01 Beta

Hip - subsequent years 0.899 0.01 Beta

Vertebral - first year 0.72 0.03 Beta

Vertebral - subsequent years 0.931 0.01 Beta

Forearm - first year 0.94 0.01 Beta

Other - first year 0.91 0.02 Beta

Parameter Ln(mean) Ln(SE) Distribution

Relative risks4

Post forearm - new hip fracture 0.64 0.08 Normal

Post forearm - new vertebral fracture 0.53 0.10 Normal

Post forearm - new forearm fracture 1.19 0.25 Normal

Post forearm - new other fracture 0.69 0.09 Normal

Post hip - new hip fracture 0.83 0.23 Normal

Post hip - new vertebral fracture 0.92 0.17 Normal

Post hip - new forearm fracture 0.88 0.13 Normal

Post hip - new other fracture 0.88 0.13 Normal

Post vertebral - new hip fracture 0.83 0.09 Normal

Post vertebral - new vertebral fracture 1.48 0.10 Normal

Post vertebral - new forearm fracture 0.34 0.09 Normal

Post vertebral - new other fracture 0.64 0.08 Normal

Post other - new hip fracture 0.69 0.08 Normal

Post other - new vertebral fracture 0.64 0.20 Normal

Post other - new forearm fracture 0.59 0.16 Normal

Post other - new other fracture 0.64 0.07 Normal

Efficacies of drugs expressed as relative risks compared to placebo

Alendronate

Effect on incidence of hip fracture -0.80 0.24 Normal

Effect on incidence of vertebral fracture -0.69 0.22 Normal

Effect on incidence of forearm fracture 0.82 0.164 Beta

Effect on incidence of other fracture -0.25 0.09 Normal

Teriparatide

Effect on incidence of hip fracture 0.42 0.084 Beta

Effect on incidence of vertebral fracture -1.20 0.32 Normal

Effect on incidence of forearm fracture 0.24 0.048 Beta

Effect incidence of other fracture -0.69 0.23 Normal

Table 3.8: ∗; these SEs correspond to 10% of the mean. 4; Relative risks of sustaining anew fracture when having sustained a fracture in the previous cycle compared to not havingsustained a prior fracture. RR; relative risk. ; for these three parameters the CIs (confidenceintervals) from the literature were cut off at 1, and therefore they were provided with betadistributions and an SE of 20% of the mean (neither means nor SEs were on a logarithmicscale). All Ln(mean) and Ln(SE) values in the table are only presented with two decimals.

26

4. Results

4.1. Base Case Cost-Utility Analysis

The expected values of the costs in the model following all 51 cycles were DKK

75,505 for teriparatide and DKK 15,001 for alendronate. For the utilities, the expected

values were 12.9115 QALYs for teriparatide and 12.8320 QALYs for alendronate. The

difference in costs and utilities between the two drugs was DKK 60,504 and 0.0795

QALY, respectively. Using the expected values for each Markov branch in the tree, an

ICER was calculated comparing teriparatide to alendronate.

ICER =Cteri − CalenEteri − Ealen

=75, 505− 15, 001

12.9115− 12.8320=

60, 5040.0795

= 761, 057 DKK/QALY

The base case resulted in an ICER of DKK 761,057 per QALY.

4.2. Sensitivity Analyses

4.2.1. Deterministic Sensitivity Analyses

The ICER tornado diagram in Figure 4.1 shows the parameters included in the base

case able to affect the ICER the most. However, the utility values for well, forearm, and

"other" in subsequent years, and dead were not included in the one-way analyses for

the tornado diagram, since they were assumed not to be able to vary. The parameters

are listed from the parameter that can affect the ICER the most when varied within the

range of uncertainty, to the parameter least able to affect the ICER. The parameters

able to affect the ICER the most when varied one by one within their uncertainty

ranges were the efficacy of teriparatide on the incidence of vertebral fractures and the

efficacies of alendronate on the incidences of hip and vertebral fractures as can be

seen in Figure 4.1.

Figure 4.1: The figure shows an ICER tornado diagram using all parameters except fourutility values (well, forearm, "other" (subsequent years), and dead). The red bars represent therange of the ICER when the parameter in question is higher than the base case value, and thecontrary is the case for the blue parts. Only the nine parameters able to affect the ICER themost were plotted. The full ICER tornado diagram including all parameters included in themodel can be seen in Figure A.3 in appendix A.4.

27

4 Results Aalborg University

A threshold one-way analysis on the annual medication cost of being treated with

teriparatide was conducted to identify the price of teriparatide required to make the

costs accumulated during the 51 cycles in the alendronate and teriparatide branches

equal. The one-way sensitivity analysis illustrated in Figure 4.2 provided a threshold

value of DKK 2,222, meaning the annual medication cost of teriparatide had to be

reduced to DKK 2,222 or less before the accumulated costs in the teriparatide branch

were lower than the accumulated costs in the alendronate branch when keeping

constant everything else.

Figure 4.2: The figure shows a one-way sensitivity analysis on the cost of teriparatide.

The required decrease in the annual cost of teriparatide to make teriparatide the

cheapest option in the model corresponded to an at least 93.3% price reduction

compared to the incorporated annual medication cost of being treated with

teriparatide.

Another one-way analysis was performed using no discounting on costs and effects

in the model resulting in an ICER of DKK 241,191 DKK per QALY. Likewise, the CUA

was performed using a higher discount rate of 7% in all cycles resulting in an ICER of

DKK 1,530,802 per QALY. When applying no discounting in the model, the resulting

ICER was below the employed WTP threshold of DKK 250,000 per QALY, meaning

teriparatide would be considered cost-effective when compared to alendronate if no

discounting was incorporated into the model.

28


4.2.2. Probabilistic Sensitivity Analysis

A PSA was conducted and resulted in a CEAC and an ICE scatter plot which are

presented in Figures 4.3 and 4.4. When utilising a WTP threshold of DKK 250,000

per QALY and performing a PSA of 10,000 iterations, there was an approximately

3% probability of teriparatide being cost-effective compared to alendronate as can be

seen in Figure 4.3. The intersect of the curves indicated the point at which teriparatide

was just as likely to be cost-effective as alendronate was. In this case, the lowest WTP

threshold required for teriparatide to have the highest probability of being considered

cost-effective was approximately DKK 730,000 per QALY, meaning if a WTP threshold

at or above DKK 730,000 per QALY was utilised, teriparatide could be considered cost-

effective when compared to alendronate. However, when adopting a WTP threshold

of less than DKK 730,000 per QALY, as e.g. the employed WTP threshold of DKK

250,000 per QALY, there is a higher probability of alendronate being considered cost-

effective.

Figure 4.3: The figure shows an acceptability curve depicting the probability of teriparatidebeing cost-effective compared to alendronate at a given WTP threshold ranging from DKK100,000 to 1,300,000.

An ICE scatter plot depicting the placement of each of the 10,000 iterations on the

ICER-plane can be seen below in Figure 4.4. From the scatter plot it can be seen that

when plotting the 10,000 ICER iterations on the ICER plane, the iterations are placed

in two of the quadrants of the plane. One is the more expensive and effective quadrant

(the northeast quadrant to the right of the dotted vertical line), and the other is the

more expensive yet less effective quadrant (the northwest quadrant to the left of the

dotted vertical line). It can be seen that the majority of the ICER iterations comparing

teriparatide to alendronate were not cost-effective when adopting the WTP threshold

of DKK 250,000 since the majority of the iterations were placed to the left and above

29


the stippled WTP threshold line, which is in accordance with the approximately 97%

of the iterations the CEAC indicated were not cost-effective at the WTP threshold of

DKK 250,000 per QALY when comparing teriparatide to alendronate. A substantial

amount of the 10,000 iterations was placed in the northwest quadrant which means

these ICER scatters represent simulations in which teriparatide is both more expensive

and less effective compared to alendronate, though the main part of the iterations is

situated in the northeast quadrant meaning teriparatide was more effective and more

expensive in the main part of iterations.

Figure 4.4: The incremental cost-effectiveness scatter plot depicts all 10,000 iterations fromthe PSA. The ellipse in the figure shows the 95% confidence interval.

4.2.3. Scenario Analyses

4.2.3.1. Changes in the Durations of the Effects of the Two Drugs

A scenario analysis was run on the base case to test the influence on the ICER other

durations of the effects of the two drugs than the life-long durations used in the

base case would have. In this scenario analysis, everything in the model was kept

the same as in the base case except for the durations of the effects of alendronate and

teriparatide. In this scenario, the full effects of alendronate were applied to the first six

stages followed by a linear decline of the effect over six years until reaching no effect.

For teriparatide/alendronate, the full effect of teriparatide was modelled for the first

eight years until the cessation of treatment followed by eight years of linear decline

in effect until no effect. This approach was in line with other studies [63, 67, 69] and

resulted in an ICER of DKK 1,044,617 per QALY.

30


4.2.3.2. Time Horizon of Eight Years

To test the influence of the employed time horizon on the ICER, the model was run

using a time horizon of eight years instead of 51 years to investigate the influence of a

shorter time horizon, which would result in the women only being modelled from 50

and up to 58 years-old and e.g. ensure the effects of the drugs were not extrapolated

into the unknown.

This scenario analysis resulted in an ICER of DKK 15,201,429 per QALY which was

well above the employed WTP threshold of DKK 250,000 per QALY.

4.2.3.3. Changes in the Included Fracture Types

The structural uncertainty of the base case was tested by removing fracture types

included in the model. The base case was constructed by including four fracture

types. In this scenario analysis, forearm and "other" fractures were removed from

the model to investigate the influence of the inclusion of these two fracture types

on the ICER. When running 51 cycles of the model with hip and vertebral fractures

remaining in the model and forearm and "other" fractures removed, the resulting

ICER was DKK 890,385 per QALY.

4.3. State Probability Charts for Teriparatide and

Alendronate

The two state probability charts in Figures 4.5 and 4.6 show the probabilities of

individuals being in each health state at each stage modelled (0-51) for teriparatide

and alendronate, respectively. The state probability chart and the associated Markov

cohort summary report for teriparatide, which can be seen in Table A.4 in appendix

A.5, show the probability of being in the absorbing state at the end of the modelled

time horizon was 99.50% for teriparatide.

31


Figure 4.5: The figure shows the state probability chart for the teriparatide branch depictingthe flow of individuals through each health state in the branch through the 51 cycles.

The state probability chart in Figure 4.6 and the associated Markov cohort summary

report, which can be seen in Table A.3 in appendix A.5, show that in the alendronate

branch, the probability of being in the health state "dead" was 99.55% following the

51 cycles.

Figure 4.6: The figure shows the state probability chart for the alendronate branch depictingthe flow of individuals through each health state in the branch through the 51 cycles.

When the two charts above and their associated summary reports, which can be seen

in Tables A.3 and A.4 in appendix A.5, were compared, it was observed that the

probability of experiencing a hip fracture while treated with alendronate was higher

32


compared to the probability of incurring a hip fracture while treated with teriparatide.

The same tendency was observed when investigating the probabilities of sustaining

vertebral fractures since the probabilities of experiencing vertebral fractures were

higher when treated with alendronate compared to when treated with teriparatide.

33

5. Discussion

5.1. Results

The base case resulted in an ICER of DKK 761,057 per QALY. From the sensitivity

analyses, it emerged the result of this study was robust to all sensitivity analyses

performed, except for the sensitivity analysis in which no discounting was applied,

as this factor was the only factor investigated able to lower the ICER enough

for teriparatide/alendronate to be considered the cost-effective treatment when

compared to alendronate alone and applying a WTP threshold of DKK 250,000 per

QALY. However, the concept of discounting costs and health benefits is, seen from a

socio-economic perspective, an important aspect to include as it is considered fallible

not to consider the uncertainties associated with the expected future costs and health

benefits, and therefore, the result of the sensitivity analysis investigating the impact

no discounting would have on the ICER is informative though it is unlikely to provide

a basis for a given decision within this field.

When comparing the base case ICER to the result from another study by Liu et al.

[12] investigating the cost-effectiveness of sequential teriparatide/alendronate therapy

compared with alendronate alone using microsimulation, the ICER of our study was

lower than the ICER of DKK 1.07 million (2020 value) per QALY found in their study.

