svmpharma real world evidence - randomised controlled trials were never designed to tell us what...
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Randomised controlled trials were never designed to tell us what happens in a real-life setting
SVMPharma Ltd
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2 © 2015 SVMPharma Ltd. All rights reserved.
Introduction
Despite the time, care, and investment you
have put into your randomised controlled trial
(RCT), there will be gaps in your dataset. The
strengths of RCT study design, which allow
them to overcome biases, minimise errors and
provide robust results are also the source of
their shortcomings.
Real World Evidence (RWE) is clinical data
collected outside of conventional randomised
controlled trials (RCTs). The role of RWE in the
pharmaceutical industry has seen a
transformation within just a few years,
catching the attention of pharmaceutical
companies, advisory bodies, regulators and
more. RWE is increasingly recognised and
accepted as an effective way of
supplementing your RCT data and bridging
these data gaps.
To understand what RWE can deliver, let us
first consider what is causing these data gaps
within the RCT dataset:
Only a small minority of patients meet the
enrolment criteria for RCTs
Participants are selected for RCTs based on
rigorous inclusion and exclusion criteria, which
means the trial population can differ greatly from
the general population. A study of 870 asthma
patients 1 found that
using the criteria
commonly found in
asthma RCTs (i.e.
defined range of
airflow obstruction/ no
co-morbidities/ 1 to 2
exacerbations in
previous 12 months
but 0 in the last
month/ non-smoker/
no regular inhaled
corticosteroid use) only 3.3% would be eligible for
randomisation. This figure is higher in other
disease areas but generally remains at
approximately 20%. RCT study designs, by
targeting internal validity, often sacrifice their
applicability to patients in a real-life setting. How
can we determine how the remaining 80%+ of
patients will respond if they are left out from
RCTs?
Key patient populations are not
adequately accounted for by RCTs
Particular patient populations and patient types
are underrepresented in RCTs. For example, heart
failure is a condition associated with the elderly.
However, an analysis of 251 heart failure trials 2
has shown that 25% of
trials excluded patients
due to an arbitrary
upper age limit, 75%
excluded patients with
renal or kidney disease,
36% excluded patients
who had a reduced life
expectancy and 18%
excluded patients
based on co-concomitant drug usage. A
combination of these exclusions means that there
is limited information regarding the efficacy and
safety of drugs in older patients and the patients
enrolled are not representative of those seen in
clinical practice.
RCTs face recruitment challenges which
limits what they can investigate
Within certain areas of treatment, the design and
conduct of RCTs brings additional challenges and
pressures which can bring the trial to a premature
halt at the recruitment stage. A retrospective of
such a scenario has been published for the SPARE
trial 3 which set out to compare radiotherapy and
surgical treatments in bladder cancer. One of the
key reasons for failure was due the difficulties in
finding patients to be randomised between the
two arms, due to the large difference in the two
treatment options, the impact of strong patient
preferences, as well as complexities regarding
patient eligibility. Despite concerted efforts to
improve recruitment, the RCT were closed in
2010. Although physicians and patients often have
An analysis of 251
heart failure trials
has shown that
36% excluded
patients who had
a reduced life
expectancy
A study of 870
asthma patients
found that using
the criteria
commonly found
in asthma RCTs
only 3.3% would
be eligible for
randomisation
3 © 2015 SVMPharma Ltd. All rights reserved.
to make choices between two very different
treatment pathways, conducting a RCT to
investigate this is challenging.
Adherence to treatment in RCTs differs
greatly to real-world adherence
Patient adherence to medication is a problem that has a direct impact on treatment effectiveness. Bisphosphonate therapy for osteoporosis is a prime example of an area where adherence has been of concern. Adherence to treatment is consistently high within RCTs, often reaching 80-95%, and is one of the prerequisites for enrolment. However a retrospective database analysis of 29,157 post-menopausal women taking alendronate 4, 5 showed that 42.5% of women discontinued therapy within 6 months and another 18.1% and 13.9% of women discontinued therapy at 1-year and 2-year, respectively. Therefore, only 25.5% of women received 3-years of treatment. These large differences in adherence rates between RCTs and real-life clinical practice lead to significant uncertainties in treatment effectiveness and is a problem inherently difficult to address with RCTs.
