Overall Survival and Quality-of-Life Superiority in Modern Phase 3 Oncology Trials
Bibliographic record
Abstract
Importance: Alternative end points, such as progression-free survival, are increasingly used in phase 3 randomized clinical trials (RCTs). However, alternative end points are often not valid surrogates for overall survival and quality of life (QOL) and may be less relevant to patients. Objective: To determine the proportion of phase 3 RCTs with overall survival or QOL superiority. Design and Setting: Meta-epidemiological study of 2-group, superiority-design, interventional phase 3 oncology RCTs screened from ClinicalTrials.gov and published between 2002 and 2024. Main Outcomes and Measures: Alternative end-point, overall survival, and QOL superiority in the experimental group vs the reference/control group according to prespecified statistical criteria for each RCT. A secondary goal was to evaluate the quality of QOL analyses, since approaches unadjusted for baseline scores may bias results. Results: A total of 791 RCTs representing 555 580 enrolled patients were included. Alternative primary end points were most common (n = 495 [63%]). The primary end point was met in 53% of the RCTs (n = 420); alternative end-point superiority was shown in 55% (n = 434). Overall survival superiority was shown in 28% (n = 221). Patient-reported outcomes were collected in 61% of the RCTs (n = 482), but global QOL results were published in only 34% (n = 271). Most between-group global QOL analyses did not adjust for baseline scores (223 [82%]). Global QOL superiority was shown in 11% (n = 84). Among all RCTs, 32% (n = 257) demonstrated either overall survival or global QOL superiority. Superiority of both overall survival and global QOL was shown in 6% (n = 48). Among 434 RCTs with a positive alternative end point, only a minority showed superiority of either overall survival (185 [43%]) or global QOL (67 [15%]). Conclusions and Relevance: Findings of superiority-design phase 3 oncology RCTs are commonly interpreted as positive. However, this is mostly based on improvements in alternative end points. Gains in either overall survival or QOL are uncommon, even when alternative end-point findings are positive. QOL appears both underevaluated and underreported; furthermore, the majority of phase 3 QOL analyses are unadjusted for baseline scores, which lose efficiency and add bias compared with adjusted analyses. To increase the meaningfulness of late-phase research, future trial designs and regulatory processes should be refocused toward overall survival and QOL improvements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.314 | 0.542 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.015 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".