However, their analysis employed a wider perspective including nursing home costs,

and their study was conducted before the expiration of the patent of teriparatide,

meaning their employed annual cost of being treated with teriparatide was 34.7%

higher than the medication cost estimate included in this study. In addition to their

broader perspective and higher medication cost of teriparatide, their study used

higher costs for forearm and hip fractures, and they furthermore did not include

"other" fractures in their analysis. Hence the study by Liu et al. [12] was not fully

comparable to our study, however, a study fully comparable to our study was not

identified.

It was found from the state probability charts and their associated summary reports

that the patients treated with teriparatide are less likely to experience both hip and

vertebral fractures than patients treated with alendronate which is in accordance with

the effects of teriparatide and alendronate obtained from a study by Mori et al. [53],

since teriparatide was superior in reducing the risk of suffering both hip and vertebral

fractures. The fracture efficacy estimates used in the present study were comparable

to the estimates used in other studies incorporating teriparatide as the drug being

superior in reducing fracture risks [12, 98]. However, some discrepancy exists between

studies regarding the effects the two drugs provide in terms of reducing fracture risk

34

5 Discussion Aalborg University

in relative risks compared to placebo, as e.g. Hiligsmann et al. [69] have employed

effects of alendronate on the occurrence of hip and wrist fractures that were more

effective than for teriparatide. However, the inclusion of the effects from Hiligsmann

et al. [69] would not be expected to lead to a different conclusion regarding which

one of the two treatments was considered cost-effective at a WTP threshold of DKK

250,000 per QALY. On the contrary, it would be expected to strengthen the conclusion

since the effects of teriparatide in their study were less efficacious than the effects

included in our study resulting in an even smaller difference in QALY gain between

teriparatide and alendronate or it may even result in teriparatide being dominated. As

can be seen in the ICER tornado diagram in Figure 4.1, the effects of the drugs were

found to be of importance since it emerged that seven out of eight of the drug effect

estimates on the incidence of each fracture type were among the nine parameters

able to affect the ICER the most when varied one by one. This indicates the choice

of literature providing the effect estimates is of extreme importance and should be

chosen carefully since, in the present study, they were found to be able to influence the

final ICER substantially. However, remembering the drawbacks of one-way sensitivity

analyses is important in this context since the likelihood of each parameter reaching

its high or low value is unknown.

Our model predicted the probability of being in the absorbing "dead" state at the

end of the modelled time horizon was approximately 99.5% for both teriparatide and

alendronate. Another study by Mori et al. [53] found when employing a 105-year time

horizon that the probability of being dead at the end of the model was 99.9%, which

must be considered very similar to the results of our study when taking into account

the difference in time horizons.

5.2. Methods

5.2.1. The Included Estimates of the Effects of Teriparatide and

Alendronate

An advantage of using DAMs was emphasised during the conduction of this study

since the effects of the two drugs obtained in the literature were only identified as the

effect of each drug when compared to placebo expressed as relative risks, meaning

no head-to-head comparison between teriparatide and alendronate was identified.

However, the use of DAMs enabled an indirect comparison of the two drugs by

combining data. This necessitated the inclusion of a baseline fracture risk in an

osteoporotic population which had to be transferable to a Danish setting. When

applying this approach instead of a direct comparison of the effects of the two drugs,

the risk of introducing uncertainties in the model is higher, since a baseline reflecting

35


the actual fracture risk in an osteoporotic population might be difficult to obtain. It

can be difficult to obtain because it would be ethically wrong not to treat patients

diagnosed with osteoporosis since the disease influences both the quality and length

of an individual’s life [48]. And therefore, the fracture risk baseline in an osteoporotic

population had to be estimated. The employed baseline probabilities of sustaining a

fracture of each of the four fracture types when suffering from osteoporosis can be

seen in Tables A.8 through A.11 in appendix A.8. The probabilities of sustaining a

fracture of any of the four types are surprisingly low when considering the modelled

cohort is a population diagnosed with a condition causing a higher risk of bone

fractures. As an example, the probability of sustaining a hip fracture for a 70-years-

old woman was just 0.01, meaning only 1% incurred a hip fracture in cycle 20 and

this was the probability before the application of the effects of the drugs. However,

the baseline probabilities of sustaining fractures were found similar to the estimated

baselines used in other studies [51, 69] and were therefore deemed reasonable for

inclusion into our model.

The estimates of effects of the drugs obtained from the literature for use in our model

were, in some instances, inexact. In particular, the CIs of the three parameters used

in the model for the effect of alendronate on the occurrence of forearm fractures and

the effects of teriparatide on the occurrence of forearm and hip fractures were, in

the original literature, all assumed to be efficacious in reducing the occurrence of

fractures. However, Mori et al. [53] were aware that these three relative risk estimates

had a CI ranging above 1 meaning they were not guaranteed to be efficacious. This

approach applied by Mori et al. [53] resulted in the CIs in question being considered

ranges of uncertainties rather than real CIs and they therefore no longer represented

the real uncertainty related to these parameters. For the results of the PSA of our

model, this meant these three effect estimates were overestimated since the "CIs" of

these effects should, in fact, incorporate the possibility of the relative risks going

above 1, meaning they could lead to more fractures. In conclusion, our model, when

running the PSA, was more effective in reducing the risk of fractures than would have

been the case if these parameters were not cut off at 1.

For the effectiveness of the two drugs on fracture risks, relative risks of sustaining

a fracture of each of the four fracture types while treated compared to fracture

risks in a placebo group were obtained as efficacy estimates from the literature as

opposed to estimates of effects. Studies estimating efficacy are conducted under

ideal circumstances whereas effectiveness trials are conducted in "real-world" clinical

settings [99]. This inevitably leads to the effects included in the model being better

than what may be observed in a normal population of osteoporotic patients. This

36


means the modelled approach using efficacy estimates likely led to a smaller amount

of fractures than would be observed in reality resulting in an overestimation of

the effects the drugs have on the reduction of fracture risk which further leads

to an overestimation of the accumulations of QALYs. This approach was chosen

due to a lack of estimates of effectiveness, however, since efficacy estimates were

utilised for both alendronate and teriparatide, no expected difference between the

two comparators was expected to be present.

Moreover, during this study, it was assumed that the effects of the drugs in terms

of reducing fracture risks when treated with alendronate or teriparatide persisted for

all years modelled, which must be considered a quite optimistic approach since no

studies confirming the effects are that long-lasting have been identified. Hence, to test

the influence of the effects of the treatments after cessation of treatment on the final

result of the model, a sensitivity analysis was performed assuming a linear decrease

in the effects of the drugs through eight and six years after treatment cessation of

sequential teriparatide/alendronate and alendronate alone, respectively. The ICER of

this scenario analysis was above DKK 250,000 per QALY resulting in no change of

conclusion regarding the cost-effectiveness of teriparatide compared to alendronate.

5.2.2. The Inclusion of Forearm and "Other" Fractures in the

Markov Model

Regarding the importance of including both the post-fracture health states for forearm

and "other" fractures, the relevance of their inclusion can be discussed. In a review

by Zethraeus et al. [48], it is argued that if only minor changes in costs, utility

values, and mortality are related to specific disease states within the model, it can

be suggested to exclude the health states in question. As an example, the exclusion

of a forearm fracture health state has been shown to be of only minor importance for

the ultimate cost-effectiveness results [48]. However, for the purpose of this study,

the common osteoporotic fractures were included to create a detailed osteoporosis

model, since assuming osteoporotic patients do not experience e.g. any forearm

fractures at all would be a gross oversimplification. The same goes for the "other"

fractures since osteoporotic patients are at higher risks of sustaining more of all types

of fractures than a population free of osteoporosis would be [51]. However, it should

be kept in mind as well that all parameters included in the model related to "other"

fractures inevitably carry an extra amount of uncertainty and roughness because of

the heterogeneity of the fractures included.

To test the influence on the ICER the inclusion of forearm and other fractures

had in the base case analysis, the two fracture types were removed completely

37


from the model in a scenario analysis. The scenario analysis resulted in an ICER

of DKK 890,385 per QALY which is just about DKK 129,000 per QALY higher

than the base case ICER which can be considered a relatively small increase when

removing the two fracture types. This scenario analysis further supports the finding

that teriparatide/alendronate was not cost-effective compared to alendronate since

regardless of the inclusion of these two fractures, the resulting ICERs were well above

the employed WTP threshold of DKK 250,000 per QALY meaning the base case ICER

was not sensitive to the exclusion of forearm and "other" fractures, which backs the

theory by Zethraeus et al. [48] that the inclusion of e.g. forearm fractures is of minor

importance for the ultimate decision.

5.2.3. Half-Cycle Correction

Including half-cycle correction in the model was considered, however, the final

decision was to omit half-cycle correction completely. Half-cycle correction is usually

performed because computer-based models simulate an occurrence of transitions at

either the end or the beginning of each cycle. However, this often fails to reflect

reality since transitions are often assumed to occur half-way through each cycle on

average.[100] In TreeAge Pro, the full cycle’s state reward is accumulated at the

beginning of each cycle while all transitions occur at the end of each cycle leading

to an overestimation of expected values [101].

In our model, the first years of treatment were quite important in terms of costs, as

they constitute a substantial part of the total costs per patient accumulated through

the 51 cycles, since the medication costs are primarily accumulated during the

first cycles, and therefore it would have been unreasonable to implement half-cycle

correction for these costs. It was considered to omit the costs of the drugs from the

half-cycle correction but still correct all other costs and effects included in the model,

however, this would result in an unwanted in-congruence in the model output and

was therefore avoided. Besides, the accumulation of costs and effects during the

remaining cycles was limited, and a half-cycle correction was expected to be of minor

importance for the result of this study.

5.2.4. Ethical Considerations

An ethical consideration regarding the employment of a WTP-threshold in economic

evaluations concerns the fact that some drugs might not be provided for widespread

use because the cost per QALY is above a given WTP threshold, meaning e.g. an

effective treatment may not be offered for all relevant patients due to the price

level, which would deprive some patients the opportunity of benefiting from the

effective treatment. This might be the case for teriparatide, as it is an effective yet

38


very expensive treatment which has up until now been restricted for use in patients

suffering from severe osteoporosis in Denmark. However, though a treatment method

may be found to be more effective than others, the implementation of a non-cost-

effective intervention would result in a net QALY loss if the intervention was to be

implemented for widespread use, which would be due to high opportunity costs,

which would not be a socially desirable outcome.

5.2.5. Limitations

5.2.5.1. Perspective

Ideally, a strict societal perspective should be included to ensure consistency with

economic theory, and it is furthermore the recommended approach in the field of

osteoporosis since the ultimate consequences of the condition go beyond any specific

health care system [102, 48]. However, during this study limitations regarding

relevant estimates provided in the literature and access to patient-specific data was

restricted, thereby limiting the inclusion of all the parameters needed to conduct

an analysis with a societal perspective. Therefore, a decision was made to only

include somewhat certain parameters into the model to avoid the incorporation of

unacceptably uncertain parameters meaning costs such as those of side effects due

to the two investigated drugs and the number of people being taken care of in care

homes and the related costs were omitted. Since the applied health care perspective

extended to include patient-paid costs is narrower than a societal perspective, some

aspects of benefits and the associated opportunity costs were excluded, and therefore,

this study is unlikely to provide a basis for social choice. In addition, differences

in the chosen perspectives of various studies within the field of osteoporosis along

with the significance of the chosen setting can add to the difficulty of finding studies

comparable to the present study.

5.2.5.2. Considerations regarding Adherence and Persistence

In the model, a limited number of parameters were included, however, there are

inevitably more relevant aspects of the matter to consider. One of these is adherence

to the treatments in question as well as compliance. Adherence rates to treatments

for osteoporosis have been shown to be poor in general [103] since for instance Imaz

et al. [104] found that the mean amount of days of persistence was just 184 days with

a follow-up of 365 days and several studies have found medical possession rates lower

than the lowest optimal level of 80% [103, 104, 34].

For oral BPs, specifically, both the overall compliance and persistence rates are

suboptimal. However, those using weekly BP medication demonstrate better

39


compliance and persistence rates than patients prescribed a dosing regimen of daily

BP [34]. Moreover, Cramer et al. [34] state that in addition to osteoporosis being a

silent disorder, BPs carry the inconvenience of needing to be consumed following a

night of fasting and the patient moreover needs to stay in an upright position for

30 minutes as mentioned in section 2.2.1. Keeping in mind the poor adherence to

oral BPs and the aforementioned associated inconveniences related to administration,

injectable agents for treating osteoporosis have furthermore been found to carry

both higher persistence and adherence rates than for oral therapies [105] leaving

the question of whether teriparatide, an injectable agent, should be preferred for a

proportion of patients showing very low adherence and persistence rates despite the

higher costs of teriparatide. However, one factor that might contribute to a higher rate

of persistence for patients taking teriparatide could be patients prescribed teriparatide

may be more motivated to be adherent and persistent to their treatments as they often

suffer from severe osteoporosis, since, for instance in Denmark, the use of teriparatide

is only recommended for patients suffering from severe osteoporosis.

