Alternate Endpoints for Screening Phase II Studies
Bibliographic record
Abstract
Phase II trials are screening trials that seek to identify agents with sufficient activity to continue development and those for which further evaluation should be halted. Although definitive phase III trials use progression-free or overall survival to confirm clinical benefit, earlier endpoints are preferable for phase II trials. Traditionally, tumor shrinkage of a predetermined degree (response) has been used as a surrogate of eventual survival benefit based on the observation that high response rates (RR), and particularly complete responses, in the phase II setting resulted in survival benefit in subsequent phase III trials. Recently, some molecularly targeted agents have shown survival and clinical benefit despite very modest RRs in early clinical trials. These observations provide a major conundrum, with concerns of inappropriate termination of development for active agents with low RRs being balanced by concerns of inactive agents being taken to late-phase development with resultant increases in the failure rate of phase III trials. Numerous alternate or complementary endpoints have been explored, incorporating multinomial endpoints (including progression and response), progression-free survival, biomarkers, and, more recently, evaluation of tumor size as a continuous variable. In this review, we discuss the current status of phase II endpoints and present retrospective analyses of two international gastrointestinal cancer studies showing the potential utility of one novel approach. Alternate endpoints, although promising, require additional evaluation and prospective validation before their use as a primary endpoint for phase II trials.
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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 | 0.064 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".