CT Colonography Versus Optical Colonoscopy: Cost-Effectiveness in Colorectal Cancer Screening
Bibliographic record
Abstract
Purpose: CT colonography (CTC) has been accepted as an optical colonoscopy (OC) alternative for colorectal cancer (CRC) screening by some guidelines, while others maintain that the data is insufficient. CTC’s less invasive nature may improve compliance; however, cost and need for colonoscopy, if lesions are detected, remain an obstacle for implementation. As a result, the authors set out to determine the cost-effectiveness of CTC in the context of its drawbacks and advantages when compared with OC within a Canadian context. Methods: Using a decision analysis software, an economic analysis was performed comparing CTC to OC for CRC screening in asymptomatic patients. The 10-year primary outcome measure was study cost, cost difference of screening 100,000 patients, and the cost of one quality adjusted life year gained. The sensitivities, specificities, and polyp prevalence rates were derived from literature. The cost of each test was derived from local data. Results: Local cost of OC is 764.36 CAD compared to 580.01 CAD for CTC. In the case of a normal OC, reassessment would not be necessary for 10 years, whereas in an asymptomatic average-risk population CTC must be repeated every 5 years. The incremental cost-effectiveness ratio, or the additional cost per life year of OC compared to CTC was calculated to be 3,390.76 CAD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.026 |
| 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) | 0.003 | 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".