Adjuvant cisplatin‐based combined chemotherapy for lymph node ( <scp>LN</scp> )‐positive urothelial carcinoma of the bladder ( <scp>UCB</scp> ) after radical cystectomy ( <scp>RC</scp> ): a retrospective international study of >1500 patients
Bibliographic record
Abstract
OBJECTIVE: To compare outcomes of patients with lymph node (LN)-positive urothelial carcinoma of the bladder (UCB) treated with or without cisplatin-based combined adjuvant chemotherapy (AC) after radical cystectomy (RC). PATIENTS AND METHODS: We retrospectively analysed 1523 patients with LN-positive UCB, who underwent RC with bilateral pelvic LN dissection. All patients had no evidence of disease after RC. AC was administered within 3 months. Competing-risks models were applied to compare UCB-related mortality. RESULTS: Of the 1523 patients, 874 (57.4%) received AC. The cumulative 1-, 2- and 5-year UCB-related mortality rates for all patients were 16%, 36% and 56%, respectively. Administration of AC was associated with an 18% relative reduction in the risk of UCB-related death (subhazard ratio 0.82, P = 0.005). The absolute reduction in mortality was 3.5% at 5 years. The positive effect of AC was detectable in patients aged ≤70 years, in women, in pT3-4 disease, and in those with a higher LN density and lymphovascular invasion. This study is limited by its retrospective and non-randomised design, selection bias, the absence of central pathological review and lack in standardisation of LN dissection and cisplatin-based protocols. CONCLUSION: AC seems to reduce UCB-related mortality in patients with LN-positive UCB after RC. Younger patients, women and those with high-risk features such as pT3-4 disease, a higher LN density and lymphovascular invasion appear to benefit most. Appropriately powered prospective randomised trials are necessary to confirm these findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".