Avelumab First-line Maintenance Therapy for Advanced Urothelial Carcinoma: Comprehensive Clinical Subgroup Analyses from the JAVELIN Bladder 100 Phase 3 Trial
Bibliographic record
Abstract
BACKGROUND: In the phase 3 JAVELIN Bladder 100 trial, avelumab first-line (1L) maintenance + best supportive care (BSC) significantly prolonged overall survival (OS) and progression-free survival (PFS) versus BSC alone in patients with advanced urothelial carcinoma (aUC) who were progression-free following 1L platinum-based chemotherapy, leading to regulatory approval in various countries. OBJECTIVE: To analyze clinically relevant subgroups from JAVELIN Bladder 100. DESIGN, SETTING, AND PARTICIPANTS: Patients with unresectable locally advanced or metastatic UC without progression on 1L gemcitabine + cisplatin or carboplatin were randomized to receive avelumab + BSC (n = 350) or BSC alone (n = 350). Median follow-up was >19 mo in both arms (data cutoff October 21, 2019). This trial is registered on ClinicalTrials.gov as NCT02603432. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: OS (primary endpoint) and PFS were analyzed in protocol-specified and post hoc subgroups using the Kaplan-Meier method and Cox proportional hazards models. RESULTS AND LIMITATIONS: tumors treated with carboplatin + gemcitabine (HR 0.67, 95% CI 0.39-1.14), and patients whose best response to chemotherapy was a complete response (HR 0.80, 95% CI 0.46-1.37), partial response (HR 0.62, 95% CI 0.46-0.84), or stable disease (HR 0.70, 95% CI 0.46-1.06). Observations were similar for PFS. Limitations include the smaller size and post hoc evaluation without multiplicity adjustment for some subgroups. CONCLUSIONS: Analyses of OS and PFS in clinically relevant subgroups were consistent with results for the overall population, further supporting avelumab 1L maintenance as standard-of-care treatment for patients with aUC who are progression-free following 1L platinum-based chemotherapy. PATIENT SUMMARY: In the JAVELIN Bladder 100 study, maintenance treatment with avelumab helped many different groups of people with advanced cancer of the urinary tract to live longer.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".