Management of localized and advanced prostate cancer in Canada: A lifetime cost and quality‐adjusted life‐year analysis
Bibliographic record
Abstract
BACKGROUND: To the authors' knowledge, the literature to date lacks studies examining lifetime costs and quality-adjusted life-years (QALYs) of prostate cancer (PCa) management strategies that integrate localized and advanced disease. The objective of the current study was to assess lifetime costs and QALYs associated with contemporary PCa management strategies across risk groups by integrating localized and advanced disease. METHODS: The authors' validated Markov chain Monte Carlo model was used to predict lifetime direct costs and QALYs. The health states modeled were active surveillance, initial treatments (radical prostatectomy or radiotherapy), PCa recurrence, PCa recurrence free, metastatic castration-resistant prostate cancer, and death (cause specific/other causes). Data regarding treatment distribution, state transition probabilities, adverse effects of management options, costs, utilities, and disutilities were derived from the published literature. RESULTS: The total cost per patient for the overall cohort increased from $18,503 at 5 years to $28,032 and $39,143, respectively, at 10 years and 15 years. Furthermore, the results indicated the influence of risk group on total cost, with the high-risk group accruing the maximum per patient cost followed by the intermediate-risk and low-risk groups. Active surveillance was found to confer the most QALYs (12.5 years) and was the least costly strategy ($18,452) for individuals at low risk. For all risk groups, radical prostatectomy was less costly and conferred modestly more QALYs compared with intensity-modulated radiotherapy modalities. CONCLUSIONS: Public health care systems in Canada and elsewhere are operating under budget constraints to allocate finite resources. The findings of the current study might inform discussions concerning budget planning to provide health care services.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".