Contemporary cost‐effectiveness analysis comparing sequential bacillus Calmette‐Guerin and electromotive mitomycin versus bacillus Calmette‐Guerin alone for patients with high‐risk non–muscle‐invasive bladder cancer
Bibliographic record
Abstract
BACKGROUND: Sequential bacillus Calmette-Guerin (BCG) and electromotive mitomycin (sequential therapy) have been shown in a randomized prospective trial to be superior to therapy with BCG alone in patients with high-risk non-muscle-invasive bladder cancer. The objective of the current study was to compare the costs and benefits of these 2 treatment strategies by performing a 5-year and 10-year cost-effectiveness study. METHODS: A Markov model was developed to estimate the incremental cost-effectiveness ratio over a 5-year and 10-year period. Estimates of disease progression, death, and treatment efficacy were obtained from what to the authors' knowledge is the only randomized trial comparing the 2 therapies. Costs included: 1) medical costs (physician fees); 2) drug costs (preparation and instillation); and 3) hospital costs (procedure fees, admission fees, and tests and procedures done during surveillance). Patients were allowed a second course of induction therapy. RESULTS: Sequential therapy was found to be associated with a higher initial material cost for induction and maintenance. The average effectiveness for the patients treated with therapy with BCG alone was 4.39 years with a mean cost of $9236 (95% confidence interval, $9118-$9345) per patient. The sequential group resulted in an average effectiveness of 4.65 years, with a mean cost of $16,468 (95% confidence interval, $16,371-$16,527). The 5-year incremental cost-effectiveness ratio of sequential versus BCG-alone therapy was $27,815 per life-year gained. The corresponding figure over a 10-year period was $8618 per life-year gained. CONCLUSIONS: The results of the current study suggest that sequential therapy is a cost-effective treatment for patients with high-risk non-muscle-invasive bladder cancer.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".