For future investigation, an approach incorporating adherence and persistence into

Markov models should be preferred since Cobden et al. [106] has found the

incorporation of adherence when modelling a chronic disease (diabetes type 2 in

their case) can influence the final ICER found through Markov models markedly.

In our model, the expected influence of incorporating adherence and persistence

would be that the incorporation of these factors would lead to teriparatide looking

more favourable when compared to alendronate than it did in the present model in

which persistence and adherence were omitted. This was expected since the effects

of alendronate would be poorer if patients were not adherent and persistent with

therapy due to the inconveniences associated with administration [34].

5.2.5.3. Utility Decrements Related to Modes of Administration of Teriparatide

and Alendronate

In our model, no utility decrements related to the modes of administration of

the drugs were incorporated, however, this may be a factor able to influence

the result of the base case ICER. Deducing in what way the incorporation of

these types of utility decrements would influence the result of our study was

not straightforward since subcutaneous injections can be associated with some

inconveniences, however, that might be the case for the oral administration of

alendronate as well since the requirements pre- and post-administration are quite

strict. It has been found in a study by Hadi et al. [107] that when the burden associated

with treatment mode of administration increases, it is associated with a subsequent

40


decline in utility and should, therefore, be included when doable. Unfortunately,

no study characterising the utility decrements for weekly oral alendronate and daily

subcutaneous teriparatide was identified, hence the lack of incorporation of utility

decrements related to modes of administration.

5.3. What’s Next?5.3.1. Restricted Prescription of Teriparatide in Denmark

An underlying assumption during the conduction of this model-based study was that

all individuals passing through the model can be prescribed teriparatide, when, in

reality, a certain degree of the severeness of the osteoporotic condition is demanded

for teriparatide to be prescribed in Denmark. Hence, the two modelled populations

were modelled as being equal in terms of the severity of their osteoporosis when,

in real life, they probably are not, at least not in Denmark. However, it should

be kept in mind that in Denmark, the use of teriparatide is restricted for patients

severely affected by their condition only because of the high price of the compound

and not because teriparatide has not been approved for use in all postmenopausal

women, meaning if the costs of teriparatide were lower, severity might be redundant.

These were the considerations creating the basis for the one-way analysis investigating

what level the medication costs of teriparatide would need to be lowered to approach

redundancy of severity of conditions of osteoporosis. As mentioned earlier in the

result section 4.2.1, for the costs accumulated in the teriparatide branch to be equal

to the costs accumulated in the alendronate branch through the 51 cycles, the annual

cost of teriparatide would need to be just DKK 2,222 as can be seen in Figure 4.2. The

required reduction of the medication costs of teriparatide to DKK 2,222 is in stark

contrast to the currently incorporated medication cost of teriparatide of DKK 33,098.

A reduction of the medication cost of teriparatide of this magnitude would call for

a reduction of the current annual cost of 93.3%. As previously mentioned in section

2.2, biosimilars are now available and therefore a reduction of the price from when

teriparatide was patented and till the patent went off has already taken place and

resulted in a 26.5% reduction. This causes it to be highly unlikely that the price will be

further reduced by 93.3% thereby making it unlikely that teriparatide will be adopted

for wide use in the near future despite the effectiveness of the compound. However, a

recent study demonstrated cyclic teriparatide therapy in patients taking alendronate

reduced the dose of teriparatide with 50% over two years, while still maintaining

the full effects of the drug [12]. This leaves the opportunity of using teriparatide in

a cheaper yet very effective way, however, this alternative way of using teriparatide

should be investigated further before a decision to implement can be made.

41

6. Conclusion

Because the price of teriparatide has been reduced by 26.5% following the

expiration of its patent, the relevance of more recent investigations of the cost-

effectiveness of teriparatide compared to the most frequently used treatment with

the bisphosphonate, alendronate, has increased. Therefore, a cost-utility analysis

comparing the use of sequential teriparatide/alendronate to alendronate alone for

treating women above the age of 50 was performed by constructing a Markov

model utilising a lifetime horizon of 51 years with an applied healthcare perspective

extended to include patient-paid costs.

The base case analysis resulted in an ICER of DKK 761,057 per QALY which means

treating Danish women above the age of 50 with sequential teriparatide/alendronate

was not considered cost-effective compared to treating these women with alendronate

when employing the WTP threshold of DKK 250,000 per QALY.

The result was robust to all sensitivity analyses performed except for the use of no

discounting on costs and effects in the model which led to an ICER of DKK 241,191

per QALY which was just below the employed WTP threshold of DKK 250,000 per

QALY. In general, the parameters most likely to influence the result of this study

when varied one at a time in one-way analyses were the effects of the two drugs

in reducing fracture risk. In addition, it was found from the PSA that there was

only a 3% probability teriparatide/alendronate was cost-effective when compared to

alendronate when employing the WTP threshold of DKK 250,000.

This study concluded that teriparatide/alendronate was more effective since the

amount of QALYs accumulated through 51 cycles was higher than for alendronate,

however, benefiting from the better effect of the sequential teriparatide/alendronate is

quite expensive for the gain in QALYs achieved. The base case ICER of DKK 761,057

per QALY indicated adopting the treatment with teriparatide for wide use would

lead to a displacement of QALYs since the opportunity costs are simply too high if

assuming society is willing to pay no more than DKK 250,000 per QALY, which can

also be interpreted as the acceptable amount of opportunity costs and benefits society

is willing to spend on a QALY. Therefore, this study indicated an expansion of the use

of teriparatide would lead to a net loss of QALYs, thereby suggesting the requirements

for receiving treatment with teriparatide should not be loosened shortly.

42

References

[1] S. K. Sandhu and G. Hampson. The pathogenesis, diagnosis, investigation and management of

osteoporosis. Journal of Clinical Pathology, 64(12):1042–1050, 2011.

[2] Sundhedsstyrelsen. Osteoporose - en afdækning af den samlede ind-

sats mod osteoporose, 2018. URL https://www.sst.dk/da/udgivelser/2018/

osteoporose-en-afdaekning-af-den-samlede-indsats-mod-osteoporose. [Access date:

2020-05-28].

[3] E. Hernlund, A. Svedbom, M. Ivergård, J. Compston, C. Cooper, J. Stenmark, E. V. McCloskey,

B. Jönsson, and J. A. Kanis. Osteoporosis in the European Union: Medical management,

epidemiology and economic burden: A report prepared in collaboration with the International

Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry

Associations (EFPIA). Archives of Osteoporosis, 8(1-2), 2013.

[4] L. Hansen, A. S. Mathiesen, P. Vestergaard, L. H. Ehlers, and K. D. Petersen. A health economic

analysis of osteoporotic fractures: Who carries the burden? Archives of Osteoporosis, 8(1-2), 2013.

[5] R. Burge, B. Dawson-Hughes, D. H. Solomon, J. B. Wong, A. King, and A. Tosteson. Incidence

and economic burden of osteoporosis-related fractures in the United States, 2005-2025. Journal of

Bone and Mineral Research, 22(3):465–475, 2007.

[6] D. Scarlet. Videnscenter for Knoglesundhed. Journal of Chemical Information and Modeling, 53(9):

1689–1699, 2019.

[7] International Osteoporosis Foundation. Epidemiology, 2020. URL https://www.iofbonehealth.

org/epidemiology. [Access date: 2020-04-22].

[8] The Danish Health Data Authority. Medstat.dk, 2019. URL https://medstat.dk/. [Access date:

2020-03-17].

[9] A. B. Hodsman, D. C. Bauer, D. W. Dempster, L. Dian, D. A. Hanley, S. T. Harris, D. L. Kendler,

M. R. McClung, P. D. Miller, W. P. Olszynski, E. Orwoll, and K. Y. Chui. Parathyroid hormone

and teriparatide for the treatment of osteoporosis: A review of the evidence and suggested

guidelines for its use. Endocrine Reviews, 26(5):688–703, 2005.

[10] R. M. Neer, C. D. Arnaud, J. R. Zanchetta, R. Prince, G. A. Gaich, J. Y. Reginster, A. B. Hodsman,

E. F. Eriksen, S. Ish-Shalom, H. K. Genant, O. Wang, B. H. Mitlak, D. Mellström, E. S. Oefjord,

E. Marcinowska-Suchowierska, J. Salmi, H. Mulder, J. Halse, and A. Z. Sawicki. Effect of

parathyroid hormone (1-34) on fractures and bone mineral density in postmenopausal women

with osteoporosis. New England Journal of Medicine, 344(19):1434–1441, 2001.

[11] D. L. Kendler, F. Marin, C. A. F. Zerbini, L. A. Russo, S. L. Greenspan, V. Zikan, A. Bagur,

J. Malouf-Sierra, P. Lakatos, A. Fahrleitner-Pammer, E. Lespessailles, S. Minisola, J. J. Body,

P. Geusens, R. Möricke, and P. López-Romero. Effects of teriparatide and risedronate on new

fractures in post-menopausal women with severe osteoporosis (VERO): a multicentre, double-

blind, double-dummy, randomised controlled trial. The Lancet, 391(10117):230–240, 2018.

[12] H. Liu, K. Michaud, S. Nayak, D. B. Karpf, D. K. Owens, and A. M. Garber. The cost-effectiveness

of therapy with teriparatide and alendronate in women with severe osteoporosis. Archives of

Internal Medicine, 166(11):1209–1217, 2006.

[13] J. Compston, A. Cooper, C. Cooper, N. Gittoes, C. Gregson, N. Harvey, S. Hope, J. A. Kanis,

E. V. McCloskey, K. E.S. Poole, D. M. Reid, P. Selby, F. Thompson, A. Thurston, and N. Vine. UK

clinical guideline for the prevention and treatment of osteoporosis. Archives of Osteoporosis, 12(1),

2017.

[14] I. Takács, E. Jókai, D. E. Kováts, and I. Aradi. The first biosimilar approved for the treatment of

43

https://www.sst.dk/da/udgivelser/2018/osteoporose-en-afdaekning-af-den-samlede-indsats-mod-osteoporose

https://www.sst.dk/da/udgivelser/2018/osteoporose-en-afdaekning-af-den-samlede-indsats-mod-osteoporose

https://www.iofbonehealth.org/epidemiology

https://www.iofbonehealth.org/epidemiology

https://medstat.dk/

References Aalborg University

osteoporosis: results of a comparative pharmacokinetic/pharmacodynamic study. Osteoporosis

International, 30(3):675–683, 2019.

[15] The Danish Endocrine Society. NBV: Postmenopausal osteoporose, 2016. URL http://www.

endocrinology.dk/index.php/3-calcium-og-knoglemetaboliske-sygdomme/3-osteoporose.

[Access date: 2020-04-21].

[16] Sundhed.dk. Knogletæthedsmålinger, 2019. URL https://www.sundhed.dk/sundhedsfaglig/

laegehaandbogen/undersoegelser-og-proever/undersoegelser/oevrige-undersoegelser/

knogletaethedsmaalinger/. [Access date: 2020-05-28].

[17] P. Vestergaard, L. Rejnmark, and L. Mosekilde. Osteoporosis is markedly underdiagnosed: A

nationwide study from Denmark. Osteoporosis International, 16(2):134–141, 2005.

[18] Dansk Knoglemedicinsk Selskab. Vejledning til udregning og behandling af osteoporose.

Technical report, Dansk Knoglemedicinsk Selskab, 2012.

[19] The Danish Health Data Authority. Prævalens, incidens og behandling i sund-

hedsvæsenet for borgere med osteoporose, 2018. URL https://www.sst.dk/~/media/

73D2379F2BA24D98866A921E9D418900.ashx. [Access date: 2019-02-21].

[20] K. L. Stone, D. G. Seeley, L. Y. Lui, J. A. Cauley, K. Ensrud, W. S. Browner, M. C. Nevitt, and S. R.

Cummings. BMD at Multiple Sites and Risk of Fracture of Multiple Types: Long-Term Results

From the Study of Osteoporotic Fractures. Journal of Bone and Mineral Research, 18(11):1947–1954,

2003.

