Overall survival and quality of life superiority in modern phase III oncology trials.
Bibliographic record
Abstract
11015 Background: The use of alternative endpoints, such as progression-free survival, has increased over time in phase III randomized clinical trials (RCTs). However, PFS and other alternative endpoints are often not valid surrogates for overall survival (OS) and quality of life (QOL), and may be less relevant to patients. We sought to determine the proportion of phase III oncology RCTs with OS or QOL superiority. A secondary goal was to evaluate the approach of QOL analyses, since “change-from-baseline” approaches may bias results (Bland and Altman. Trials. 2011;12:264). Methods: We performed a meta-epidemiological study of two-arm, superiority-design, interventional phase III oncology RCTs screened from ClinicalTrials.gov. RCT publications were reviewed for alternative endpoint, OS, and QOL results by at least two investigators. Alternative endpoint and OS superiority were defined for the experimental arm vs control arm according to the pre-specified statistical criteria for each RCT. QOL superiority was defined by either statistically significant or minimal clinically important differences (MCID). QOL was sub-classified as global QOL, defined by the composite summary measure obtained using the patient-reported outcome instrument, or domain QOL, referring to measures obtained from instrument subscales. Results: We included 791 RCTs published between 2002 and 2024, representing 555,580 enrolled patients. Primary RCT results were published between 2002 and 2024. Alternative primary endpoints were most common (n = 495, 63%). The primary endpoint was met in 53% of the RCTs (n = 420). Alternative endpoint superiority was shown in 55% of the RCTs (n = 434). OS was reported by 705 RCTs (89%), and OS superiority was shown in 28% of the RCTs (n = 221). Patient-reported outcomes were collected in 61% of the RCTs (n = 482), and 34% of the RCTs published global QOL results (n = 271). Most global QOL analyses were change-from-baseline (55%, n = 148). Global QOL superiority was shown in 11% of the RCTs (n = 84). In a sensitivity analysis of QOL subscale outcomes, 80 trials (10%) showed superiority in at least one QOL domain. Collectively, in 32% of the RCTs (n = 257), superiority of either OS or global QOL was demonstrated. In 6% of all RCTs (n = 48), both OS and global QOL superiority was shown. Conclusions: Phase III, superiority design oncology RCTs are commonly interpreted as “positive.” However, this is usually based on improvements in unvalidated alternative endpoints. Gains in either OS or QOL are uncommon, and exceedingly rare in combination. QOL appears both under-evaluated and under-reported. Furthermore, the majority of phase III QOL analyses, which are based on change-from-baseline comparisons, may be misleading. To increase the meaningfulness of late-phase research, future trial designs and regulatory processes should be re-focused towards OS and methodologically rigorous QOL improvements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.168 | 0.225 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.014 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".