Differential utilization of preventive care among colon cancer survivors compared to non-cancer patients.
Bibliographic record
Abstract
577 Background: With advances in diagnosis and treatment, many cancer patients survive more than 5 years. The care of these cancer survivors (CS) represent an area of unmet need. We aim to characterize the patterns of preventive care in colon CS compared to non-cancer controls (NCC) and identify areas of deficiencies within the context of a universal health care system. Methods: Adult patients with non-metastatic colon cancer treated at the BC Cancer Agency between 2000-2012 were included. An age and gender matched cohort constructed from the provincial database served as NCC. Areas of preventive care examined include vaccinations, cancer, osteoporosis and cardiovascular diseases (CVD) screening. Multivariate regressions were done to test for associations between CS and preventive care. Results: In total, 9381 colon CS and 47187 NCC, matched at a ratio of 1:5, were analyzed. Among CS, median age of diagnosis was 68, 58% were male and 47% had stage 3 disease. The median overall survivals were 12/10/8 years for stages 1/2/3 disease respectively. 61% of these survivors died from colon cancer, 12% from other cancers and 25% from non-cancer causes. Deaths from colon cancer are more common within 5 years of diagnosis, particularly stage 3 disease. CS were more likely to receive any preventive care. In CS compared to NCC, 90% vs 85%, 47% vs 39% and 53% vs 46% of eligible patients had CVD screening, cancer screening and other preventive care respectively. This remained significant in multivariate analyses (Table). Patients who were female, had higher income and resided in urban areas were more likely to receive screening. Among CS, patients > 65 years (OR1.2, p = 0.04 95%CI 1.0-1.4), females (OR 1.5, p < 0.01 95%CI 1.3-1.8) and stages 1 or 2 disease (OR 1.3, p < 0.01 95%CI 1.1-1.5) had higher uptake of screening. Conclusions: Many colon cancer patients are long term survivors. CS are more likely to receive screening than NCC but uptake is suboptimal in certain areas. Targeted education towards certain sub-groups such as males, ≤65 years, low income and rural area patients may improve long term health outcomes. [Table: see text]
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".