[21] O. Ström, F. Borgström, N. Zethraeus, O. Johnell, L. Lidgren, S. Ponzer, O. Svensson, P. Abdon,

E. Ornstein, L. Ceder, K. G. Thorngren, I. Sernbo, and B. Jönsson. Long-term cost and effect on

quality of life of osteoporosis-related fractures in Sweden. Acta Orthopaedica, 79(2):269–280, 2008.

[22] S. Boonen and A. J. Singer. Osteoporosis management: Impact of fracture type on cost and

quality of life in patients at risk for fracture I. Current Medical Research and Opinion, 24(6):1781–

1788, 2008.

[23] D. Diacinti and G. Guglielmi. How to define an osteoporotic vertebral fracture? Quantitative

Imaging in Medicine and Surgery, 9(9):1485–1494, 2019.

[24] B. Nygaard, J. K. Kristensen, and H. C. Kjeldsen. Lægehåndbogen - Osteoporose,

2020. URL https://www.sundhed.dk/sundhedsfaglig/laegehaandbogen/endokrinologi/

tilstande-og-sygdomme/knoglevaev-og-vitamin-d/osteoporose/. [Access date: 2019-02-19].

[25] D. T. Gold. The nonskeletal consequences of osteoporotic fractures: Psychologic and social

outcomes. Rheumatic Disease Clinics of North America, 27(1):255–262, 2001.

[26] M. Ji and Q. Yu. Primary osteoporosis in postmenopausal women. Chronic Diseases and

Translational Medicine, 1(1):9–13, 2015.

[27] D. M. Black, A. V. Schwartz, K. E. Ensrud, J. A. Cauley, S. Levis, S. A. Quandt, S. Satterfield,

R. B. Wallace, D. C. Bauer, L. Palermo, L. E. Wehren, A. Lombardi, A. C. Santora, and S. R.

Cummings. Effects of continuing or stopping alendronate after 5 years of treatment: The Fracture

Intervention Trial long-term extension (FLEX): A randomized trial. Journal of the American Medical

Association, 296(24):2927–2938, 2006.

[28] E. Canalis, A. Giustina, and J. P. Bilezikian. Mechanisms of Anabolic Therapies for Osteoporosis.

The New England Journal of Medicine, 357:905–916, 2007.

[29] L. S. Kates and C. L. Ackert-Bicknell. How Do Bisphosphonates Affect Fracture Healing?

Physiology & behavior, 176(10):139–148, 2017.

[30] Pro.medicin. Bisfosfonater, 2019. URL http://pro.medicin.dk/laegemiddelgrupper/grupper/

160520. [Access date: 2019-02-18].

44

http://www.endocrinology.dk/index.php/3-calcium-og-knoglemetaboliske-sygdomme/3-osteoporose

http://www.endocrinology.dk/index.php/3-calcium-og-knoglemetaboliske-sygdomme/3-osteoporose

https://www.sundhed.dk/sundhedsfaglig/laegehaandbogen/undersoegelser-og-proever/undersoegelser/oevrige-undersoegelser/knogletaethedsmaalinger/



https://www.sst.dk/~/media/73D2379F2BA24D98866A921E9D418900.ashx

https://www.sst.dk/~/media/73D2379F2BA24D98866A921E9D418900.ashx

https://www.sundhed.dk/sundhedsfaglig/laegehaandbogen/endokrinologi/tilstande-og-sygdomme/knoglevaev-og-vitamin-d/osteoporose/

https://www.sundhed.dk/sundhedsfaglig/laegehaandbogen/endokrinologi/tilstande-og-sygdomme/knoglevaev-og-vitamin-d/osteoporose/

http://pro.medicin.dk/laegemiddelgrupper/grupper/160520

http://pro.medicin.dk/laegemiddelgrupper/grupper/160520


[31] A. Cranney, G. Wells, A. Willan, L. Griffith, N. Zytaruk, V. Robinson, D. Black, J. Adachi, B. Shea,

P. Tugwell, and G. Guyatt. II. Meta-analysis of alendronate for the treatment of postmenopausal

women. Endocrine Reviews, 23(4):508–516, 2002.

[32] U. A. Liberman, S. R. Weiss, J. Bröll, H. W. Minne, H. Quan, N. H. Bell, J. Rodriguez-Portales,

R. W. Downs, J. Dequeker, M. Favus, E. Seeman, R. R. Recker, T. Capizzi, A. C. Santora,

A. Lombardi, R. V. Shah, L. J. Hirsch, and D. B. Karpf. Effect of oral alendronate on bone

mineral density and the incidence of fractures in postmenopausal osteoporosis. New England

Journal of Medicine, 333(22):1437–1444, 1995.

[33] Min.medicin.dk. Alendronat - min.medicin.dk, 2020. URL https://min.medicin.dk/Medicin/

Praeparater/4579. [Access date: 2019-02-19].

[34] J. A. Cramer, D. T. Gold, S. L. Silverman, and E. M. Lewiecki. A systematic review of persistence

and compliance with bisphosphonates for osteoporosis. Osteoporosis International, 18(8):1023–

1031, 2007.

[35] R. Lindsay, J. H. Krege, F. Marin, L. Jin, and J. J. Stepan. Teriparatide for osteoporosis: Importance

of the full course. Osteoporosis International, 27(8):2395–2410, 2016.

[36] European Medicines Agency. EMA - FORSTEO. Technical report, European Medicines Agency,

2012.

[37] N. Napoli, B. L. Langdahl, Ö. Ljunggren, E. Lespessailles, G. Kapetanos, T. Kocjan, T. Nikolic,

P. Eiken, H. Petto, T. Moll, E. Lindh, and F. Marin. Effects of Teriparatide in Patients

with Osteoporosis in Clinical Practice: 42-Month Results During and After Discontinuation of

Treatment from the European Extended Forsteo® Observational Study (ExFOS). Calcified Tissue

International, 103(4):359–371, 2018.

[38] Lilly USA. Full prescribing information - Forteo. Technical report, Lilly USA, 2019.

[39] ProMedicin.dk. Teriparatid (osteoporose). 2019.

[40] R. L. Jilka, R. S. Weinstein, T. Bellido, P. Roberson, A. M. Parfitt, and S. C. Manolagas. Increased

bone formation by prevention of osteoblast apoptosis with parathyroid hormone. Journal of

Clinical Investigation, 104(4):439–446, 1999.

[41] N. Miyakoshi, Y. Kasukawa, T. A. Linkhart, D. J. Baylink, and S. Mohan. Evidence that anabolic

effects of PTH on bone require IGF-I in growing mice. Endocrinology, 142(10):4349–4356, 2001.

[42] E. Canalis, M. Centrella, W. Burch, and T. L. McCarthy. Insulin-like growth factor I mediates

selective anabolic effects of parathyroid hormone in bone cultures. Journal of Clinical Investigation,

83(1):60–65, 1989.

[43] D. T. Gold, B. S. Pantos, D. N. Masica, D. A. Misurski, and R. Marcus. Initial experience with

teriparatide in the United States. Current Medical Research and Opinion, 22(4):703–708, 2006.

[44] Pro.medicin, L. Rejnmark, and B. L. Hansen. Teriparatid, 2019. URL https://pro.medicin.dk/

Laegemiddelgrupper/grupper/315021. [Access date: 2019-02-17].

[45] European Medicines Agency. Terrosa - EMA, 2019. URL https://www.ema.europa.eu/en/

medicines/human/EPAR/terrosa. [Access date: 2020-05-28].

[46] European Medicines Agency. Movymia - EMA, 2019. URL https://www.ema.europa.eu/en/

medicines/human/EPAR/movymia. [Access date: 2020-05-28].

[47] The Danish Medicines Agency. Medicinpriser.dk, 2020. URL https://medicinpriser.dk/

default.aspx. [Access date: 2020-03-17].

[48] N. Zethraeus, W. B. Sedrine, F. Caulin, S. Corcaud, H. J. Gathon, M. Haim, O. Johnell, and B. Jo.

International Review Article Models for Assessing the Cost-Effectiveness of the Treatment and

Prevention of Osteoporosis. Osteoporosis international : a journal established as result of cooperation

45

https://min.medicin.dk/Medicin/Praeparater/4579

https://min.medicin.dk/Medicin/Praeparater/4579

https://pro.medicin.dk/Laegemiddelgrupper/grupper/315021

https://pro.medicin.dk/Laegemiddelgrupper/grupper/315021

https://www.ema.europa.eu/en/medicines/human/EPAR/terrosa

https://www.ema.europa.eu/en/medicines/human/EPAR/terrosa

https://www.ema.europa.eu/en/medicines/human/EPAR/movymia

https://www.ema.europa.eu/en/medicines/human/EPAR/movymia

https://medicinpriser.dk/default.aspx

https://medicinpriser.dk/default.aspx


between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA,

13:841–857, 2002.

[49] D. Andrew. Carrying NICE over the threshold, 2015. URL https:

//www.nice.org.uk/news/blog/carrying-nice-over-the-threshold?fbclid=

IwAR0G6lhBWNB7xflDcehZdaSvmuPC5duLmCITjlOkA2jK-L0XXz79THlbmP8. [Access date: 2020-05-

13].

[50] M. Hiligsmann, O. Bruyère, O. Ethgen, H. J. Gathon, and J. Y. Reginster. Lifetime absolute risk

of hip and other osteoporotic fracture in Belgian women. Bone, 43(6):991–994, 2008.

[51] M. Hiligsmann and J. Y. Reginster. Cost effectiveness of denosumab compared with

oral bisphosphonates in the treatment of post-menopausal osteoporotic women in Belgium.

PharmacoEconomics, 29(10):895–911, 2011.

[52] N. Freemantle, C. Cooper, A. Diez-Perez, M. Gitlin, H. Radcliffe, S. Shepherd, and C. Roux.

Response to comments on: Results of indirect and mixed treatment comparison of fracture

efficacy for osteoporosis treatments: A meta-analysis. Osteoporosis International, 24(6):1931–1932,

2013.

[53] T. Mori, C. J. Crandall, and D. A. Ganz. Cost-Effectiveness of Sequential Teriparatide/Alen-

dronate Versus Alendronate-Alone Strategies in High-Risk Osteoporotic Women in the US: An-

alyzing the Impact of Generic/Biosimilar Teriparatide. JBMR Plus, 3(11), 2019.

[54] O. Johnell, J. A. Kanis, A. Odén, I. Sernbo, I. Redlund-Johnell, C. Petterson, C. De Laet, and

B. Jönsson. Mortality after osteoporotic fractures. Osteoporosis International, 15(1):38–42, 2004.

[55] Statistics Denmark. Consumer Price Index, 2019. URL https://www.dst.dk/da/Statistik/

emner/priser-og-forbrug/forbrugerpriser/forbrugerprisindeks. [Access date: 2020-04-

16].

[56] The Danish Health Data Authority. Interactive DRG, 2020. URL http://interaktivdrg.

sundhedsdata.dk. [Access date: 2020-03-26].

[57] M. Hiligsmann, O. Ethgen, F. Richy, and J. Y. Reginster. Utility values associated with

osteoporotic fracture: A systematic review of the literature. Calcified Tissue International, 82(4):

288–292, 2008.

[58] T. Peasgood, K. Herrmann, J. A. Kanis, and J. E. Brazier. An updated systematic review of health

state utility values for osteoporosis related conditions. Osteoporosis International, 20(6):853–868,

2009.

[59] M. Drummond. Methods for Economic Evaluation of Health Care Programmes. Oxford, fourth edition,

2015.

[60] A. Brennan and R. Akehurst. Modelling in health economic evaluation: What is its place? What

is its value? PharmacoEconomics, 17(5):445–459, 2000.

[61] T. A. Sheldon. Problems of using modelling in the economic evaluation of health care. Health

Economics, 5(1):1–11, 1996.

[62] J. Soto. Health economic evaluations using decision analytic modeling. Principles and practices

- Utilization of a checklist to their development and appraisal. International journal of technology

assessment in health care, 18(1):94–111, 2002.

[63] M. Hiligsmann, O. Ethgen, O. Bruyère, F. Richy, H. J. Gathon, and J. Y. Reginster. Development

and validation of a markov microsimulation model for the economic evaluation of treatments in

osteoporosis. Value in Health, 12(5):687–696, 2009.

[64] F. A. Sonnenberg and J. R. Beck. Markov Models in Medical Decision Making: A Practical Guide.

Medical Decision Making, 13(4):322–338, 1993.

