Improving cancer surveillance for breast, colorectal, and prostate cancer: Actionable recommendations for the BETTER Program
Bibliographic record
Abstract
Context: Cancer and chronic disease prevention and screening (CCDPS) guidelines are not consistently applied in primary care. Cancer survivors are not only at risk of cancer recurrence but also remain at risk for other cancers and chronic diseases. Despite closer monitoring, cancer survivors achieve fewer prevention and screening goals than the general population. The BETTER program (Building on Existing Tools to Improve Chronic Disease Prevention and Screening in Primary Care) involves an evidence-based intervention provided by a healthcare professional with specialized skills in CCDPS and cancer surveillance, the Prevention Practitioner (PP). Guided by the BETTER toolkit, the PP meets with patients to assess their risk for cancer and chronic disease, and for patients with a personal history of breast, colorectal, or prostate cancer, also determines their cancer surveillance status. Objectives: To describe the: 1) evidence review process used to identify high-quality clinical practice guidelines (CPGs), 2) harmonization of cancer survivorship recommendations for breast, colorectal, and prostate cancer, and 3) identification, development, and refinement of resources and tools for inclusion in the BETTER toolkit. The BETTER toolkit will be used to inform cancer survivorship care in rural, remote, and urban primary care settings across Canada. Design: In 2017, the BETTER Program conducted a literature review of evidence-based CPGs published between 2010 and 2016. For this update, high-quality international, Canadian, and Provincial CPGs published between 2016 and 2021, focusing on breast, colorectal, or prostate cancer survivorship, and applicable to patients 40-69 years of age were identified. A Clinical Working Group reviewed the high-quality literature identified through a rigorous search, synthesized guidelines based on evidence, and updated the toolkits to inform the PP role. Setting: Rural, remote, and urban settings in Canada. Participants: Canadian researchers, clinicians, decision-makers, a patient representative. Results: Development of an updated care map for breast, colorectal, and prostate cancer surveillance that considers method of cancer treatment, long-term symptoms, and symptoms of recurrence that is tailored to the patient and adaptable to diverse practice settings. Conclusions: Synthesized and evidence-based integrated care paths can be used to assess patients’ cancer survivorship status and preferences in diverse populations in Canada.
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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 | 0.090 | 0.232 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".