Second-Line Systemic Therapies for Metastatic Urothelial Carcinoma: A Population-Based Cohort Analysis
Bibliographic record
Abstract
Introduction: Patients with urothelial carcinoma (uc) have a poor prognosis after progression on first-line cisplatinbased chemotherapy. Real-world data about second-line cytotoxic therapies are limited. We sought to characterize patients with metastatic uc who receive more than 1 line of systemic therapy and to describe their treatments and outcomes. Methods: Using BC Cancer’s pharmacy database, we identified patients with documented metastatic uc who had received more than 1 line of systemic therapy. A retrospective chart review was then performed to collect clinicopathologic, treatment, and outcomes data. Results: The 51 included patients, of whom 42 were men (82%), had a median age of 65 years (range: 38–81 years). Sites of metastasis included lymph nodes (n = 30), bone (n = 7), lung (n = 9), and peritoneum (n = 2). Second-line chemotherapy regimens included gemcitabine–cisplatin [gc (n = 14)], paclitaxel (n = 24), docetaxel (n = 12), and an oral topoisomerase i inhibitor (n = 1). Median time to progression (ttp) and overall survival (os) were 2.0 and 6.83 months respectively. Compared with patients who received a different agent, patients who had experienced a prior response to first-line gc and who were re-challenged with second-line gc had a better median ttp (11.0 months vs. 6.0 months, p = 0.02) and survived longer (4.0 months vs. 1.0 months, p = 0.02). No differences in os between non-gc regimens were evident. Conclusions: In patients with metastatic uc, overall outcomes remain poor, but compared with patients receiving other agents, the subgroup of patients re-challenged with second-line gc demonstrated improved ttp. Conventional chemotherapy regimens provide only modest benefits in the second-line setting and have largely been replaced with immunotherapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".