Editorial comment: understanding the cost of bladder preservation in muscle invasive bladder cancer—an evaluation of radical cystectomy versus trimodal therapy costs
Bibliographic record
Abstract
Bladder cancer represents a significant source of morbidity and mortality worldwide. Nearly 430,000 diagnoses of bladder cancer are made each year leading to approximately 165,000 deaths (1). Within the context of healthcare spending it is a costly diagnosis and has been reported as the most expensive diagnosis per patient lifetime among all cancers (2,3), with a total cost of almost $4 billion annually in the United States in 2010 (4). Previous studies have shown that radical cystectomy (RC) accounts for the largest proportion of costs associated with bladder cancer care (5); however, few studies have evaluated the cost of trimodal therapy (TMT). TMT has progressively been accepted as a viable treatment option for the treatment of muscle-invasive bladder cancer (MIBC) (6-8) and therefore the implications from a healthcare economic perspective have become increasingly important to consider.
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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 | 0.001 | 0.001 |
| 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".