RCTs struggle to handle complex
situations and overlapping interventions
RCTs are restricted to evaluating specific discrete
interventions one at a time, whilst patients often
have co-morbidities that can lead to complex
interactions. A database of 980 patients
representative of a
typical population
visiting primary care
services had the
inclusion and
exclusion criteria of 5
hypertension RCTs
applied to them. 6 Of
the patients who
were eligible for entry
in the RCTs, 89%-
100% had multiple chronic conditions and the
mean number of chronic conditions per patient
ranged from 5.5 to 11.7. None of the RCTs
addressed the competing demands raised by
treatment of co-morbidities and the complex
realities of the situation. In RCT study design, such
issues could only be assessed in a framework
where each factor is isolated from the others
which would make the costs of the multiple
treatment arms prohibitive. RCTs, especially when
driven by the desire to secure a label or prove
safety, opt towards a highly-selected
homogeneous study population instead of a
diverse population reflective of real-life clinical
practice.
What are the consequences of having
gaps in your data?
Relying exclusively on RCTs can lead to significant
issues. The data from RCTs may not be applicable
to certain population segments, leading to
treatment ineffectiveness and patient and HCP
disappointment. The effects of variable adherence
on patient health could be missed. The actual
costs to payors and reimbursement strategies
may not be accurate, whilst promotional and
marketing campaigns may be misdirected and
inefficient.
Additionally, not having any RWE for your product
may itself be problematic. For example, there is
now the possibility that you will be directly asked
for RWE from HTA bodies (i.e. within the new
Cancer Drug Fund proposals) 7, or you may need
5 key reasons behind data gaps in RCTs
Only a small minority of patients meet the enrolment criteria for RCTs
Key patient populations are not adequately accounted for by RCTs
RCTs face recruitment challenges which limits what they can investigate
Adherence to treatment in RCTs differs greatly to real-world adherence
RCTs struggle to handle complex situations and overlapping interventions
In RCT study
designs, such issues
could only be
assessed in a
framework where
each factor is
isolated from the
others
4 © 2015 SVMPharma Ltd. All rights reserved.
to counter your competitor’s RWE generation to
protect your market share.
How can data gaps be addressed?
By first identifying and understanding the gaps,
RWE programmes can be tailored to address the
pertinent issues and provide a richer and more
well-rounded data set. RWE covers observational
studies, patient registries, large datasets e.g.
Clinical Practice Research Datalink (CPRD) and
more, but the most expedient option is via a
custom RWE data collection programme to collect
individual patient data. This has been consistently
proven to generate and enhance positive
outcomes.
These successes have been assisted by an
increasing awareness of the advantages that RWE
provides over traditional RCTs, being more
representative of a real-life population, better
demonstrative of the benefits of a drug in
everyday clinical practice and more valuable in
covering real-world patient behaviour and
adherence.
Conclusion
Conventional RCTs are necessary for
determining efficacy and safety, but real-
world clinical practice can be very different.
RWE complements RCT data and offers the
opportunity to bridge the data gaps.
Have you identified your data gaps?
References and Further Reading
1. Herland et al. How representative are clinical study patients with
asthma or COPD for a larger ‘‘real life’’ population of patients with
obstructive lung disease? Respiratory Medicine. 2004. Available at:
http://www.sciencedirect.com/science/article/pii/S09546111040020
69 Accessed Dec 2015.
2. Cherubini et al. The Persistent Exclusion of Older Patients From
Ongoing Clinical Trials Regarding Heart Failure. Arch Intern Med.
2011. Available at:
http://archinte.jamanetwork.com/article.aspx?articleid=226912
Accessed Dec 2015.
3. Paramasivan et al. Key issues in recruitment to randomised
controlled trials with very different interventions: a qualitative
investigation of recruitment to the SPARE trial (CRUK/07/011). Trials.
2011. Available at:
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3068963/ Accessed
Dec 2015.
4. Hiligsmann et al. The clinical and economic burden of non-
adherence with oral bisphosphonates in osteoporotic patients.
Health Policy. 2010. Available at:
http://www.esceo.org/sites/esceo/files/publications/economics/Hea
lthPolicy_Hiligsmann.pdf Accessed Dec 2015.
5. Rabenda et al. Adherence to bisphosphonates therapy and hip
fracture risk in osteoporotic women. Osteoporos Int. 2008. Available
at: http://www.ncbi.nlm.nih.gov/pubmed/17999022 Accessed Dec
2015.
6. Fortin et al. Randomized controlled trials: do they have external
validity for patients with multiple comorbidities? Ann Fam
Med. 2006. Available at
http://www.annfammed.org/content/4/2/104.long Accessed Dec
2015
7. NICE. Consultation now open on plans to reform Cancer Drugs
Fund. NICE. 2015, Available at:
https://www.nice.org.uk/news/article/consultation-open-on-plans-
to-reform-cancer-drugs-fund Accessed Dec 2015.
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