Cost-effectiveness of computerized tomographic colonography versus colonoscopy for colorectal cancer screening
Bibliographic record
Abstract
BACKGROUND: Computerized tomographic (CT) colonography is a potential alternative to colonoscopy for colorectal cancer screening. Its main advantage, a better safety profile, may be offset by its limitations: lower sensitivity, need for colonoscopy in cases where results are positive, and expense. METHODS: We performed an economic evaluation, using decision analysis, to compare CT colonography with colonoscopy for colorectal cancer screening in patients over 50 years of age. Three-year outcomes included number of colonoscopies, perforations and adenomas removed; deaths from perforation and from colorectal cancer from missed adenomas; and direct health care costs. The expected prevalence of adenomas, test performance characteristics of CT colonography and colonoscopy, and probability of colonoscopy complications and cancer from missed adenomas were derived from the literature. Costs were determined in detail locally. RESULTS: Using the base-case assumptions, a strategy of CT colonography for colorectal cancer screening would cost 2.27 million dollars extra per 100,000 patients screened; 3.78 perforation-related deaths would be avoided, but 4.11 extra deaths would occur from missed adenomas. Because screening with CT colonography would cost more and result in more deaths overall compared with colonoscopy, the latter remained the dominant strategy. Our results were sensitive to CT colonography's test performance characteristics, the malignant risk of missed adenomas, the risk of perforation and related death, the procedural costs and differences in screening adherence. INTERPRETATION: At present, CT colonography cannot be recommended as a primary means of population-based colorectal cancer screening 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 | 0.004 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".