08 pharmacoepidemiology

7/28/2019 08 Pharmacoepidemiology

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NG ICRI Pharmacoepidemiology

Pharmacoepidemiology


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Outline of presentation

Definitions

The importance of pharmacoepidemiology

Studies on drug use

Studies on drug effects

Signal generation

Risk quantification

Hypothesis testing

Problem solving

Applications of pharmacoepidemiology


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Definitions

Epidemiology-Study of distribution and

determinants of disease in populations

Clinical epidemiology:How to critically

evaluate medical literature and how to apply

principles of epidemiology to clinicalmedicine


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Pharmacoepidemiology: Definition - 1

Pharmacoepidemiology is the study of

Use of drugsEffect of drugs

in large numbers of subjects.


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Pharmacoepidemiology Definition2

Application of the principles of epidemiology

to drug use and drug effect in large numbers

patients


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Evolution of Pharmacoepidemiology as a science

1961Thalidomide disaster

Case reports of limb malformations in offspring of women.

Treated with thalidomide

Development of systems for Adverse Drug Reactions Monitoring.

Development of the science of Pharmacoepidemiology.


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The importance of pharmacoepidemiology- the

problem of ADRs

Account for 5% of all hospital admissions.

Occur in 10-20% of hospital inpatients.

Cause death in 0.1% of medical and 0.01% of surgical inpatients.

Adversely effect patients quality of life.

Cause patients to lose confidence in their doctors.

Increase costs of patients care.


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The importance of pharmacoepidemiology- the

inadequacies of clinical trials

For the investigation of certain drug events,

models are not possible e.g. pregnancy.

RCTs are often inadequate to answer questions

on safety.


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Aims of Pharmacoepidemiological studies

Signal generation

Risk quantification

Hypothesis testing


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Studies on drug use


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Drug utilization studies

WHO definition: The marketing, distribution, prescriptionand use of drugs in a society with the resultant medical,

social and economic consequences

Quantitative or Qualitative (DUR or drug utilization

reviews)

DURs focus on specific drugs or class of drugs

(4th generation cephalosporins, aminoglycosides)


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The concepts of DDD and PDD

The defined daily dose (DDD) is the estimated

average maintenance dose per day of a drug when

used for its major indication (e.g aspirin)

Expressed as DDDs/1000 population

In hospitals, DDDs/100 bed days, adjusted for

occupancy


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Prescribed daily dose -PDD

The prescribed daily dose or PDD is the average daily

dose of a drug that has actually been prescribed

Calculated from a representative sample of prescriptions


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The need for drug utilization studies

Indication of pattern of use of drugs

Early signals of irrational use of drugs

Allows comparisons between regions, countries

Interventions to improve drugs use

Continuous quality improvement


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Study of drug effects


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Aims of Pharmacoepidemiological studies?

Signal generation

Risk quantification

Hypothesis testing


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What is a signal?

Reported information on a possible causal relationshipbetween an adverse event and a drug, the relationship

being unknown or incompletely documented previously.

Usually more than one report is required to generate a

signal depending upon the seriousness of the event and

quality of the information.


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Rawlins and Thompson classification -1991

Type A Predictable (Augmented)

Dose-dependent

Related to the drugs

pharmacological properties.

Diarrhea with antibiotic

use.

Type B Bizarre, unpredictable.

Dose-independent(idiosyncratic).

Unrelated

Hypersensitivity withpenicillin.


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Methods of signal generation


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Spontaneous reporting - 1

A system by which practicing clinicians are encouraged to

report any and all adverse events with a drug

Reports complied at the National Centre

Reports from National Centers are then sent to the

Uppsala Monitoring Centre.


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Spontaneous reporting:- Advantages

Early warning signals

Relatively inexpensive

Do not interfere with clinical practice


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Spontaneous reporting: Disadvantages

Information inadequate, incomplete, notverifiable

Cause- effect difficult to establish

Voluntary, thus under reporting

Incidence and prevalence difficult to calculate


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Prescription Event monitoring - 1

Used for both signal generation and risk quantification

Used to study large cohorts of drugs

500018,000 prescriptions from prescribers studied

Information:

All adverse events

Death from any cause

Hospitalization Fetal abnormalities

Changes in laboratory values

Advantages: Calculation of incidence


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Prescription event monitoringwhen?

