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Exploratory analyses of clinical trial data used for health technology assessments: a retrospective evaluation. | LitMetric

AI Article Synopsis

  • The study investigates the validity and limitations of exploratory analyses in clinical trial data used by agencies assessing medical product reimbursements in Germany from 2015 to 2020.
  • The analysis reviewed 422 Health Technology Assessment evaluations, revealing that a significant number (34.7%) were based on small subpopulations, which may distort results due to reduced sample size and random biases.
  • The authors conclude that reliance on these exploratory analyses, especially with multiple tests, can lead to misleading conclusions about the efficacy and safety of medical products, urging caution in decision-making.

Article Abstract

Objectives: To examine the validity and statistical limitations of exploratory analyses of clinical trial data commonly requested by agencies responsible for determining which medical products may be financed or reimbursed by a healthcare system.

Design: This was a retrospective review of efficacy and safety analyses conducted for German Health Technology Assessment (HTA) evaluations with a decision date between 2015 and 2020, and an illustrative safety-related exploratory analysis of data from two phase III clinical trials of verubecestat (an anti-amyloid drug whose development was stopped for lack of efficacy) as would be mandated by the German HTA agency.

Results: We identified 422 HTA evaluations of 404 randomised controlled clinical trials. For 140 trials (34.7%), the evaluation was based on subpopulations of participants in the originating confirmatory trial (175 subpopulations were assessed). In 57% (100 of 175), the subpopulation sample size was 50% or less of the original study population. Detailed analysis of five evaluations based on subpopulations of the original trial is presented. The safety-related exploratory analysis of verubecestat led to 206 statistical analyses for treatments and 812 treatment-by-subgroup interaction tests. Of 31 safety endpoints with an elevated HR (suggesting association with drug treatment), the HR for 81% of these (25 of 31) was not elevated in both trials. Of the 812 treatment-by-subgroup interactions evaluated, 26 had an elevated HR for a subgroup in one trial, but only 1 was elevated in both trials.

Conclusions: Many HTA evaluations rely on subpopulation analyses and numerous post hoc statistical hypothesis tests. Subpopulation analysis may lead to loss of statistical power and uncontrolled influences of random imbalances. Multiple testing may introduce spurious findings. Decisions about benefits of medical products should therefore not rely on exploratory analyses of clinical trial data but rather on prospective clinical studies and careful synthesis of all available evidence based on prespecified criteria.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345082PMC
http://dx.doi.org/10.1136/bmjopen-2021-058146DOI Listing

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