Impact of number of cycles of platinum-based first-line chemotherapy for advanced urothelial carcinoma.
Bibliographic record
Abstract
426 Background: 6 cycles of platinum-based chemotherapy (CT) are conventionally targeted to treat locally advanced unresectable or metastatic urothelial carcinoma (UC). However, cisplatin is associated with significant cumulative toxicities, which render it challenging to deliver 6 cycles. Since this issue has not been investigated prospectively, we conducted a retrospective analysis. Methods: The Retrospective International Study of Invasive/Advanced Cancer of the Urothelium (RISC) database was used to conduct a retrospective analysis. The association of the number of cycles of platinum-based first-line CT with overall survival (OS) was investigated by a Cox regression utilizing multivariate analysis after controlling for previously recognized prognostic factors used in a nomogram ( Eur Urol, 2017). The primary analysis was a comparison of < 6 cycles vs. ≥6 cycles. Six-month landmark analysis was applied throughout, accounting for OS events. Additionally, we excluded patients (pts) receiving < 3 or > 9 cycles to reduce confounding due to early removal for toxicities, progression and patient decision and increased number of cycles due to response and pt-related factors. Results: Of 1020 pts available from RISC, 472 (cisplatin = 338, carboplatin = 134) were evaluable for the landmark analysis with 281 events. A total of 157 pts received 3-5 cycles (median 4) and 315 received 6-9 cycles (median 6). There was no significant difference between 3-5 vs. 6-9 cycles of platinum-based chemotherapy (HR 1.02, 95%CI: 0.77-1.33, p = 0.91). No significant interactions were observed with type of platinum (p = 0.09) and “completed planned CT” (p = 0.56). Comparison of 4 vs. 6 cycles (p = 0.57) and < 6 vs 6 vs 7-9 (p = 0.9) also yielded no significant differences for association with OS. No differential association was observed with survival for 3-5 vs. 6-9 cycles when examining by nomogram-defined risk group tertiles. Limitations of a hypothesis-generating retrospective analysis apply. Conclusions: 4 cycles of platinum based first-line CT appear adequate to treat advanced UC. The omission of excessive cycles will avoid unnecessary toxicities and facilitate better transition to second-line and switch maintenance therapy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".