New chemical entity

Predicted widespread use

Identified but unquantified risks


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Post-marketing surveillance

Carried out by the pharmaceutical industry

A single cohort of 5000-10,000 patients studied

Follow up- months/years

Data submitted to regulatory authorities

d li k


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Record linkage Monitoring drug use and effect via database research

Databases provide accessible information on thousands of patients

Each patient in the database has a unique identifier

Examples of information- hospitalization, infections developed, death,birth defects, lab investigations, physician services

Databases can also be linked

Disadvantages: Accuracy of data, missing data, lack of data

Advantages: Speed


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Methods of

Risk Quantification

&

Hypothesis testing


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What is risk?

The probability of developing an outcome,regardless of severity.

Wh i h h i ?


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What is a hypothesis ?

A hypothesis is a supposition based on observation or reflection.

Cigarette smoking causes lung cancer.

Use of O.C pills causes hypertension and thromboembolic

phenomenon.

Epidemiological studies allow you to accept or reject a hypothesis.

Wh i k t k ti ?


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Why measure risk postmarketing?

Risk quantification often requires large sample sizes

Rule of 3

An AE of 1/3000 will require 9000 subjects to be

studied

Pre marketing studies usually pick up Type A adverse

events (dose dependent)

i k


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Risk versus exposure

Single group risk [ cases/ total exposure],

does not account for baseline risk.

Risk is always calculated against an another

group- unexposed or an experimental

exposure


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Classification of risk - CIOMS

Very common 1 in 10 exposures Common < 1 in 10 1 in 100 exposures Uncommon < 1 in 100 1 in 1000 exposures Rare < 1: 1000 1:10,000 exposures Very rare > 1 in 10,000 exposures


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Measurement of risk

Absolute risk (AR)

Absolute risk reduction (ARR)

Relative risk (RR)

Relative risk reduction (RRR)

Odds ratio (OR)

Number needed to treat (NNT)


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Problem - 1

In a randomized trial, investigators

compared mortality rates in patients with

bleeding oesophageal varices treated eitherby endoscopic ligation or endoscopic

sclerotherapy. After a mean follow up of 10

months, 18/64 pts treated with ligation died,29/65 pts treated with sclerotherapy died.


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(1) Absolute risk (AR)

Simplest measure of association

Absolute risk of dying in the ligation group is18/64 or 28%

Absolute risk of dying in the sclerotherapy groupis 29/65 or 45%

f i k


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Measurement of risk

Absolute risk (AR)


Relative risk (RR)


Odds ratio (OR)


(2) Ab l t i k d ti (ARR)


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(2) Absolute risk reduction (ARR)

Establishes a relation between the two absolute risks

Also called as Risk difference (RD)

Tells us what proportion of pts are spared the outcome if

they receive the experimental therapy (rather than

conventional therapy)

ARR = 0.445-0.281 = 0.165 = 16.5%

M f i k


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Measurement of risk

Absolute risk (AR)


Relative risk (RR) Relative risk reduction (RRR)

Odds ratio (OR)


(3) Th t f l ti i k


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(3) The concept of relative risk

RR or risk ratio

Defined as the ratio of the risk rate in the

exposed population versus unexposed orcontrol versus experimental population


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Contingency table/ 2x2 table

Anoutcome

Did not developan outcome

Total

Exposed to

drug/test

a b a + b

Not exposed to

drug/control

c d c + d

RR = a = P1a+b

c = P2

c+d

P1P2


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P1= 0.446

P2= 0.281

P1/P2 = 0. 63

Thus the risk of death in subjects is 2/3rds that

with ligation

Or

Subjects receiving sclerotherapy were 1.58 times

or one and a half times as likely to die as

compared to ligation treated subjects


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Measurement of risk

Absolute risk (AR)


Relative risk (RR)


Odds ratio (OR)


(4) Relative Risk Reduction RRR


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(4) Relative Risk Reduction- RRR

Another measure of assessing effectiveness of

treatment

What is the proportion of baseline risk that isremoved by the experimental therapy

