Split-Dose Cisplatin in Patients With Locally Advanced or Metastatic Urothelial Carcinoma: A Systematic Literature Review and Network Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: on day 1 of a 3-week cycle; however, for many patients, impaired renal or cardiac function, neuropathy, or poor performance status (PS) can preclude the use of cisplatin. A promising alternative is split-dose GC, in which the cisplatin dose is divided over 2 days. METHODS: We conducted a systematic literature review (SLR) and network meta-analysis (NMA) to better understand treatment patterns and comparative effectiveness and safety of split-dose GC vs gemcitabine plus carboplatin (GCa), GC, and methotrexate, vinblastine, doxorubicin, and cisplatin (MVAC). RESULTS: Among 120 identified studies, 16 studies representing 1,767 patients included split-dose GC. Common reasons for choosing split-dose GC were impaired renal function, age > 70 years, comorbidities, and physician preference. Split-dose GC had objective response rates (ORRs) of 39%-80%, median progression-free survival (PFS) of 3.5-9.9 months, and median overall survival (OS) of 8.5-18.1 months. Discontinuation rates due to adverse events were 5%-38%. In the NMA, ORR with split-dose GC was significantly higher than with GCa. PFS and OS for split-dose GC were similar to that observed with the other regimens (GCa, GC, and MVAC). CONCLUSIONS: This is the first SLR and NMA of split-dose GC in la/mUC. Despite heterogeneity in the limited studies included, split-dose GC demonstrated comparable effectiveness and safety profile to those seen with other regimens. Split-dose GC thus has the potential to extend the la/mUC population eligible to receive cisplatin-based regimens and warrants further prospective study.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.026 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".