Comparison of patients with high-risk nonmetastatic clear cell renal carcinoma in adjuvant therapy trials versus nonclinical trial patients.
Bibliographic record
Abstract
361 Background: Characteristics of patients with high risk for recurrence non-metastatic renal cell carcinoma (nmRCC) participating in adjuvant therapy clinical trials post-nephrectomy have not been well described. We evaluated high risk nmRCC patients in the CKCis database to explore differences between trial and non-trial patients. Methods: Adult patients undergoing partial or radical nephrectomy for clear cell nmRCC between January 1, 2011 and March 31, 2021 were included. CKCis is a prospective cohort of patients from 14 Canadian academic institutions. Patients with high risk nmRCC (using modified UCLA Integrated Staging System) were included. Demographic, clinical, and survival statistics were analyzed for all patients and comparatively for the trial and non-trial groups. Results: 1459 patients, including 63 in adjuvant trials, were evaluated. 71% were male, 91% had pT3N0M0 disease. Disease characteristics including tumor size, stage, grade, location, necrosis, and margin status were similar between groups. Trial patients were younger (mean age 58.1 vs. 63.6; p < 0.0001) and had lower Charlson Comorbidity Index scores (median 4 [3,6) vs. 5 [4,6] p < 0.001). Estimated overall survival (OS) at 5 years was 80.8% (95% CI, 65,90) for trial patients and 74.8% (95% CI, 71,78.2) for non-trial patients. Recurrence-free survival at 5 years for trial patients was 48.6% (95% CI, 34,61.7) and 39.2% (95% CI, 35.2,43.1) for non-trial patients. Conclusions: Patients in adjuvant trials were younger and healthier at baseline than the average high risk nmRCC CKCis patient. Trial patients appear to have had longer time to recurrence and longer survival compared to non-trial patients, although not reaching statistical significance. Selection bias is common in clinical trials and evaluation of real-world population-based evidence of patients receiving adjuvant therapy will be important to ensure phase 3 trial results have external validity.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".