Impact of Follow-Up Colonoscopy Quality on Canadian Colorectal Cancer Outcomes and Costs
Bibliographic record
Abstract
Background: Most colorectal cancer (CRC) cases develop from precancerous polyps. Screening using fecal testing for occult blood, with follow-up diagnostic colonoscopy to remove polyps, can prevent invasive cancer from occurring. However, there is variation in the quality of colonoscopy, which may result in nonoptimal health outcomes. Aim: We evaluated the impact of follow-up colonoscopy quality on health outcomes, resource utilization and costs using the OncoSim-CRC microsimulation model (version 2.5). Methods: OncoSim is a microsimulation model led by the Canadian Partnership Against Cancer with model development by Statistics Canada. We compared results of high quality follow-up colonoscopy after positive fecal immunochemical testing (FIT) (colonoscopy sensitivity for cancer detection= 95%; compliance to follow-up colonoscopy = 85%) with that of reduced quality colonoscopy. Variations in colonoscopy performance were simulated through plausible overall effectiveness reduction (ER) and incomplete colonoscopy (IC). Screening system/patient follow-up deficiencies were simulated through poor compliance to diagnostic colonoscopy (PC). Modeling assumptions included: Biennial FIT screening of average-risk people aged 50-74; positive FIT followed by diagnostic colonoscopy; ER = 20% reduction in overall sensitivity; IC = zero sensitivity in proximal colon; PC = compliance reduction by 50%. Overall cost was calculated for 2017-2036 in undiscounted 2016 CAD, and included screening, treatment and end-of-life costs. Results: Compared with high quality colonoscopy follow-up, incomplete colonoscopy with poor compliance over 20 years led to as many as 12% new cases of CRC; 23% more CRC deaths; 89% more interval cancers; and 6% increased costs to the health care system, annually. Conclusion: Reduced colonoscopy quality can lead to considerable declines in the predicted effectiveness of screening and to increased costs to the healthcare system. Efforts to increase and maintain colonoscopy performance is a necessary component of CRC control planning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".