46

https://www.nice.org.uk/news/blog/carrying-nice-over-the-threshold?fbclid=IwAR0G6lhBWNB7xflDcehZdaSvmuPC5duLmCITjlOkA2jK-L0XXz79THlbmP8



https://www.dst.dk/da/Statistik/emner/priser-og-forbrug/forbrugerpriser/forbrugerprisindeks

https://www.dst.dk/da/Statistik/emner/priser-og-forbrug/forbrugerpriser/forbrugerprisindeks

http://interaktivdrg.sundhedsdata.dk

http://interaktivdrg.sundhedsdata.dk


[65] E. Olariu, K. K. Cadwell, E. Hancock, D. Trueman, and H. Chevrou-Severac. Current

recommendations on the estimation of transition probabilities in Markov cohort models for use

in health care decision-making: A targeted literature review. ClinicoEconomics and Outcomes

Research, 9:537–546, 2017.

[66] A. N.A. Tosteson, B. Jönsson, D. T. Grima, B. J. O’Brien, D. M. Black, and J. D. Adachi.

Challenges for model-based economic evaluations of postmenopausal osteoporosis interventions.

Osteoporosis International, 12(10):849–857, 2001.

[67] T. Yoshizawa, T. Nishino, I. Okubo, and M. Yamazaki. Cost-effectiveness analysis of drugs for

osteoporosis treatment in elderly Japanese women at high risk of fragility fractures: comparison

of denosumab and weekly alendronate. Archives of Osteoporosis, 13(1), 2018.

[68] F. Borgström, O. Ström, F. Marin, A. Kutahov, and Ö. Ljunggren. Cost effectiveness of teriparatide

and PTH(1-84) in the treatment of postmenopausal osteoporosis. Journal of Medical Economics, 13

(3):381–392, 2010.

[69] M. Hiligsmann, S. A. Williams, L. A. Fitzpatrick, S. S. Silverman, R. Weiss, and J. Y. Reginster.

Cost-effectiveness of sequential treatment with abaloparatide vs. teriparatide for United States

women at increased risk of fracture. Seminars in Arthritis and Rheumatism, 49(2):184–196, 2019.

[70] S. Taheri, F. Mirzayeh Fashami, F. Peiravian, and P. Yousefi. Teriparatide in the Treatment of

Severe Postmenopausal Osteoporosis: A Cost-Utility Analysis. Iranian journal of pharmaceutical

research : IJPR, 18(2):1073–1085, 2019.

[71] The Danish Ministry of Finance. Den samfundsøkonomiske diskonteringsrente. Technical

Report november, The Danish Ministry of Finance, 2018. URL file:///C:/Users/Laurynas/

Downloads/Dokumentationsnotat_Densamfundsoekonomiskediskonteringsrente.pdf.

[72] L. J. Melton, M. Thamer, N. F. Ray, J. K. Chan, C. H. Chesnut, T. A. Einhorn, C. C. Johnston, L. G.

Raisz, S. L. Silverman, and E. S. Siris. Fractures attributable to osteoporosis: Report from the

national osteoporosis foundation. Journal of Bone and Mineral Research, 12(1):16–23, 1997.

[73] J. R. Beck and S. G. Pauker. The Markov Process in Medical Prognosis. Medical Decision Making,

3(4), 1983.

[74] C. M. Klotzbuecher, P. D. Ross, P. B. Landsman, T. A. Abbott, and M. Berger. Patients with

Prior Fractures Have an Increased Risk of Future Fractures: A Summary of the Literature and

Statistical Synthesis. Journal of Bone and Mineral Research, 15(4):721–739, 2010.

[75] Statistics Denmark. Statistikbanken, 2019. URL https://statistikbanken.dk/statbank5a/

default.asp?w=1280. [Access date: 2020-05-28].

[76] Statistikbanken. DOD - Døde efter køn og alder, 2019. [Access date: 2020-03-25].

[77] J. A. Cauley, D. E. Thompson, K. C. Ensrud, J. C. Scott, and D. Black. Risk of mortality following

clinical fractures. Osteoporosis International, 11(7):556–561, 2000.

[78] The Danish Health Data Authority. DRG-charges, 2020. URL https://sundhedsdatastyrelsen.

dk/da/afregning-og-finansiering/takster-drg/takster-2020. [Access date: 2020-04-07].

[79] HMSA. HMSA - Provider Resource Center, 2018. URL https://hmsa.com/portal/provider/

zav_pel.fh.DIA.650.htm. [Access date: 2020-04-22].

[80] S. Kold, B. Christensen, J. B. Lauritzen, and H. C. Kjeldsen. Femur, hoftenært brud - Sund-

hed.dk, 2019. URL https://www.sundhed.dk/sundhedsfaglig/laegehaandbogen/ortopaedi/

tilstande-og-sygdomme/knoglebrud/femur-hoftenaert-brud/. [Access date: 2020-05-28].

[81] North Denmark Region. Total primary hip alloplasty, 2018. URL https://pri.rn.dk/Sider/

8929.aspx. [Access date: 2020-04-16].

[82] the Danish Medical Association. Overenskomst om almen praksis. Vasa, 3(april):1–9, 2020.

47

https://statistikbanken.dk/statbank5a/default.asp?w=1280

https://statistikbanken.dk/statbank5a/default.asp?w=1280

https://sundhedsdatastyrelsen.dk/da/afregning-og-finansiering/takster-drg/takster-2020

https://sundhedsdatastyrelsen.dk/da/afregning-og-finansiering/takster-drg/takster-2020

https://hmsa.com/portal/provider/zav_pel.fh.DIA.650.htm

https://hmsa.com/portal/provider/zav_pel.fh.DIA.650.htm

https://www.sundhed.dk/sundhedsfaglig/laegehaandbogen/ortopaedi/tilstande-og-sygdomme/knoglebrud/femur-hoftenaert-brud/

https://www.sundhed.dk/sundhedsfaglig/laegehaandbogen/ortopaedi/tilstande-og-sygdomme/knoglebrud/femur-hoftenaert-brud/

https://pri.rn.dk/Sider/8929.aspx

https://pri.rn.dk/Sider/8929.aspx


[83] Sundhed.dk. Lægehåndbogen, 2019. URL https://www.sundhed.dk/

sundhedsfaglig/laegehaandbogen/ortopaedi/tilstande-og-sygdomme/knoglebrud/

vertebralt-kompressionsbrud/. [Access date: 2020-03-30].

[84] North Jutland Orthopaedic Surgery. Stabilising back surgery. Technical report, North Denmark

Region, 2020.

[85] Osteoporoseforeningen. Knogleskørhed - en almindelig sygdom hos mænd, 2020. URL https:

//www.osteoporose-f.dk/stoette-og-hjaelp/osteoporose-og-maend/. [Access date: 2020-

03-17].

[86] The Danish Health Data Authority. LPR - Landspatientregisteret (National Patient Registry),

2018. URL www.esundhed.dk. [Access date: 2020-03-26].

[87] Lægehåndbogen. Sundhed.dk - håndledsbrud, 2018. URL https://www.sundhed.

dk/sundhedsfaglig/laegehaandbogen/ortopaedi/tilstande-og-sygdomme/knoglebrud/

haandledsbrud/. [Access date: 2020-04-28].

[88] S. E. Gabriel, S. E. Gabriel, A. N.A. Tosteson, C. L. Leibson, C. S. Crowson, G. R. Pond,

C. S. Hammond, and L. J. Melton. Direct medical costs attributable to osteoporotic fractures.

Osteoporosis International, 13(4):323–330, 2002.

[89] P. Vestergaard. Mail correspondance,, 2020.

[90] L. Si, T. M. Winzenberg, B. De Graaff, and A. J. Palmer. A systematic review and meta-analysis

of utility-based quality of life for osteoporosis-related conditions. Osteoporosis International, 25

(8):1987–1997, 2014.

[91] P. Lips and N. M. van Schoor. Quality of life in patients with osteoporosis. Osteoporosis

international : a journal established as result of cooperation between the European Foundation for

Osteoporosis and the National Osteoporosis Foundation of the USA, 16(5):447–455, 2005.

[92] M. C. Weinstein, G. Torrance, and A. McGuire. QALYs: The basics. Value in Health, 12(SUPPL.

1):S5–S9, 2009.

[93] L. Lundberg, M. Johannesson, D. G. L. Isacson, and L. Borgquist. Health-state utilities in a

general population in relation to age, gender and socioeconomic factors. European Journal of

Public Health, 9(3):211–217, 1999.

[94] A. D. M. Briggs, L. J. Cobiac, J. Wolstenholme, and P. Scarborough. PRIMEtime CE: A multistate

life table model for estimating the cost-effectiveness of interventions affecting diet and physical

activity. BMC Health Services Research, 19(1):1–19, 2019.

[95] P. W. Sullivan, J. F. Slejko, M. J. Sculpher, and V. Ghushchyan. Catalogue of EQ-5D scores for the

United Kingdom. Medical Decision Making, 31(6):800–804, 2011.

[96] A. Briggs. Probabilistic analysis of cost-effectiveness models: Statistical representation of

parameter uncertainty. Value in Health, 8(1):1–2, 2005.

[97] L. Zaninetti. A right and left truncated gamma distribution with application to the stars.

Advanced Studies in Theoretical Physics, 7(23):1139–1147, 2013.

[98] M. H. Murad, Matthew T. Drake, Rebecca J. Mullan, Karen F. Mauck, Louise M. Stuart,

Melanie A. Lane, Nisrin O. Abu Elnour, Patricia J. Erwin, Ahmad Hazem, Milo A. Puhan, and

Victor M. Montori. Comparative effectiveness of drug treatments to prevent fragility fractures:

A systematic review and network meta-analysis. Journal of Clinical Endocrinology and Metabolism,

97(6):1871–1880, 2012.

[99] M. Godwin, L. Ruhland, I. Casson, S. MacDonald, D. Delva, R. Birtwhistle, M. Lam, and

R. Seguin. Pragmatic controlled clinical trials in primary care: The struggle between external

and internal validity. BMC Medical Research Methodology, 3:1–7, 2003.

48

https://www.sundhed.dk/sundhedsfaglig/laegehaandbogen/ortopaedi/tilstande-og-sygdomme/knoglebrud/vertebralt-kompressionsbrud/



https://www.osteoporose-f.dk/stoette-og-hjaelp/osteoporose-og-maend/

https://www.osteoporose-f.dk/stoette-og-hjaelp/osteoporose-og-maend/

www.esundhed.dk

https://www.sundhed.dk/sundhedsfaglig/laegehaandbogen/ortopaedi/tilstande-og-sygdomme/knoglebrud/haandledsbrud/




[100] D. M. J. Naimark, M. Bott, and M. Krahn. The half-cycle correction explained: Two alternative

pedagogical approaches. Medical Decision Making, 28(5):706–712, 2008.

[101] TreeAge Software Inc. TreeAge Pro 2020 User’s Manual. Technical report, TreeAge Pro, 2020.

[102] World Health Organization. Recommendations for Health Economics Evaluations of Interven-

tions in Osteoporosis. Technical report, WHO, 1999.

[103] P. Kothawala, E. Badamgarav, S. Ryu, R. M. Miller, and R. J. Halbert. Systematic Review

and Meta-analysis of Real-World Adherence to Drug Therapy for Osteoporosis. Mayo Clinic

Proceedings, 82(12):1493–1501, 2007.

[104] I. Imaz, P. Zegarra, J. González-Enríquez, B. Rubio, R. Alcazar, and J. M. Amate. Poor

bisphosphonate adherence for treatment of osteoporosis increases fracture risk: Systematic

review and meta-analysis. Osteoporosis International, 21(11):1943–1951, 2010.

[105] E. Durden, L. Pinto, L. Lopez-Gonzalez, P. Juneau, and R. Barron. Two-year persistence

and compliance with osteoporosis therapies among postmenopausal women in a commercially

insured population in the United States. Archives of Osteoporosis, 12(1):1–9, 2017.

[106] D. S. Cobden, L. W. Niessen, F. F. H. Rutten, and W. K. Redekop. Modeling the economic

impact of medication adherence in type 2 diabetes: A theoretical approach. Patient Preference and

Adherence, 4:283–290, 2010.

[107] M. Hadi, P. Swinburn, L. Nalysnyk, A. Hamed, and A. Mehta. A health state utility valuation

study to assess the impact of treatment mode of administration in Gaucher disease. Orphanet

journal of rare diseases, 13(1):159, 2018.

