Updated efficacy results from the JAVELIN Renal 101 trial: first-line avelumab plus axitinib versus sunitinib in patients with advanced renal cell carcinoma
Bibliographic record
Abstract
BACKGROUND: The phase 3 JAVELIN Renal 101 trial (NCT02684006) demonstrated significantly improved progression-free survival (PFS) with first-line avelumab plus axitinib versus sunitinib in advanced renal cell carcinoma (aRCC). We report updated efficacy data from the second interim analysis. PATIENTS AND METHODS: Treatment-naive patients with aRCC were randomized (1 : 1) to receive avelumab (10 mg/kg) intravenously every 2 weeks plus axitinib (5 mg) orally twice daily or sunitinib (50 mg) orally once daily for 4 weeks (6-week cycle). The two independent primary end points were PFS and overall survival (OS) among patients with programmed death ligand 1-positive (PD-L1+) tumors. Key secondary end points were OS and PFS in the overall population. RESULTS: Of 886 patients, 442 were randomized to the avelumab plus axitinib arm and 444 to the sunitinib arm; 270 and 290 had PD-L1+ tumors, respectively. After a minimum follow-up of 13 months (data cut-off 28 January 2019), PFS was significantly longer in the avelumab plus axitinib arm than in the sunitinib arm {PD-L1+ population: hazard ratio (HR) 0.62 [95% confidence interval (CI) 0.490-0.777]}; one-sided P < 0.0001; median 13.8 (95% CI 10.1-20.7) versus 7.0 months (95% CI 5.7-9.6); overall population: HR 0.69 (95% CI 0.574-0.825); one-sided P < 0.0001; median 13.3 (95% CI 11.1-15.3) versus 8.0 months (95% CI 6.7-9.8)]. OS data were immature [PD-L1+ population: HR 0.828 (95% CI 0.596-1.151); one-sided P = 0.1301; overall population: HR 0.796 (95% CI 0.616-1.027); one-sided P = 0.0392]. CONCLUSION: Among patients with previously untreated aRCC, treatment with avelumab plus axitinib continued to result in a statistically significant improvement in PFS versus sunitinib; OS data were still immature. CLINICAL TRIAL NUMBER: NCT02684006.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".