Feasibility and acceptability of a personalised primary prevention strategy for women and men at high risk of breast and prostate cancer: the 3PC study protocol for a pilot randomised controlled trial
Bibliographic record
Abstract
Introduction Several primary prevention strategies, including chemoprevention, prophylactic surgery and lifestyle modifications, have been shown to reduce the risk of breast cancer (BC) and prostate cancer (Pca). However, the uptake of these preventive measures is considered suboptimal, limiting their impact on cancer prevention. A personalised primary prevention strategy has yet to be tested for cancer prevention. Therefore, we aim to determine the feasibility, acceptability and potential benefits and harms of this strategy in women and men at high risk of BC and Pca. Methods and analysis This is a two-arm, parallel-group mixed-methods pilot randomised controlled trial with a 1:1 allocation. The study aims to recruit 60 women and 60 men at high risk of BC and PCa in two specialised sites: the Breast Diseases Center and the Department of Urologic Oncology of the CHU de Québec-Université Laval, Canada. Assessments include intentions to uptake, actual uptake rates of primary preventive measures and decision regret. Feasibility and acceptability of the intervention and the study will be measured by quantifying the recruitment rate, appropriateness of randomisation process and satisfaction metrics. Data will be collected using mixed methods. Quantitative measures will be assessed at baseline and 6 months post randomisation. Quantitative analysis will include descriptive statistics for all variables of interest. Generalised linear mixed models with random intercepts will be used to assess the overall intervention effect. Semistructured interviews will be conducted at the end of follow-up, and a thematic analysis will be performed using NVivo to understand participants’ perspectives. Ethics and dissemination The protocol was approved by the Institutional Review Board of CHU de Québec-Université Laval (4 October 2022; 2023-6315). The findings of the study will be published in a peer-reviewed journal and disseminated at national and international conferences and through social media. Trial registration number The protocol for this study was registered with the International Clinical Trials Registry ( ISRCTN15749766 ) https://doi.org/10.1186/ISRCTN15749766 ).
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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 | 0.069 | 0.060 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.072 | 0.014 |
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".