Concomitant Carcinoma in situ in Cystectomy Specimens Is Not Associated with Clinical Outcomes after Surgery
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to externally validate the prognostic value of concomitant urothelial carcinoma in situ (CIS) in radical cystectomy (RC) specimens using a large international cohort of bladder cancer patients. METHODS: The records of 3,973 patients treated with RC and bilateral lymphadenectomy for urothelial carcinoma of the bladder (UCB) at nine centers worldwide were reviewed. Surgical specimens were evaluated by a genitourinary pathologist at each center. Uni- and multivariable Cox regression models addressed time to recurrence and cancer-specific mortality after RC. RESULTS: 1,741 (43.8%) patients had concomitant CIS in their RC specimens. Concomitant CIS was more common in organ-confined UCB and was associated with lymphovascular invasion (p < 0.001). Concomitant CIS was not associated with either disease recurrence or cancer-specific death regardless of pathologic stage. The presence of concomitant CIS did not improve the predictive accuracy of standard predictors for either disease recurrence or cancer-specific death in any of the subgroups. CONCLUSIONS: We could not confirm the prognostic value of concomitant CIS in RC specimens. This, together with the discrepancy between pathologists in determining the presence of concomitant CIS at the morphologic level, limits the clinical utility of concomitant CIS in RC specimens for clinical decision-making.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".