Survival after radical cystectomy of non‐bilharzial squamous cell carcinoma vs urothelial carcinoma: a competing‐risks analysis
Bibliographic record
Abstract
Study Type – Therapy (case series) Level of Evidence 4 What's known on the subject? and What does the study add? To date, there is controversy about the impact of histological subtype of bladder cancer (nonbilharzial squanous cell carcinoma vs. urothelial carcinoma) on cancer control outcomes. Our study shows that the histological subtype may have an impact on the stage of bladder cancer at presentation. However, after adjusting to stage, the histological subtype has no impact on cancer control outcomes. OBJECTIVES To test the effect of histological subtype (NBSCC vs UC) on cancer‐specific mortality (CSM), after adjusting for other‐cause mortality (OCM). In Western countries, non‐bilharzial squamous cell carcinoma (NBSCC) is the second most common histological subtype in bladder cancer (BCa) after urothelial carcinoma (UC). PATIENTS AND METHODS We identified 12 311 patients who were treated with radical cystectomy (RC) between 1988 and 2006, within 17 Surveillance, Epidemiology and End Results (SEER) registries. Univariable and multivariable competing‐risks analyses tested the relationship between histological subtype and CSM, after accounting for OCM. Covariates consisted of age, sex, year of surgery, race, pathological T and N stages, as well as tumour grade. RESULTS Histological subtype was NBSCC in 614 (5%) patients vs UC in 11 697 (95%) patients. At RC, the rate of non‐organ confined (NOC) BCa was higher in NBSCC patients than in their UC counterparts (71.7% vs 52.2%; P < 0.001). After adjustment for OCM, The 5‐year cumulative CSM rates were 25.0% vs 19.8% ( P = 0.2) for patients with NBSCC vs UC organ confined (OC) BCa, respectively. The same rates were 46.3% vs 49.3% in patients with NOC BCa ( P = 0.1). In multivariable competing‐risks analyses, histological subtype (NBSCC vs UC) failed to achieve independent predictor status of CSM in patients with OC (hazard ratio, 1.2; P = 0.06) or NOC BCa (hazard ratio, 1.1; P = 0.1). CONCLUSIONS At RC, the rate of NOC BCa is higher in NBSCC patients than in their UC counterparts. Despite a more advanced stage at surgery, NBSCC histological subtype is not associated with a less favourable CSM than UC histological subtype, after accounting for OCM and the extent of the disease (OC vs NOC).
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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 | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".