Systematic Literature Review (SLR) and Network Meta-Analysis (NMA) of First-Line Therapies (1L) for Locally Advanced/Metastatic Urothelial Carcinoma (la/mUC)
Bibliographic record
Abstract
To compare efficacy outcomes for all approved and investigational first-line (1L) treatment regimens for locally advanced or metastatic urothelial carcinoma (la/mUC) with standard of care (SOC), a network meta-analysis (NMA) was conducted. A systematic literature review (SLR) identified phase 2 and 3 randomized trials investigating 1L treatment regimens in la/mUC published January 2001-September 2021. Three networks were formed based on cisplatin (cis) eligibility: cis-eligible/mixed (cis-eligible patients and mixed populations of cis-eligible/ineligible patients), cis-ineligible (strict; exclusively cis-ineligible patients), and cis-ineligible (wide; including studies with investigator's choice of carbo). Analyses examined comparative efficacy by hazard ratio (HR) for overall survival (OS), and progression-free survival (PFS), and odds ratio (OR) for overall response rate (ORR), with 1L regimens vs. SOC. SOC was gemcitabine + cis (GemCis) or carboplatin (GemCarbo), cis-eligible/mixed network, and GemCarbo cis-ineligible networks. Of 1906 SLR identified citations, 55 trials were selected for data extraction. The NMA comprised 11, 6, and 8 studies in the cis-eligible/mixed, cis-ineligible (strict), cis-ineligible (wide) networks, respectively. In a meta-analysis of SOC control arms, median (95% CI) overall survival (OS) in months varied by network: 13.19 (12.43, 13.95) cis-eligible/mixed, 11.96 (10.43, 13.48) cis-ineligible (wide), and 9.74 (6.71, 12.76) cis-ineligible (strict). Most differences in OS, PFS, and ORR with treatment regimens across treatment networks were not statistically significant compared with SOC. Outcomes with current 1L regimens remain poor, and few significant improvements over SOC have been made, despite inclusion of recent clinical trial data, highlighting an unmet need in the la/mUC patient population.
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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 | 0.041 | 0.102 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".