A Primary Care Initiative for Cancer Survivorship: A Case Study of Cancer in Obese Men
Bibliographic record
Abstract
Background: Men in rural and northern areas of Canada experience considerable challenges in health care access for chronic conditions such as obesity, type 2 diabetes (T2D), and cancer. Obese men (body mass index/BMI ≥ 30 kg/m2) in rural/remote northern British Columbia (BC) experience poorer health outcomes due to cancer risk compared to other men elsewhere in urban Canada. Context: Challenges faced by men who develop cancer as a complication of being obese are paramount in terms of primary care treatment of their cancers. Oftentimes cancer treatment is multi-modal and complex. Models of shared care have been proposed to provide coordinated survivorship care to the growing population of rural male cancer patients suffering from obesity and the Metabolic Syndrome (MetS). Methods: Objectives: The main objective of the study was to examine the type of cancer care programs that may have focused on men with cancer in northern British Columbia (BC). A secondary objective is to identify challenges in care experienced by men with cancer during their transition from in-hospital care back to their home communities. Population: We conducted a comprehensive literature review and a qualitative focus group interview with primary care physicians (PCPs), oncologists (n=8), and a convenience sample of male cancer patients (n=6) who have underlying obesity and Metabolic Syndrome (MetS). We examined the types of cancer care programs that may have targeted such men. We further identified challenges experienced by male cancer patients while transitioning back to their home communities. Results: The focus group results outlined themes speaking to a comprehensive shared care model that goes beyond surveillance of cancer recurrence in men with obesity. Conclusion: A shared survivorship care plan or model integrates collaboration among specialists in clinical decision making and best practice for treatment of cancer in obese men.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".