Predictors of costs associated with radical cystectomy for bladder cancer: A population‐based retrospective cohort study in the province of Quebec, Canada
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: There is paucity of studies on the predictors of bladder cancer (BC) management costs. We aimed to determine predictors of costs associated with radical cystectomy (RC) for BC. METHODS: We conducted a retrospective analysis in a cohort of 2,759 patients who underwent RC for BC between 2000 and 2009. We analyzed predictors of pre-surgery, RC, post-surgery, and total costs. The following variables were considered as potential predictors: age, gender, hospital/surgeon case load, academic hospital, and geo-administrative region. Multivariate linear regression was used to determine predictors. RESULTS: Predictors of pre-surgery costs were: age (β = 808.64, P < 0.0001) and having surgery in an academic hospital (β = 511.42, P = 0.003). Increased RC costs were associated with age (β = 196.73, P = 0.0006), hospital/surgeon annual load (β = 484.45 and β = 254.21, P < 0.0001, respectively). Having surgery in academic hospitals and geographic region were significant predictors of low RC costs (β = -1085.82 and β = -449.31, P < 0.0001, respectively). Increasing age and the presence of post-operative complications were predictors of high post-operative costs (β = 623.48, β = 5781.44, P = 0.01, respectively), while hospital load was associated with low post-surgery costs (β = -949.79, P < 0.0001). CONCLUSION: Patients' age and surgery performed by high-volume health providers were predictive factors of high RC costs. Low RC costs were associated with surgeries performed in academic hospitals.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".