49

A. Appendix

A.1. Cost Calculations

This section provides the full calculations that are the basis of the final cost estimates

used in the model. The full descriptions with the associated sources can be seen in

section 3.3.2.3

A.1.1. Costs of Treatment

The costs of pharmacological treatment with teriparatide and alendronate were

calculated from the prices of one package of each drug from The Danish Medicines

Agency [47]. The price of one package of teriparatide comprising 28 doses was DKK

2,539. One dosage is injected every day. The annual cost of teriparatide treatment was

calculated as:

2,539/28 = DKK 90.67857 a day

90.6786*365 days = DKK 33,097.678 annually

For alendronate the price for one package containing 14 units was DKK 128.75.

A patient consumes one unit once a week. The annual cost of treatment with

alendronate was calculated as:

128.75/14 = DKK 9.19642 per unit

9.19642*(365 days/7) = DKK 479.527 annually

A.1.2. Costs of a Hip Fracture

It was found that all hip fractures require surgery, of which 75.4% of hip fractures

were treated by internal fixation and the remaining 25.6% were treated by primary

alloplasty. The 2020 DRG-charge of internal fixation and primary hip alloplasty of

67,991 and 51,979, respectively, were applied. The average cost of hip surgery was

calculated as:

(67,991*75.4)+(51,979*24.6)/100 = DKK 64,052.048 annually

Following a hip fracture, some costs are accumulated after discharge and are therefore

not included in the DRG-charge. These costs include treatment of the wound at a

50

A Appendix Aalborg University

GP and one follow-up visit at the ambulatory. The costs of treatment of the wound,

removal of staples at the GP, and follow-up at the ambulatory for orthopaedic surgery

of DKK 199.34, DKK 145.46, and DKK 1,512, respectively, were added to the average

cost of hip surgery, and the total mean cost of a hip fracture was calculated:

64,052.048+199.34+145.46+1,512= DKK 65,908.8

DKK 65,908.8 was the final mean cost estimate of a hip fracture.

A.1.3. Costs of a Vertebral Fracture

As every clinical vertebral fracture was assumed to require surgery, the 2020 DRG-

charge of back/neck surgery of DKK 92,307 was applied for each vertebral fracture.

The costs of one consultation (DKK 145.46), removal of staples (DKK 199.34), and

three follow-up visits including X-rays at the ambulatory of DKK 1,512 and DKK 747,

respectively, were added to the cost of back/neck surgery:

92,307+145.46+199.34+(1512*3)+(747*3) = DKK 99,428.8

The final mean cost of a vertebral fracture was estimated at DKK 99,428.8.

A.1.4. Costs of a Forearm Fracture

The numbers of forearm fractures in 2016 in both the general population and in people

suffering from osteoporosis can be seen in Table A.1.

Forearm fractures, 2016 Fractures in osteoporosis patients Fractures in the general population Total

Diagnosis code S522 112 1,266 1,378

Diagnosis code S525 4,442 36,865 41,307

Diagnosis code S526 459 5,512 5,971

Total: 5,013 43,643 48,656

Table A.1: This table gives an overview of the numbers of fractures of the forearm sustainedby people suffering from osteporosis and in the general population. All numbers are from year2016 and the information was drawn from a report by The Danish Health Data Authority[19].

To identify 50% of all the fractures, 48,656 was divided by two, since it was assumed

half of all the forearm fractures occur in women.

48,656/2 = 24,328

Meaning 24,328 out of the 48,656 forearm fractures occurred in women.

51


The number of forearm fractures occurring in women suffering from osteoporosis was

needed as well. It was assumed that 2/3 fractures occured in women and 1/3 was

sustained by men. The total number of forearm fractures sustained by people with

osteoporosis was 5,013 as can be seen from Table A.1. In order to identify 2/3 of the

5,013 fracture the following calculation was performed:

5013/100*(100/3*2) = 3,342

Meaning 3,342 out of the 5012 forearm fractures that occurred in the population

suffering from osteoporosis were sustained by women.

The percentage of the fractures occurring in women suffering from osteoporosis could

then be calculated from the number of fractures occurring in women in the general

population:

3,342/24328*100 = 13.7%

Data on men and women discharged from hospital after a forearm fracture and

patients visiting the emergency ward was obtained through the National Patient

Register [86] and can be seen in Table A.2.

Acute ambulant patients (DS52) 11,550

Discharged patients (DS52) 3,714

Table A.2: Total numbers of both discharged and acute ambulant patients within the diagnosiscode S52.

The 13.7% were applied to the total number of both acute ambulant patients within

the diagnosis code DS52 (fracture of the elbow and forearm) and the total number of

patients that were discharged within the same diagnosis code (DS52) which can be

seen in Table A.2.

Acute ambulant: 13.7% of 11,550 = 1582

Discharged patients: 13.7% of 3,714 = 509

Distribution: 1582/509 = 3.1099

Which means women were being treated 3.1099 times more often as acute ambulant

patients than they were admitted.

The cost of being treating with plaster or splint was estimated using interactive DRG-

charges from 2020 and was found to be DKK 1,952 [56]. And furthermore, the cost

52


of being treated surgically was obtained through The Danish Health Data Authority

[78]. The DRG-charge 08MP24 of forearm fracture surgery was found to be DKK

34,854 in 2020.

It was assumed that all patients that were discharged carried a cost of DKK 34,854

from being treated surgically, and it was furthermore assumed all acute ambulant

patients carried the cost of splint or plaster treatment of DKK 1,952 found through

interactive DRG. The interactive DRG charge was found to be DKK 1,952 since no

matter what fracture of the forearm, gender, and age was chosen within the system,

the cost was still DKK 1,952. When taking into account that women are being treated

3.1099 times more often in the ambulatory, the average estimated inpatient cost was:

34,854+(1,952*3.1099)/4.1099= DKK 9957.55

A follow-up visit at the ambulatory for orthopaedic surgery of DKK 1,512 was

included for each forearm fracture, and moreover, the DRG-charge of DKK 507 for an

uncomplicated x-ray was added for the patients who were treated surgically. When

taking into account that women were being treated 3.1099 times more often in the

ambulatory, the average cost of a follow-up visit was DKK 1,635.36

1,512+(507/4.1099) = 1,635.36

The final weighted mean cost of a forearm fracture was estimated to be:

9,957.55+1,635.36= DKK 11,592.91

A.1.5. Cost of an "Other" Fracture

It was assumed the cost of an "other" fracture could be estimated from taking 25% of

the costs related to a hip fracture:

DKK 65,908.8*0.25 = DKK 16,477.2

The final mean cost of an "other" fracture was therefore estimated at DKK 16,477.2.

53


A.2. The Markov Model - The Teriparatide Branch

Figure A.1: The figure depicts the Markov node and the associated branches for teriparatidein the base CUA. To the left of this image was a decision node called "choice of treatment forosteoporosis".

54


A.3. The Markov Model - The Alendronate Branch

Figure A.2: The figure depicts the Markov node and the associated branches for alendronatein the base case CUA. To the left of this image was a decision node called "choice of treatmentfor osteoporosis".

55


A.4. Full Tornado Diagram - CUA

Figure A.3: The figure shows an ICER tornado diagram using all parameters, except the fourutility values (well, forearm, "other" (subsequent years), and dead). The red parts of the barsrepresent the range of the ICER when the parameter in question is higher than the base casevalue, and the contrary is the case for the blue parts.

56


A.5. Summary Reports - Base Case

Stage % - Well % - Post-fracture (hip) % - Post-fracture (vertebral) % - Post-fracture (forearm) % - Post-fracture (others) % - Dead Cum Costs Cum Utility Cum Effects

0 1 0 0 0 0 0 749.3037673 0.754869815 0.01045602

1 0.987564084 0.000607509 0.00093832 0.003546566 0.00526654 0.002076981 1471.172207 1.479146775 0.020603276

2 0.984002086 0.001192422 0.001845257 0.003577589 0.005291101 0.004091545 2164.511429 2.173347801 0.030358062

3 0.979551164 0.001749472 0.00271351 0.003565476 0.005272914 0.007147463 2829.707854 2.8376377 0.039724247

4 0.974873116 0.002279372 0.003543801 0.003549433 0.005249164 0.010505114 3467.68053 3.473981119 0.048713824

5 0.970012332 0.002782982 0.004337086 0.003532503 0.00522412 0.014110977 4133.249921 4.083628338 0.059123447

6 0.963431729 0.003406806 0.005426599 0.005118945 0.005227242 0.017388678 4399.960398 4.667397149 0.069143165

7 0.957887796 0.00399946 0.006465807 0.005112026 0.005209226 0.021325685 4656.11804 5.225258211 0.078757362

8 0.951791605 0.004559924 0.00745305 0.005083105 0.00517961 0.025932706 4901.932537 5.758938038 0.087974947

9 0.94556223 0.005090469 0.008391692 0.00505085 0.00514672 0.030758039 5137.736117 6.268889008 0.096809404

10 0.938317759 0.00558741 0.009275407 0.005017819 0.005113056 0.036688549 5519.584301 6.741555304 0.109781812

11 0.924660527 0.007541036 0.010739931 0.008941532 0.005342784 0.04277419 5888.186898 7.192243631 0.122311518

12 0.913784087 0.009383199 0.012108669 0.008938792 0.005312819 0.050472434 6241.687744 7.621895971 0.134313286

13 0.903097656 0.011115316 0.013391259 0.008837332 0.005251817 0.05830662 6580.503643 8.030617147 0.14580272

14 0.891942573 0.012735581 0.014583687 0.008734095 0.005190445 0.066813619 6904.914835 8.419513723 0.156791188

15 0.880014892 0.014241288 0.015682378 0.008626451 0.005126436 0.076308555 7256.224794 8.789093537 0.168287281

16 0.865878514 0.016056757 0.016830029 0.007331897 0.007305887 0.086596916 7592.309718 9.139505147 0.179267383

17 0.852147136 0.017734837 0.017876925 0.007216168 0.007204519 0.097820415 7913.109762 9.471786239 0.189737569

18 0.837697405 0.019271926 0.01882031 0.007101955 0.007090498 0.110017907 8218.869096 9.786695352 0.199707353

19 0.823129284 0.02068209 0.01967411 0.00698186 0.006970521 0.122562134 8510.056713 10.08506464 0.209193396

20 0.808705266 0.021976388 0.02044799 0.006860579 0.006849405 0.135160372 8958.748893 10.3473769 0.221693717

21 0.786935559 0.022295218 0.021459838 0.008775442 0.008182735 0.152351208 9384.947559 10.59445881 0.233562834

22 0.769043529 0.022517421 0.022299091 0.008639696 0.008031835 0.169468429 9788.056567 10.82639942 0.244775941

23 0.7491848 0.022574147 0.022906271 0.008446108 0.007851124 0.189037551 10167.85962 11.04323816 0.255329545

24 0.728080488 0.022495398 0.023312178 0.00822952 0.007649462 0.210232954 10524.63639 11.24572782 0.265233766

25 0.705853655 0.022294207 0.023532343 0.007998794 0.007434759 0.232886241 10902.45187 11.433862 0.274969766

26 0.680198356 0.0236129 0.023224545 0.005430133 0.008958402 0.258575663 11254.96152 11.60833203 0.284042133

27 0.65410457 0.024528284 0.022825438 0.005201538 0.008618828 0.284721342 11583.25994 11.7695063 0.292488635

28 0.627676102 0.025085151 0.022333745 0.005001562 0.008287793 0.311615646 11888.14299 11.9181175 0.300330479

29 0.600460308 0.025309894 0.021740895 0.004799949 0.007953579 0.339735376 12170.21538 12.05449843 0.307583767

30 0.571844474 0.02521325 0.021031564 0.004592521 0.007609667 0.369708524 12457.16761 12.1671508 0.314885794

31 0.539742094 0.025596478 0.020139751 0.003926026 0.008531839 0.402063812 12720.27188 12.26931238 0.321578837

32 0.50759633 0.025546967 0.019164681 0.003712686 0.008077898 0.435901438 12959.7874 12.36093367 0.327671174

33 0.472953838 0.025027497 0.018049253 0.003492646 0.00759886 0.472877906 13175.68457 12.44243917 0.333162259

34 0.436524295 0.02410452 0.016821816 0.003255849 0.007083175 0.512210345 13368.33793 12.51418246 0.338061765

35 0.398745667 0.022835018 0.01550256 0.003006579 0.006540408 0.553369767 13621.66784 12.5766638 0.344477795

