Values and preferences of men for undergoing prostate-specific antigen screening for prostate cancer: a systematic review
Bibliographic record
Abstract
OBJECTIVES: To investigate men's values and preferences regarding prostate-specific antigen (PSA)-based screening for prostate cancer. DESIGN: Systematic review. DATA SOURCES: We searched MEDLINE, EMBASE, PsycINFO and grey literature up to 2 September 2017. ELIGIBILITY CRITERIA: Primary studies of men's values and preferences regarding the benefits and harms of PSA screening. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers extracted data and assessed risk of bias with a modified version of a risk of bias tool for values and preferences studies, the International Patient Decision Aid Standards instrument V.3 and the Cochrane Collaboration risk of bias tool. RESULTS: We identified 4172 unique citations, of which 11 studies proved eligible. Five studies investigated PSA screening using a direct choice study design, whereas six used decisions aids displaying patient-important outcomes. The direct choice studies used different methodologies and varied considerably in the reporting of outcomes. Two studies suggested that men were willing to forego screening with a small benefit in prostate cancer mortality if it would decrease the likelihood of unnecessary treatment or biopsies. In contrast, one study reported that men were willing to accept a substantial overdiagnosis to reduce their risk of prostate cancer mortality. Among the six studies involving decision aids, willingness to undergo screening varied substantially from 37% when displaying a hypothetical reduction in mortality of 10 per 1000 men, to 44% when displaying a reduction in mortality of 7 per 1000. We found no studies that specifically investigated whether values and preferences differed among men with family history, of African descent or with lower socioeconomic levels. CONCLUSION: The variability of men's values and preferences reflect that the decision to screen is highly preference sensitive. Our review highlights the need for shared decision making in men considering prostate cancer screening. TRIAL REGISTRATION NUMBER: CRD42018095585.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".