The association between 'compliance with colonoscopy surveillance' after primary treatment and healthcare utilization
Bibliographic record
Abstract
Choosing Wisely Canada recommends surveillance with colonoscopy for colorectal cancer patients undergoing curative-intent treatment. Although surveillance with colonoscopy after surgery is beneficial in terms of early detection of recurrence and survival, there is limited real-world evidence on the compliance of recommended colonoscopy surveillance, and the health utilization and costs associated with it. This retrospective study uses existing administrative data sets from Alberta Health Services and Alberta Health, which includes 7120 observations for the 2004-2015 period. The study sample consisted of colorectal cancer patients at stages I and II, who underwent curative-intent surgery. This project compared healthcare utilization (measured by cost) and health outcomes (measured by survival) for patients who complied with colonoscopy surveillance, versus those who did not comply. Cost and survival analysis were conducted, employing multivariate analyses via COX and logistic regressions. For the purposes of this study, cost data was calculated using the physician claims or the physician’s payment. In total, 6,962 patients were eligible for analysis. The median age was 67 (range: 18-104) years old. The proportion of patients with stage Ⅰ and Ⅱ colorectal cancer was 42.46% and 57.54%, respectively. A total of 2,812 (40.39%) patients had a one-year compliance, and 275 patients (3.95%) had two-to-five-year compliance. The average healthcare utilization of one-year and two-to-five-year compliance per person was 3,762 and 4,758 in CAD dollars, respectively. Compliance with colonoscopy surveillance after a primary treatment was associated with lower age, earlier cancer stage (stage Ⅰ), lower cancer grade (grade 1), lower CCI, and higher income. In addition, the overall death ratio and cancer-related death ratio was lower for those patients with compliance in each category (one-year and two-five-year follow-up), compared to those with no compliance. The results of this study suggest that colonoscopy surveillance compliance following primary treatment for early-stage colorectal cancer is associated with lower healthcare utilization and better cancer-specific survival.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".