36 0.354610323 0.023311868 0.014466506 0.003113017 0.009643113 0.594855173 13846.49277 12.63001421 0.350170373

37 0.312957676 0.022844456 0.013217124 0.002830183 0.008764123 0.639386439 14040.60762 12.67524705 0.35508392

38 0.274198511 0.021776515 0.011929103 0.002503153 0.007749657 0.681843061 14206.48228 12.71269829 0.359281457

39 0.23463133 0.020005117 0.010486222 0.002194662 0.006794079 0.725888589 14344.83837 12.74337043 0.36278181

40 0.199142012 0.018005817 0.009109107 0.001881426 0.005823268 0.766038369 14502.94291 12.76784477 0.366780593

41 0.160829301 0.016694499 0.007983605 0.002216406 0.006843129 0.80543306 14632.38222 12.78688913 0.370053583

42 0.128492041 0.014801967 0.006772976 0.001853172 0.005701216 0.842378628 14734.5122 12.801303 0.372634412

43 0.100013405 0.01255798 0.005548264 0.001487681 0.004574387 0.875818283 14812.73832 12.81197327 0.374610092

44 0.076376929 0.010301848 0.004424858 0.001162017 0.003571737 0.904162611 14871.33895 12.81950143 0.376089399

45 0.055440025 0.007971788 0.003343659 0.000889722 0.002734042 0.929620764 14919.81162 12.82452956 0.377312493

46 0.037498594 0.005982084 0.002430434 0.000755507 0.00231425 0.951019131 14952.91599 12.82771612 0.378147581

47 0.024304926 0.004214319 0.001666808 0.000527056 0.001609473 0.967677419 14974.21053 12.8297908 0.378684494

48 0.01635966 0.003010723 0.001165861 0.000345438 0.001053673 0.978064645 14988.2119 12.83096586 0.379037317

49 0.009432306 0.00186213 0.000706799 0.00023151 0.000706447 0.987060808 14996.27155 12.83163071 0.379240389

50 0.005498627 0.00114094 0.000425996 0.000136879 0.000416677 0.99238088 15000.87007 12.83200578 0.379356212

51 0.003208569 0.000692716 0.000255126 7.99742E-05 0.000243389 0.995520227 15000.87007 12.83200578 0.379356212

Table A.3: The summary report related to the alendronate branch in the base case CUA.

57


Stage % - Well % - Post-fracture (hip) % - Post-fracture (vertebral) % - Post-fracture (forearm) % - Post-fracture (others) % - Dead Cum Costs Cum Utility Cum Effects

0 1 0 0 0 0 0 33264.54222 0.75520419 0.00561328

1 0.992406824 0.000567008 0.000562992 0.001038019 0.003375987 0.00204917 65185.08866 1.479858478 0.011030253

2 0.989343891 0.001110376 0.001105576 0.001040001 0.003379016 0.00402114 65781.50182 2.174480739 0.016235769

3 0.985320891 0.001627644 0.001625355 0.001036834 0.003368708 0.007020568 66353.50189 2.839238956 0.021232554

4 0.981061503 0.002119535 0.002122768 0.001032628 0.003355039 0.010308527 66901.91352 3.476101278 0.026027268

5 0.976613873 0.002586873 0.002598372 0.001028167 0.003340544 0.013832172 67457.67183 4.086389647 0.031324242

6 0.97174205 0.003165672 0.003251998 0.001490589 0.003344054 0.017005637 67990.75117 4.670866584 0.03641222

7 0.966771493 0.003714594 0.003875474 0.00148554 0.003330677 0.020822222 68501.65215 5.229502054 0.041292955

8 0.961212761 0.004233469 0.004468393 0.001477965 0.003313682 0.02529373 68649.42406 5.764024119 0.045971373

9 0.95550942 0.004724456 0.005032749 0.001469477 0.003294649 0.029969248 68791.09712 6.274884524 0.050454552

10 0.948777993 0.005184166 0.005564714 0.001460761 0.003275107 0.035737258 69032.97693 6.748637738 0.056950763

11 0.93890916 0.006991803 0.006447896 0.002604584 0.00342434 0.041622217 69265.44622 7.200503165 0.063192575

12 0.928954011 0.008690179 0.007272645 0.00258877 0.003398252 0.049096142 69488.15972 7.631419259 0.069168724

13 0.919059344 0.01028642 0.008047109 0.002561477 0.003362375 0.056683275 69701.44322 8.041487789 0.074888427

14 0.908667964 0.011779191 0.008768845 0.002534198 0.003326565 0.064923236 69905.50479 8.431814186 0.080357719

15 0.897469754 0.013166101 0.00943557 0.002505571 0.00328898 0.074134024 70133.61447 8.802923581 0.08652206

16 0.884087449 0.014838365 0.010133987 0.002131771 0.004692152 0.084116276 70351.72237 9.154941717 0.092412236

17 0.871088686 0.016383783 0.010772992 0.0021035 0.004632959 0.09501808 70559.77055 9.488903007 0.098027943

18 0.857330757 0.01779928 0.011350961 0.002072637 0.004564968 0.106881397 70757.9449 9.805560649 0.103374594

19 0.843413259 0.019097936 0.011876114 0.002039942 0.004492945 0.119079804 70946.57618 10.10574154 0.108461477

20 0.82960724 0.020290057 0.012354133 0.002006843 0.004420038 0.131321688 71238.59684 10.37007146 0.115298583

21 0.811195047 0.020592258 0.01299415 0.00256998 0.005286648 0.147361917 71515.45189 10.61944553 0.121777469

22 0.794644283 0.020800281 0.013528659 0.002524333 0.005188456 0.163313988 71777.37783 10.85392092 0.127903419

23 0.775930017 0.020857911 0.013924822 0.002472951 0.005082796 0.181731503 72024.28332 11.07350137 0.133675016

24 0.755827182 0.020792852 0.014200547 0.002414883 0.004963393 0.201801143 72256.37514 11.27891088 0.139097726

25 0.734462611 0.02061691 0.0143645 0.002352446 0.004835023 0.22336851 72520.99357 11.47009568 0.145043655

26 0.708468883 0.021846526 0.01421127 0.001600597 0.005839137 0.248033587 72768.46119 11.64772898 0.150602311

27 0.682891281 0.02271474 0.014002407 0.001543755 0.00563947 0.273208347 72999.23013 11.81214418 0.155785104

28 0.65688351 0.023255971 0.013735359 0.001488071 0.00543605 0.299201039 73213.83193 11.964046 0.160604151

29 0.629932719 0.023492953 0.0134044 0.001431464 0.005229237 0.326509228 73412.66772 12.10373176 0.165068613

30 0.601390449 0.023434194 0.012999649 0.001372827 0.005015 0.355787882 73620.07175 12.21936403 0.169731363

31 0.56929877 0.02382668 0.01248283 0.001176341 0.005636068 0.387579312 73810.52186 12.32445742 0.174012523

32 0.536814417 0.023817871 0.011910714 0.00111585 0.005348557 0.42099259 73984.19598 12.41892037 0.177916385

33 0.501537298 0.023372304 0.011248012 0.001052339 0.005044084 0.457745964 74141.02628 12.50314821 0.181441472

34 0.464178886 0.022549558 0.010511694 0.000983408 0.004713609 0.497062845 74281.23691 12.57746375 0.184592869

35 0.425189991 0.021400786 0.00971385 0.000910371 0.004363466 0.538421535 74470.28673 12.64238431 0.188875627

36 0.381399175 0.021904704 0.009100687 0.000944951 0.006449905 0.580200577 74637.83469 12.69797942 0.192670505

37 0.338139244 0.021503837 0.008343886 0.000858439 0.005860815 0.625293779 74782.70965 12.74525863 0.195951403

38 0.297510853 0.020537912 0.007557692 0.000761775 0.00520068 0.668431088 74906.75459 12.78453098 0.198760232

39 0.255742404 0.018907522 0.006668342 0.000670464 0.004577236 0.713434032 75010.43994 12.81680246 0.201107788

40 0.218009593 0.017056562 0.005814627 0.000576863 0.003938091 0.754604263 75129.19689 12.84266872 0.203795994

41 0.178535912 0.015865182 0.005123054 0.000682274 0.004646507 0.795147072 75226.19975 12.8628847 0.205991047

42 0.143748946 0.01409602 0.004366159 0.000568511 0.003869166 0.833351199 75302.87687 12.87825774 0.207725621

43 0.112731003 0.011987829 0.003594471 0.000458621 0.003121048 0.868107028 75361.76463 12.88969544 0.209057414

44 0.086731915 0.009861511 0.002882003 0.000360257 0.002451496 0.897712817 75406.02407 12.89781005 0.210058146

45 0.063507259 0.007655937 0.002190554 0.000277516 0.00188837 0.924480363 75442.75609 12.90326661 0.210888389

46 0.043665168 0.005768717 0.001603645 0.000236931 0.001607947 0.947117593 75467.86818 12.90674965 0.211455819

47 0.028664258 0.004079023 0.001107422 0.000165383 0.001121736 0.964862177 75484.08451 12.90903354 0.21182214

48 0.019460104 0.002925491 0.000780028 0.000109096 0.000739827 0.975985453 75494.81175 12.91033871 0.212064409

49 0.011414658 0.001819152 0.000477058 7.38921E-05 0.000501135 0.985714105 75501.01495 12.91108386 0.212204478

50 0.006735068 0.001120515 0.000289972 4.38792E-05 0.000297454 0.991513113 75504.57986 12.91150816 0.21228496

51 0.003974989 0.000684408 0.00017523 2.59047E-05 0.000175602 0.994963866 75504.57986 12.91150816 0.21228496

Table A.4: The summary report related to the teriparatide branch in the base case CUA.

58


A.6. Tables Used in TreeAge When Altering the

Durations of the Effects of the Two Drugs

E teriparatid forearm E teriparatid hip E teriparatid other E teriparatid vertebral

Index Value Index Value Index Value Index Value

0 0.24 0 0.42 0 0.5 0 0.3

1 0.24 1 0.42 1 0.5 1 0.3

2 0.24 2 0.42 2 0.5 2 0.3

3 0.24 3 0.42 3 0.5 3 0.3

4 0.24 4 0.42 4 0.5 4 0.3

5 0.24 5 0.42 5 0.5 5 0.3

6 0.24 6 0.42 6 0.5 6 0.3

7 0.24 7 0.42 7 0.5 7 0.3

8 0.335 8 0.4925 8 0.5625 8 0.3875

9 0.43 9 0.565 9 0.625 9 0.475

10 0.525 10 0.6375 10 0.6875 10 0.5625

11 0.62 11 0.71 11 0.75 11 0.65

12 0.715 12 0.7825 12 0.8125 12 0.7375

13 0.81 13 0.855 13 0.875 13 0.825

14 0.905 14 0.9275 14 0.9375 14 0.9125

15 1 15 1 15 1 15 1

E alendronate forearm E alendronate hip E alendronate other E alendronate vertebral

Index Value Index Value Index Value Index Value

0 0.82 0 0.45 0 0.78 0 0.5

1 0.82 1 0.45 1 0.78 1 0.5

2 0.82 2 0.45 2 0.78 2 0.5

3 0.82 3 0.45 3 0.78 3 0.5

4 0.82 4 0.45 4 0.78 4 0.5

5 0.82 5 0.45 5 0.78 5 0.5

6 0.85 6 0.541666667 6 0.816666667 6 0.583333333

7 0.88 7 0.633333333 7 0.853333333 7 0.666666667

8 0.91 8 0.725 8 0.89 8 0.75

9 0.94 9 0.816666667 9 0.926666667 9 0.833333333

10 0.97 10 0.908333333 10 0.963333333 10 0.916666667

11 1 11 1 11 1 11 1

Table A.5: The table shows the values used for creating a linear decline in the effects of thedrugs. E; efficacy. For teriparatide, the values for all indices following index 15 was 1, andlikewise, all values after index 11 were 1 for alendronate, however, they are not shown in thetable in order to keep the table small. In the model, the teriparatide branch applies 8 stages ofthe effects of treatment with teriparatide (2 stages of teriparatide and 6 stages of alendronateto maintain the effect of teriparatide), and the effect declines linearly following stage 8 for 8stages. Likewise, in the alendronate branch, individuals are treated for 6 years, and the effectdeclines towards 1 during the 6 following cycles.

