A population‐based competing‐risks analysis of the survival of patients treated with radical cystectomy for bladder cancer
Bibliographic record
Abstract
BACKGROUND: Patients treated with radical cystectomy represent a very heterogeneous group with respect to cancer-specific and other-cause mortality. Comorbidities and comorbidity-associated events represent very important causes of mortality in those individuals. The authors examined the rates of cancer-specific and other-cause mortality in a population-based radical cystectomy cohort. METHODS: The authors identified 11,260 patients treated with radical cystectomy for urothelial carcinoma of the urinary bladder between 1988 and 2006 within 17 Surveillance, Epidemiology, and End Results registries. Patients were stratified into 20 strata according to patient age and tumor stage at radical cystectomy. Smoothed Poisson regression models were fitted to obtain estimates of cancer-specific and other-cause mortality rates at specific time points after radical cystectomy. RESULTS: After stratification according to disease stage and patient age, cancer-specific mortality emerged as the main cause of mortality in all patient strata. Nonetheless, at 5 years after radical cystectomy, between 8.5% and 27.1% of deaths were attributable to other-cause mortality. The 3 most common causes of other-cause mortality were other malignancies, heart disease, and chronic obstructive pulmonary disease. The most prominent effect on cancer-specific mortality was exerted by locally advanced bladder cancer stages. Conversely, age was the main determinant of other-cause mortality. Interestingly, even after adjusting for bladder cancer pathologic stage, cancer-specific mortality was higher in older individuals than their younger counterparts. CONCLUSIONS: The current study provides a valuable graphical aid for prediction of cancer-specific and other-cause mortality according to disease stage and patient age. It can help clinicians to better stratify the risk-benefit ratio of radical cystectomy. Hopefully, these findings will be considered in treatment decision making and during informed consent before radical cystectomy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 teacher head, 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".