ARR / Baseline risk



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ARR = 0.446 - 0.281

Baseline risk = 0.446 (sclerotherapy group)

RRR = 0.165/0.446 = 0.369

Or ligation decreases the risk of death by 37%


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Measurement of risk

Absolute risk (AR)


Relative risk (RR)


Odds ratio (OR)



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(5 ) Odds Ratio

Measures the strength of association

between an exposure and outcome

C l l i f dd i


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Calculation of odds ratio

Odds in the exposed/odds in the unexposed

Odds in the exposed: a/a+b = ab/a+b b

Odds in the unexposed:c/c+d = cd/c+d d

C ti t bl / 2 2 t bl


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Contingency table/ 2x2 table

An

outcome

Did not develop

an outcome

Total

Exposed todrug/test a b a + b

Not exposed to

drug/control

c d c + d

OR = ad/bc


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Calculation of odds ratioDeath No Death Total

Exposed to ligation 18

a

46

b

64

a+b

Exposed to

sclerotherapy

29

c

36

d

65

c+d

OR

ad/bc

Odds Ratio


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Odds Ratio

Odds of dying in the ligation group is 0.39

Odds of dying in the sclerotherapy group is 0.80

Odds ratio = 0.39/0.80 = 0.48

Inference: Pts treated with ligation have half as likely to die as

compared to sclerotherapy

Or, 0.8/0.39, pts treated with sclerotherapy as twice as likely to die as

compared to ligation treated subjects


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Measurement of risk

Absolute risk (AR)


Relative risk (RR)


Odds ratio (OR)


(6) Number needed to treat


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(6) Number needed to treat

Another way to express the impact of the new treatment

Allows comparison between treatments

NNT = 1/ARR

For every 17 pts treated with ligation, 1 pt will be saved

For 100 pts, 28 pts will die with ligation

For 100 pts, 44.6 pts will die with sclerotherapy

Case control and cohort studies


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Case control and cohort studies

Case control

Proceeds from effect to cause.

Starts with the disease.

Fewer subjects.

Quicker results.

Relative inexpensive.

Cohort

Proceeds from cause toeffect.

Starts with the risk factor.

Larger number of subjects.

Longer follow up.

Expensive.

Levels of Evidence - 1


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Levels of Evidence - 1

Level 1- RCTs, direct comparisons of drugs within

the same class, rather than with placebos, for effect

on important treatment outcomes

Level 2: 1) RCTs, direct comparisons of drugs

within the same class, but on validated surrogate

outcomes or 2) Comparisons of active agents with

placebos on clinically important outcomes or

validated surrogate outcomes

Levels of evidence 2


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Levels of evidence- 2

Level 3: Placebo controlled trials where outcomesare restricted to unvalidated surrogate markers

Level 4: Non randomized studies (case control,

cohort studies)

Applications of Pharmacoepidemiology


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Applications of Pharmacoepidemiology

Estimation/quantitation of risk

Patient counseling

Formulation of public health/policy decisions

Formulation of therapeutic guidelines and discovery of

new indications

Pharmacoeconomic decision making

E ti ti f i k f d


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Estimation of risks of drug use

The most common application

Use of case-control and cohort studies

E.g., Clozapine and agranulocytosis and

neutropenia (1:5000 versus 1:200)

F l ti f bli h lth li d i i


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Formulation of public-health policy decisions

Is the risk associated with the drugs too

high?

Does the labeling need to be changed?

Is there too much of inappropriate

prescribing?

P ti t li


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Patient counseling

Termination of pregnancy versus

continuation of pregnancy when the risk of

malformation is low/high


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Formulation of therapeutic decision making

Effectiveness and safety of drugs used in

groups of people not included in Phase III

trials (elderly, pediatrics)

E.g, Use of ciprofloxacin for typhoid fever

in children

Summary


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Summary

Application of principles of epidemiology to the study of the use andeffects of drugs in large numbers of patients

Deals with signal generation, risk quantification and hypothesis

generation

Applications in risk quantification, patient counseling, therapeutic,

regulatory and economic decision making

08 pharmacoepidemiology

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