The information required by patients with early‐stage prostate cancer in choosing their treatment
Bibliographic record
Abstract
OBJECTIVE: To determine the information that men diagnosed with early-stage prostate cancer think is necessary to choose their treatment (surgery, radiotherapy or 'watchful waiting'). PATIENTS AND METHODS: All men diagnosed with early-stage prostate cancer in a regional urology practice in an 18-month period were surveyed. Respondents considered the treatment decision for a specific hypothetical case and judged whether each of 59 specific information items would be 'necessary' to know to make the treatment decision. Respondents provided basic demographic information (age, education and marital status). RESULTS: Of 89 patients, 71 (80%) responded; the mean (SD, range) number of items that individual respondents identified as necessary was 32 (12, 9-58). Each item was considered necessary by 54 (18, 20-93)% of respondents. Of the 59 items, only five were necessary to > or = 80% of respondents; 23 were necessary to > or = 67% of respondents and five were not necessary to > or = 67% of respondents. Patients were divided about the remaining 31 items. There were no strong correlations (none accounted for > 20% of the variance) between the responses and demographic characteristics. CONCLUSIONS: There appears to be large variation among patients with early-stage prostate cancer in the number of information items deemed necessary to make a treatment decision, and little agreement on the need for most individual items. Demographic characteristics were not useful as predictors of the information needs of each patient. The process of informing patients with early-stage prostate cancer (and their decision aids) needs to be flexible and able to accommodate a wide range of patients' information needs.
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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 | 0.053 |
| 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 | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".