Avelumab First-line Maintenance for Advanced Urothelial Carcinoma: Long-term Analyses of Patient-reported Outcomes and Quality-adjusted Time Without Symptoms or Toxicity from the JAVELIN Bladder 100 Trial
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: In JAVELIN Bladder 100, avelumab first-line maintenance plus best supportive care (BSC) significantly prolonged overall survival versus BSC alone, with no detrimental impact on quality of life (QOL), in patients with advanced urothelial carcinoma without progression following first-line platinum-based chemotherapy. We report long-term analyses of patient-reported outcomes (PROs) in patients treated with avelumab (any duration or ≥12 mo) and a post hoc analysis comparing quality-adjusted time without symptoms or toxicity (Q-TWiST) between arms. METHODS: PROs were assessed using National Comprehensive Cancer Network/Functional Assessment of Cancer Therapy Bladder Symptom Index-18 (FBlSI-18) and EuroQol 5-level EQ-5D (EQ-5D-5L). Q-TWiST was calculated as the utility-weighted sum of mean time in three health states: time with all-cause grade 3/4 toxicity prior to progression, time without grade 3/4 toxicity or symptoms of progression, and time after progression. KEY FINDINGS AND LIMITATIONS: In the overall avelumab plus BSC arm (n = 350) and the subgroup treated for ≥12 mo (n = 118), completion rates for PRO assessments during treatment were >80%. FBlSI-18 total and EQ-5D-5L index scores remained stable throughout 24 mo of treatment, with no clinically important changes from baseline. The mean Q-TWiST was 18.46 mo with avelumab plus BSC versus 15.13 mo with BSC alone (22% relative improvement). Limitations include open-label trial design and small patient numbers at later cycles. CONCLUSIONS AND CLINICAL IMPLICATIONS: Patients receiving avelumab had preserved health-related QOL and control of cancer-related symptoms with manageable toxicity, further supporting avelumab first-line maintenance as the recommended treatment for advanced urothelial carcinoma not progressed after platinum-based chemotherapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".