Residual Pathological Stage at Radical Cystectomy Significantly Impacts Outcomes for Initial T2N0 Bladder Cancer
Bibliographic record
Abstract
PURPOSE: We hypothesized that in patients with T2N0 stage disease at transurethral bladder tumor resection a lower residual cancer stage (P1N0 or less) at radical cystectomy may correlate with improved outcomes relative to those with residual P2N0 disease. MATERIALS AND METHODS: We analyzed 208 patients with T2N0 stage disease at transurethral bladder tumor resection whose tumors were organ confined at radical cystectomy (P2 or lower, pN0). None received perioperative chemotherapy. Kaplan-Meier as well as univariable and multivariable Cox regression models addressed the effect of residual pT stage at radical cystectomy on recurrence and cancer specific mortality rates. Covariates consisted of age, gender, grade, lymphovascular invasion, carcinoma in situ, number of lymph nodes removed and year of surgery. RESULTS: Residual pT stage at radical cystectomy was P0 in 24 (11.5%) patients, Pa in 9 (4.3%), PCIS in 22 (10.6%), P1 in 35 (16.8%) and P2 in 118 (56.7%). Median followup of censored patients was 55.7 months for recurrence and 52.1 months for cancer specific mortality analyses. The 5-year recurrence-free survival rates of patients with P0/Pa/PCIS, P1 and P2 stage disease were 100%, 85% and 75%, respectively. The 5-year cancer specific survival rates for the same cohorts were 100%, 93% and 81%, respectively. On multivariable analysis the effect of residual stage P1 or lower at radical cystectomy achieved independent predictor status for recurrence (adjusted HR 0.20, p = 0.002) and cancer specific mortality (adjusted HR 0.24, p = 0.02). CONCLUSIONS: Down staging from initial T2N0 bladder cancer at transurethral bladder tumor resection to lower stage at radical cystectomy significantly reduces recurrence and cancer specific mortality. Further validation of this finding is warranted.
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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 | 0.000 |
| 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 | 0.000 |
| 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".