Impact of number of lines of prior chemotherapy in patients (pts) with advanced urothelial carcinoma (UC) receiving salvage therapy.
Bibliographic record
Abstract
353 Background: The prognostic impact of number of lines of prior chemotherapy and prior perioperative chemotherapy on survival results in salvage trials for advanced UC is unknown. Methods: We pooled 10 prospective phase II trials of salvage therapy for advanced UC with data on the number of prior lines of therapy in addition to known prognostic factors: TFPC (time from prior chemotherapy), Hb (hemoglobin), PS (performance status), and LM (liver metastasis) status. Cox proportional hazards regression was used to evaluate the association of number of prior lines with overall survival (OS) and progression-free survival (PFS). Trial was included as a stratification factor. Sub-analysis examined the impact of prior perioperative chemotherapy. Results: Of 731 pts, data for all factors was available for 711. The overall median PFS and OS were 2.7 and 6.8 months, respectively. Trials evaluated vinflunine (N=151), docetaxel +/- vandetanib (N=147), paclitaxel-gemcitabine (N=83), sunitinib (N=77), nab-paclitaxel (N=48), volasertib (N=46), everolimus (N=45), pazopanib (N=43), cetuximab +/-paclitaxel (N=39) and paclitaxel-cyclophosphamide (N=32). The number of prior lines of therapy were 1 in 559 (78.6%), 2 in 111 (15.6%), 3 in 29 (4.1%), 4 in 10 (1.4%) and 5 in 2 (0.3%) pts. Prior perioperative chemotherapy was given to 277 (39.1%) and chemotherapy for metastatic disease to 454 (64.1%) pts. While TFPC, Hb, PS and LM were significantly associated with OS and PFS on multivariate analyses, the number of prior lines was not associated with OS (HR 0.99 [95% CI: 0.86-1.14]) or PFS (0.92 [0.80-1.05]). Prior peri-operative chemotherapy was a favorable factor for both OS and PFS on univariable but not multivariable analysis. Conclusions: The number of prior lines of therapy and prior perioperative chemotherapy were not independently prognostic for OS or PFS in UC pts receiving salvage therapy, although the data are limited by few pts with >2 prior regimens. We infer that interpretation of OS and PFS results in salvage therapy trials will not be affected by inclusion of pts with ≥ 2 prior regimens including perioperative and/or metastatic disease treatment. These data need external validation.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".