Eligibility criteria and endpoints in metastatic renal cell carcinoma trials.
Bibliographic record
Abstract
465 Background: Treatments for metastatic renal cell carcinoma (mRCC) are often compared across trials, but trial eligibility criteria and endpoints differ. In Sept 2015, DATECAN published recommendations for time-to-event endpoints in mRCC trials. The success of their efforts to harmonize endpoints has not yet been assessed. Methods: We assessed eligibility criteria and endpoints from 18 Phase III mRCC trials starting from 2003 onwards. We also assessed 4 Phase III trials submitted after Sept. 2015 for compliance with DATECAN recommendations. Results: Among the 18 trials, consistent criteria were: absolute neutrophil count ≥1,500/µL, platelet count ≥100,000/µL, and bilirubin ≤1.5xULN. However, the following differed in requirements and measures used: see table.The 4 newer trials did not entirely follow DATECAN’s recommendations. Although their primary endpoint is progression free survival (PFS) as recommended, 3/4 trials do not define PFS, and the one that does includes death from any cause instead of DATECAN’s “death from kidney cancer.” Conclusions: Key eligibility criteria were somewhat inconsistent across phase III mRCC trials, and newer trials’ endpoints did not align with DATECAN’s recommendations. Not only is greater standardization needed to facilitate meta-analyses and cross-trial comparisons, but as evident from lack of adherence to DATECAN’s recommendations, greater promotion and enforcement of recommendations is needed to harmonize trial design and improve comparability.[Table: see text]
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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 | 0.235 | 0.400 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".