Cost‐effectiveness analysis of immediate radical cystectomy versus intravesical <i>Bacillus</i> Calmette‐Guerin therapy for high‐risk, high‐grade (T1G3) bladder cancer
Bibliographic record
Abstract
BACKGROUND: Although both radical cystectomy and intravesical immunotherapy are initial treatment options for high-risk, T1, grade 3 (T1G3) bladder cancer, controversy regarding the optimal strategy persists. Because bladder cancer is the most expensive malignancy to treat per patient, decisions regarding the optimal treatment strategy should consider costs. METHODS: A Markov Monte-Carlo cost-effectiveness model was created to simulate the outcomes of a cohort of patients with incident, high-risk, T1G3 bladder cancer. Treatment options included immediate cystectomy and conservative therapy with intravesical Bacillus Calmette-Guerin (BCG). The base case was a man aged 60 years. Parameter uncertainty was assessed with probabilistic sensitivity analyses. Scenario analyses were used to explore the 2 strategies among patients stratified by age and comorbidity. RESULTS: The quality-adjusted survival with immediate cystectomy and BCG therapy was 9.46 quality-adjusted life years (QALYs) and 9.39 QALYs, respectively. The corresponding mean per-patient discounted lifetime costs (in 2005 Canadian dollars) were $37,600 and $42,400, respectively. At a willingness-to-pay threshold of $50,000 per QALY, the probability that immediate cystectomy was cost-effective was 67%. Immediate cystectomy was the dominant (more effective and less expensive) therapy for patients aged <60 years, whereas BCG therapy was dominant for patients aged >75 years. With increasing comorbidity, BCG therapy was dominant at lower age thresholds. CONCLUSIONS: Compared with BCG therapy, immediate radical cystectomy for average patients with high-risk, T1G3 bladder cancer yielded better health outcomes and lower costs. Tailoring therapy based on patient age and comorbidity may increase survival while yielding significant cost-savings for the healthcare system.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".