Depth of response (DepOR) analysis and correlation with clinical outcomes from JAVELIN Renal 101.
Bibliographic record
Abstract
690 Background: In the phase 3 JAVELIN Renal 101 trial (NCT02684006), avelumab + axitinib (A+Ax) significantly improved progression-free survival (PFS) in patients (pts) with advanced renal cell carcinoma (aRCC) compared with sunitinib (S); median PFS (mPFS) in the A+Ax arm was 13.8 mo (95% CI, 11.1 mo, not estimable [NE]) vs 8.4 mo (95% CI, 6.9, 11.1) in the S arm (HR, 0.69; 95% CI, 0.56, 0.84; P < 0.001) (Motzer NEJM 2019). Here, we report on the correlation of PFS with DepOR at early imaging timepoints. Methods: Data from pts in both arms were analyzed based on blinded independent central review (BICR) per RECIST 1.1. Tumor shrinkage or growth was categorized by best percent change in target lesions on imaging obtained up to 13 wk: shrinkage ≥0% to < 30%, ≥30% to < 60%, and ≥60% and growth > 0% to < 20%. Pts without progressive disease and who had not died at or prior to 13 wk after randomization were included in the landmark analysis. PFS data were analyzed for each category. A Cox multivariate landmark analysis was conducted for PFS for pts in the A+Ax arm, with DepOR as a continuous variable. Results: Results are reported on the basis of the first interim analysis, with a minimum follow-up of 6.0 mo in all pts. The table shows the proportion of pts in each shrinkage category and PFS outcomes according to best percent change in target lesions at the 13-wk landmark. After adjusting for prognostic covariates, Cox multivariate analyses showed a meaningful association between DepOR and PFS for pts in the A+Ax arm, consistent with the results observed in each shrinkage category. Conclusions: Greater tumor shrinkage at early imaging timepoints was associated with longer PFS in JAVELIN Renal 101. Clinical trial information: NCT02684006 .[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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".