Adjuvant chemotherapy for bladder cancer does not alter cancer‐specific survival after cystectomy in a matched case‐control study
Bibliographic record
Abstract
OBJECTIVE: To assess the effect of adjuvant chemotherapy (ACHT; methotrexate, vinblastine, adriamycin and cisplatin, MVAC, or gemcitabine/cisplatin, GC) on the rate of cancer-specific survival and overall survival, as the benefit of ACHT after radical cystectomy (RC) for bladder cancer is controversial. PATIENTS AND METHODS: Within a study group of 958 patients treated with RC between 1984 and 2003, we identified 274 (29.0%) with a high risk of progression due to pT3 or pT4 and/or pN1-3 stages. Of these, 129 (46.6%) received ACHT (MVAC in 103, GC in 26). These patients were then matched with the remaining patients who were unexposed to ACHT. Exact matches were made for pT stage, tumour grade, pN stage and lymphovascular invasion. Age (+/-5 years) and year of surgery (+/-5 years) were calliper-matched. Matching resulted in 62 patients treated with RC/ACHT and 65 treated with RC alone. Kaplan-Meier, life-table and Cox regression analyses were used to assess cancer-specific and overall survival. RESULTS: There was no statistically significant difference in cancer-specific survival probabilities at 5 years after RC between the two groups (relative risk 1.2; P = 0.5). There was also no difference in overall survival at 5 years (1.1; P = 0.7). In multivariable analyses the delivery of adjuvant chemotherapy was not an independent predictor for survival endpoints (P = 0.3 for cancer-specific and 0.3 for overall survival). CONCLUSIONS: This matched case-control analysis showed that either MVAC or GC chemotherapy had no effect on cancer-specific or overall survival after RC in high-risk patients. Further randomized long-term studies are necessary to confirm these results.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".