Evidence map›Paper›PMID 35906049›Full record

ArticleBMJ open2022

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

Björn J Oddens, Israel T Agaku, Ellen S Snyder, William Malbecq, William Wb Wang, Karen M Kaplan, Gary G Koch, Frank W Rockhold

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 2 countries.

Björn J OddensMRL, Merck & Co, Rahway, New Jersey, USA bjorn.oddens@merck.com.ORCID 0000-0001-5393-2555
Israel T AgakuDepartment of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, Boston, Massachusetts, USA.ORCID 0000-0002-5116-2961
Ellen S SnyderMRL, Merck & Co, Rahway, New Jersey, USA.ORCID 0000-0002-8097-2621
William MalbecqMRL, MSD Europe, Brussels, Belgium.
William Wb WangMRL, Merck & Co, Rahway, New Jersey, USA.
Karen M KaplanMRL, Merck & Co, Rahway, New Jersey, USA.
Gary G KochDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Frank W RockholdDuke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.ORCID 0000-0003-3732-4765
Merck & Co., Inc., Rahway, NJ, USA (United States) · USClinical Research Institute · USHarvard University · USMSD (Belgium) · BEUniversity of North Carolina at Chapel Hill · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo 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.

designThis 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.

resultsWe 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.

conclusionsMany 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.

Indexed as

Biomedical TechnologyTechnology Assessment, BiomedicalHumansProspective StudiesRetrospective StudiesSample SizeHealth policyRisk managementSTATISTICS & RESEARCH METHODS

Identifiers

PMID35906049
PMCPMC9345082
OpenAlexW4288740114

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.