comparative effectiveness research : rethinking therapeutic evaluation in chronic diseases ph ravaud
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Comparative Effectiveness Research :Rethinking Therapeutic Evaluation in
Chronic Diseases
Ph Ravaud
Therapeutic Evaluation of Chronic diseases
• Today : mainly RCts and Meta-Analysis (one drug )
• Tomorrow
- RCTs
- Meta-analysis and Network Meta-analysis (all drugs for a specific disease)
- Observational Data
Too slow Too expensive Doesn’t answer many critical questions ( or
doesn’t answer questions relevant for physicians ( Short term , inadequate comparator, side effects)
Otherwise its great ( RCTs are the best way to obtain groups of patients comparable for known and unknown prognostic factors )
Applicability or generalizability of trials
• Patients included are not representative of the patients treated in usual care (trial patients are younger and with less co-morbidities)
• Setting is not representative (centers are highly selected)
• Treatments are evaluated mainly according to the principle “one size fits all”
Critical Knowledge Gaps
• The paradox
- 18,000 RCTs published each year
- more than 350,000 RCTs available
• Despite that available evidence remains limited or of poor quality
Much of Care Today is Not Based on Scientific Evidence
Robert Califf, IOM Meeting on Evidence-based Medicine, December 2007
Less than 20% of AHA/ACC heart disease management recommendations are based on a high level of evidence and over 40% are based on the lowest level of evidence AND proportionof recommendations with high evidence levels has not increased over time
From Meta-analysis to Network Meta-analysis
One treatment All treatments available for a disease
Thousands/yLess than 50/y
Network meta-analysis
Intervention C
Intervention A
Intervention E
Intervention F
Intervention B
Intervention D
Combining direct and indirect evidence
Biologic Treatment in Rheumatoid Arthritis: Ongoing Trials
-Only 5 head to Head trials - Ongoing Trials recruiting patients failing to respond to Methotrexate and with high disease activity
Cost of RCTs: an example
• 18,000 patients
• Total crf pages 1.8 millions
• Total crf variables 2.5 Billions
• Total number of queries 600,000
• Cost 700 millions Euros
• Treatment effects decrease over time , number of patients required mecanically increase
Unrealistic to expect head-to-head RCTs addressing all 2-by-2 comparisons
Number of competing interventions
Number of pair-wise comparisons
4 65 106 157 218 289 3610 4511 5512 66
• It is an unrealistic expectation that we will have randomized trials for every intervention and its combinations in every patient subgroup ( for example if for a disease we have 20 different treatment options and 3 different subgroups of patients, we need theoritically at least 470 head to head trials !)
•We need Effectiveness evidence in a timely manner. Randomized trials take time to conduct
•Therefore, 85% of the CER evidence is from non-experimental data!*
* Academy Health Report June 2009
Transparency of clinical trials
• Reporting guidelines
• Clinicaltrial.gov 2005
• FDA amendment act 2007
Consort Extensions
• Too many extensions
• Too many reporting guidelines
• Editors do not really implement the guidelines
• Quality of reporting remains poor
Trial registration mandatory since 2005( International Committee of Medical Journal Editors)
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Impact of dissemination bias
Separate meta-analyses of the FDA and journal data sets show that the increase in effect size ranged from 11 to 69% for individual drugs and was 32% overall
Turner et al. NEJM 200816
Selective Dissemination Bias
FDA Amendment Act
• US Federal law enacted in 2007 mandates registration and results reporting for clinical trials of drugs , biological products and devices at clinicaltrial.gov
• Study sponsors or PI are requires to report summary results information within 1 year of completing data collection for teh prespecified primary outcome
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Levels of “Transparency”
Zarin DA, Tse T.. Science. 2008 Mar 7;319(5868):1340-2.21
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