We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Differential Treatment Effects of Subgroup Analyses in Phase 3 Oncology Trials From 2004 to 2020.
- Authors
Sherry, Alexander D.; Hahn, Andrew W.; McCaw, Zachary R.; Abi Jaoude, Joseph; Kouzy, Ramez; Lin, Timothy A.; Minsky, Bruce; Fuller, C. David; Meirson, Tomer; Msaouel, Pavlos; Ludmir, Ethan B.
- Abstract
Key Points: Question: Among phase 3 oncology trials, how often do subgroup analyses support claims of differential treatment effects? Findings: In this cross-sectional study of 379 published phase 3 randomized clinical trials with subgroup analyses, which enrolled 331 653 participants, most claims for differential treatment effects were rated as low or very low credibility according to the Instrument for Assessing the Credibility of Effect Modification Analyses. Meaning: In this study, the differential treatment effect claims of most phase 3 randomized clinical trials in oncology were not well-supported. This cross-sectional study evaluates the credibility of differential treatment effect claims in published phase 3 randomized clinical oncology trials published prior to 2021 according to the Instrument for Assessing the Credibility of Effect Modification Analyses. Importance: Subgroup analyses are often performed in oncology to investigate differential treatment effects and may even constitute the basis for regulatory approvals. Current understanding of the features, results, and quality of subgroup analyses is limited. Objective: To evaluate forest plot interpretability and credibility of differential treatment effect claims among oncology trials. Design, Setting, and Participants: This cross-sectional study included randomized phase 3 clinical oncology trials published prior to 2021. Trials were screened from ClinicalTrials.gov. Main Outcomes and Measures: Missing visual elements in forest plots were defined as a missing point estimate or use of a linear x-axis scale for hazard and odds ratios. Multiplicity of testing control was recorded. Differential treatment effect claims were rated using the Instrument for Assessing the Credibility of Effect Modification Analyses. Linear and logistic regressions evaluated associations with outcomes. Results: Among 785 trials, 379 studies (48%) enrolling 331 653 patients reported a subgroup analysis. The forest plots of 43% of trials (156 of 363) were missing visual elements impeding interpretability. While 4148 subgroup effects were evaluated, only 1 trial (0.3%) controlled for multiple testing. On average, trials that did not meet the primary end point conducted 2 more subgroup effect tests compared with trials meeting the primary end point (95% CI, 0.59-3.43 tests; P =.006). A total of 101 differential treatment effects were claimed across 15% of trials (55 of 379). Interaction testing was missing in 53% of trials (29 of 55) claiming differential treatment effects. Trials not meeting the primary end point were associated with greater odds of no interaction testing (odds ratio, 4.47; 95% CI, 1.42-15.55, P =.01). The credibility of differential treatment effect claims was rated as low or very low in 93% of cases (94 of 101). Conclusions and Relevance: In this cross-sectional study of phase 3 oncology trials, nearly half of trials presented a subgroup analysis in their primary publication. However, forest plots of these subgroup analyses largely lacked essential features for interpretation, and most differential treatment effect claims were not supported. Oncology subgroup analyses should be interpreted with caution, and improvements to the quality of subgroup analyses are needed.
- Subjects
TUMOR treatment; CROSS-sectional method; HEALTH insurance reimbursement; CLINICAL trials; ONCOLOGY; TREATMENT effectiveness; DESCRIPTIVE statistics; ODDS ratio; QUALITY of life; COMPARATIVE studies; CONFIDENCE intervals
- Publication
JAMA Network Open, 2024, Vol 7, Issue 3, pe243379
- ISSN
2574-3805
- Publication type
Article
- DOI
10.1001/jamanetworkopen.2024.3379