Information for Decision Making by Patients With Early-Stage Prostate Cancer
Bibliographic record
Abstract
PURPOSE: To describe decisional roles of patients with early-stage prostate cancer in 9 countries and to compare the information they rated important for decision making (DM). METHOD: A survey of recently treated patients was conducted in Canada, Italy, England, Germany, Poland, Portugal, Netherlands, Spain, and Turkey. Participants indicated their decisional role in their actual decision and the role they would prefer now. Each participant also rated (essential/desired/no opinion/avoid) the importance of obtaining answers, between diagnosis and treatment decision, to each of 92 questions. For each essential/desired question, participants specified all purposes for that information (to help them: understand/decide/plan/not sure/other). RESULTS: A total of 659 patients participated with country-specific response rates between 58%-77%. Between 83%-96% of each country's participants recalled actually taking an active decisional role and, in most countries, that increased slightly if they were to make the decision today; there were no significant differences among countries. There was a small reliable difference in the mean number of questions rated essential for DM across countries. More striking, however, was the wide variability within each country: no question was rated essential for DM by even 50% of its participants but almost every question was rated essential by some. CONCLUSIONS: Almost all participants from each country want to participate in their treatment decisions. Although there are country-specific differences in the amount of information required, wide variation within each country suggests that information that patients feel is essential or desired for DM should be addressed on an individual basis in all countries.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".