Avelumab first-line maintenance in locally advanced or metastatic urothelial carcinoma: Applying clinical trial findings to clinical practice
Bibliographic record
Abstract
Although urothelial carcinoma (UC) is considered a chemotherapy-sensitive tumor, progression-free survival and overall survival (OS) are typically short following standard first-line (1L) platinum-containing chemotherapy in patients with locally advanced or metastatic disease. Immune checkpoint inhibitors (ICIs) have antitumor activity in UC and favorable safety profiles compared with chemotherapy; however, trials of 1L ICI monotherapy or chemotherapy + ICI combinations have not yet shown improved OS vs chemotherapy alone. In addition to direct cytotoxicity, chemotherapy has potential immunogenic effects, providing a rationale for assessing ICIs as switch-maintenance therapy. In the JAVELIN Bladder 100 phase 3 trial, avelumab administered as 1L maintenance with best supportive care (BSC) significantly prolonged OS vs BSC alone in patients with locally advanced or metastatic UC that had not progressed with 1L platinum-containing chemotherapy (median OS, 21.4 vs 14.3 months; hazard ratio, 0.69 [95% CI, 0.56-0.86]; P = 0.001). Efficacy benefits were seen across various subgroups, including recipients of 1L cisplatin- or carboplatin-based chemotherapy, patients with PD-L1+ or PD-L1- tumors, and patients with diverse characteristics. Results from JAVELIN Bladder 100 led to the approval of avelumab as 1L maintenance therapy for patients with locally advanced or metastatic UC that has not progressed with platinum-containing chemotherapy. Avelumab 1L maintenance is also included as a standard of care in treatment guidelines for advanced UC with level 1 evidence. This review summarizes the data that supported these developments and discusses practical considerations for administering avelumab maintenance in clinical practice, including patient selection and treatment management.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".