59


A.7. Tables Used in TreeAge Containing the Baseline

Probabilities of Dying and Baseline Utility

Table A.6: The table lists the baseline proba-bilities of dying at each stage in the model forpeople aged 50 through 100 years.

Probabilities - mortality

Index Value

0 0.00197989644

1 0.00186354407

2 0.00285765775

3 0.00311750600

4 0.00332838202

5 0.00292780860

6 0.00354452813

7 0.00418245189

8 0.00436841301

9 0.00547520334

10 0.00548325087

11 0.00706478695

12 0.00713589639

13 0.00778746315

14 0.00880230413

15 0.00960611707

16 0.01061375173

17 0.01171046876

18 0.01215509116

19 0.01229319096

20 0.01329753632

21 0.01335524350

22 0.01649210798

23 0.01885678782

24 0.02121513944

25 0.02548490594

26 0.02685498309

27 0.02883288881

28 0.03176601617

29 0.03603319676

30 0.04147312541

31 0.04634591602

32 0.05496662740

33 0.06373448858

34 0.07323091618

35 0.08035075161

36 0.09644619941

37 0.10344057194

38 0.12342163902

39 0.13080771980

40 0.15078733895

41 0.17091114884

42 0.19195179686

43 0.20696068013

44 0.24339314845

45 0.28008474576

46 0.31474597274

47 0.29474485910

48 0.38247863248

49 0.38247863248

50 0.38247863248

Table A.7: The table gives the baseline utilityvalues used in the model. The utility decrementassociated with suffering from osteoporosis (-0.0418) has been subtracted.

Baseline - utility

Index Value

0 0.7572

1 0.7572

2 0.7572

3 0.7562

4 0.7562

5 0.7562

6 0.7562

7 0.7552

8 0.7552

9 0.7552

10 0.7332

11 0.7332

12 0.7332

13 0.7322

14 0.7322

15 0.7322

16 0.7312

17 0.7312

18 0.7312

19 0.7312

20 0.6822

21 0.6822

22 0.6822

23 0.6812

24 0.6812

25 0.6812

26 0.6812

27 0.6802

28 0.6802

29 0.6802

30 0.6162

31 0.6162

32 0.6152

33 0.6152

34 0.6152

35 0.6152

36 0.6142

37 0.6142

38 0.6142

39 0.6132

40 0.6132

41 0.6132

42 0.6132

43 0.6122

44 0.6122

45 0.6122

46 0.6122

47 0.6112

48 0.6112

49 0.6112

50 0.6102

60


A.8. Tables Used in TreeAge Containing Fracture

Incidence Probabilities for Hip, Vertebral, Forearm,

And Other Fractures

Table A.8: The baseline probabilities of suffer-ing a hip fracture from 50 years-old (cycle 0)to 100 years-old (cycle 50) when suffering fromosteoporosis.

Incidence - hip fracture

Index Value

0 0.001423501

1 0.001423501

2 0.001423501

3 0.001423501

4 0.001423501

5 0.001762342

6 0.001762342

7 0.001762342

8 0.001762342

9 0.001762342

10 0.005318124

11 0.005318124

12 0.005318124

13 0.005318124

14 0.005318124

15 0.006367213

16 0.006367213

17 0.006367213

18 0.006367213

19 0.006367213

20 0.010079854

21 0.010079854

22 0.010079854

23 0.010079854

24 0.010079854

25 0.01567266

26 0.01567266

27 0.01567266

28 0.01567266

29 0.01567266

30 0.018929063

31 0.018929063

32 0.018929063

33 0.018929063

34 0.018929063

35 0.030549369

36 0.030549369

37 0.030549369

38 0.030549369

39 0.030549369

40 0.042265958

41 0.042265958

42 0.042265958

43 0.042265958

44 0.042265958

45 0.049018851

46 0.049018851

47 0.049018851

48 0.049018851

49 0.049018851

50 0.049018851

Table A.9: The baseline probabilities of suffer-ing a vertebral fracture from 50 years-old (cycle0) to 100 years-old (cycle 50) when sufferingfrom osteoporosis.

Incidence - vertebral fracture

Index Value

0 0.002004678

1 0.002004678

2 0.002004678

3 0.002004678

4 0.002004678

5 0.002723298

6 0.002723298

7 0.002723298

8 0.002723298

9 0.002723298

10 0.004203342

11 0.004203342

12 0.004203342

13 0.004203342

14 0.004203342

15 0.004573196

16 0.004573196

17 0.004573196

18 0.004573196

19 0.004573196

20 0.009109677

21 0.009109677

22 0.009109677

23 0.009109677

24 0.009109677

25 0.008528487

26 0.008528487

27 0.008528487

28 0.008528487

29 0.008528487

30 0.008582517

31 0.008582517

32 0.008582517

33 0.008582517

34 0.008582517

35 0.011432501

36 0.011432501

37 0.011432501

38 0.011432501

39 0.011432501

40 0.015846761

41 0.015846761

42 0.015846761

43 0.015846761

44 0.015846761

45 0.01839958

46 0.01839958

47 0.01839958

48 0.01839958

49 0.01839958

50 0.01839958

61


Table A.10: The baseline probabilities ofsuffering a forearm fracture from 50 years-old (cycle 0) to 100 years-old (cycle 50) whensuffering from osteoporosis.

Incidence - forearm fracture

Index Value

0 0.00432508

1 0.00432508

2 0.00432508

3 0.00432508

4 0.00432508

5 0.006298846

6 0.006298846

7 0.006298846

8 0.006298846

9 0.006298846

10 0.011310583

11 0.011310583

12 0.011310583

13 0.011310583

14 0.011310583

15 0.0097431

16 0.0097431

17 0.0097431

18 0.0097431

19 0.0097431

20 0.012684706

21 0.012684706

22 0.012684706

23 0.012684706

24 0.012684706

25 0.008881206

26 0.008881206

27 0.008881206

28 0.008881206

29 0.008881206

30 0.007970466

31 0.007970466

32 0.007970466

33 0.007970466

34 0.007970466

35 0.009029496

36 0.009029496

37 0.009029496

38 0.009029496

39 0.009029496

40 0.012523289

41 0.012523289

42 0.012523289

43 0.012523289

44 0.012523289

45 0.014555897

46 0.014555897

47 0.014555897

48 0.014555897

49 0.014555897

50 0.014555897

Table A.11: The baseline probabilities ofsuffering an "other" fracture from 50 years-old (cycle 0) to 100 years-old (cycle 50) whensuffering from osteoporosis.

Incidence - other fracture

Index Value

0 0.006751974

1 0.006751974

2 0.006751974

3 0.006751974

4 0.006751974

5 0.006789839

6 0.006789839

7 0.006789839

8 0.006789839

9 0.006789839

10 0.007149515

11 0.007149515

12 0.007149515

13 0.007149515

14 0.007149515

15 0.010326834

16 0.010326834

17 0.010326834

18 0.010326834

19 0.010326834

20 0.012557075

21 0.012557075

22 0.012557075

23 0.012557075

24 0.012557075

25 0.015605279

26 0.015605279

27 0.015605279

28 0.015605279

29 0.015605279

30 0.018368561

31 0.018368561

32 0.018368561

33 0.018368561

34 0.018368561

35 0.029634209

36 0.029634209

37 0.029634209

38 0.029634209

39 0.029634209

40 0.041002382

41 0.041002382

42 0.041002382

43 0.041002382

44 0.041002382

45 0.047537088

46 0.047537088

47 0.047537088

48 0.047537088

49 0.047537088

50 0.047537088

62


A.9. Tables Used in TreeAge for Excess Mortality

Following Hip and Vertebral in First and Subsequent

YearsTable A.12: The probabilities of dying duringthe first year after having suffered a hip fracturefrom 50 years-old (cycle 0) to 100 years-old(cycle 50).

Mortality - hip, first year

Index Value

0 0.051619988

1 0.051619988

2 0.051619988

3 0.051619988

4 0.051619988

5 0.051619988

6 0.051619988

7 0.051619988

8 0.051619988

9 0.051619988

10 0.051619988

11 0.051619988

12 0.051619988

13 0.051619988

14 0.051619988

15 0.051619988

16 0.051619988

17 0.051619988

18 0.051619988

19 0.051619988

20 0.150408812

21 0.150408812

22 0.150408812

23 0.150408812

24 0.150408812

25 0.150408812

26 0.150408812

27 0.150408812

28 0.150408812

29 0.150408812

30 0.150408812

31 0.150408812

32 0.150408812

33 0.150408812

34 0.150408812

35 0.150408812

36 0.150408812

37 0.150408812

38 0.150408812

39 0.150408812

40 0.150408812

41 0.150408812

42 0.150408812

43 0.150408812

44 0.150408812

45 0.150408812

46 0.150408812

47 0.150408812

48 0.150408812

49 0.150408812

50 0.150408812

Table A.13: The probabilities of dying duringthe first year after having suffered a vertebralfracture from 50 years-old (cycle 0) to 100years-old (cycle 50).

Mortality - vertebral, first year

Index Value

0 0.063869136

1 0.063869136

2 0.063869136

3 0.063869136

4 0.063869136

5 0.063869136

6 0.063869136

7 0.063869136

8 0.063869136

9 0.063869136

10 0.063869136

11 0.063869136

12 0.063869136

13 0.063869136

14 0.063869136

15 0.063869136

16 0.063869136

17 0.063869136

18 0.063869136

19 0.063869136

20 0.150408812

21 0.150408812

22 0.150408812

23 0.150408812

24 0.150408812

25 0.150408812

26 0.150408812

27 0.150408812

28 0.150408812

29 0.150408812

30 0.150408812

31 0.150408812

32 0.150408812

33 0.150408812

34 0.150408812

35 0.150408812

36 0.150408812

37 0.150408812

38 0.150408812

39 0.150408812

40 0.150408812

41 0.150408812

42 0.150408812

43 0.150408812

44 0.150408812

45 0.150408812

46 0.150408812

47 0.150408812

48 0.150408812

49 0.150408812

50 0.150408812

63


Table A.14: The probabilities of dying after thefirst year after having suffered a hip fracturefrom 50 years-old (cycle 0) to 100 years-old(cycle 50).

Mortality - hip, subsequent years

Index Value

0 0.04208861

1 0.04208861

2 0.04208861

3 0.04208861

4 0.04208861

5 0.04208861

6 0.04208861

7 0.04208861

8 0.04208861

9 0.04208861

10 0.04208861

11 0.04208861

12 0.04208861

13 0.04208861

14 0.04208861

15 0.04208861

16 0.04208861

17 0.04208861

18 0.04208861

19 0.04208861

20 0.123659005

21 0.123659005

22 0.123659005

23 0.123659005

24 0.123659005

25 0.123659005

26 0.123659005

27 0.123659005

28 0.123659005

29 0.123659005

30 0.123659005

31 0.123659005

32 0.123659005

33 0.123659005

34 0.123659005

35 0.123659005

36 0.123659005

37 0.123659005

38 0.123659005

39 0.123659005

40 0.123659005

41 0.123659005

42 0.123659005

43 0.123659005

44 0.123659005

45 0.123659005

46 0.123659005

47 0.123659005

48 0.123659005

49 0.123659005

50 0.123659005

Table A.15: The probabilities of dying afterthe first year after having suffered a vertebralfracture from 50 years-old (cycle 0) to 100years-old (cycle 50).

Mortality - vertebral, subsequent years

Index Value

0 0.033428495

1 0.033428495

2 0.033428495

3 0.033428495

4 0.033428495

5 0.033428495

6 0.033428495

7 0.033428495

8 0.033428495

9 0.033428495

10 0.033428495

11 0.033428495

12 0.033428495

13 0.033428495

14 0.033428495

15 0.033428495

16 0.033428495

17 0.033428495

18 0.033428495

19 0.033428495

20 0.081487716

21 0.081487716

22 0.081487716

23 0.081487716

24 0.081487716

25 0.081487716

26 0.081487716

27 0.081487716

28 0.081487716

29 0.081487716

30 0.081487716

31 0.081487716

32 0.081487716

33 0.081487716

34 0.081487716

35 0.081487716

36 0.081487716

37 0.081487716

38 0.081487716

39 0.081487716

40 0.081487716

41 0.081487716

42 0.081487716

43 0.081487716

44 0.081487716

45 0.081487716

46 0.081487716

47 0.081487716

48 0.081487716

49 0.081487716

50 0.081487716

64

a c -u a s t /a a o · medicine with industrial specialisation, medical market access master thesis...

Documents