Direct Cost for Initial Management of Prostate Cancer: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Prostate cancer (pca) is the most common non-skin cancer among men in Canada and other Western countries. Increased prevalence and higher cost of newer treatments have led to a significant rise in the economic burden of pca. The objectives of the present study were to systematically review the literature on direct costs for the initial management of pca, and to examine the methodologic considerations across studies. METHODS: Bibliographic databases were systematically searched for peer-reviewed articles in English. Studies were reviewed for methodologic considerations and mean direct cost of active surveillance or watchful waiting (as/ww) and initial treatments. Direct cost was standardized to 2011 Canadian dollars. RESULTS: After a review of abstracts and full-text papers, seventeen articles met the eligibility criteria and were included in the review. Studies were published during 1992-2010. The studies reported on health care systems in the United States, France, the United Kingdom, German, Italy, and Spain. Our review identified a lack of methodologic consensus, leading to variation in direct costs between studies. Nevertheless, results indicate a significant direct cost of pca treatments. CONCLUSIONS: The existing literature lacks methodologically rigorous studies on the direct costs of pca treatments specific to publicly funded health care systems. Additional studies are required to appreciate the direct costs of newer treatments and the impact of their adoption on the growing economic burden of pca management.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".