Cost-effectiveness analysis of colorectal cancer screening in a low incidence country
Bibliographic record
Abstract
Background: Colorectal cancer (CRC) screening is cost-effective in many Western countries, and many have successfully implemented CRC screening programs. For countries with a lower CRC incidence, like Saudi Arabia, the value of CRC screening is less evident and requires careful weighing of harms, benefits, and costs. Methods: We used the MISCAN-Colon microsimulation model to simulate a male and female cohort with life expectancy and CRC risk as observed in Saudi Arabia. For both cohorts, we evaluated strategies without screening, with annual or biennial faecal immunochemical testing (FIT), and with 10-yearly or once-only colonoscopy. We also considered different start and end ages of screening. For both cohorts, we estimated lifetime costs and effects of each strategy. We then identified a set of potentially cost-effective strategies using incremental cost-effectiveness ratios (ICERs) defined as the additional cost per additional quality-adjusted life year (QALY). Results: Without CRC screening, an estimated 14 per 1,000 males would develop CRC during their lifetime and 9 would die from CRC. Several strategies proved potentially cost-effective including biennial FIT at ages 55-65 (ICER of $7,400), once-only colonoscopy at age 55 (ICER of $7,700), and 10-yearly colonoscopy at ages 50-65, 45-65, and 45-75 (ICERs of $34,000, 71,000, and 375,000, respectively). For females, risk of CRC was lower and CRC screening was therefore less cost-effective, but efficient strategies were largely similar. Conclusions: Despite low CRC incidence in Saudi Arabia, some FIT or colonoscopy screening strategies may meet reasonable thresholds of cost-effectiveness. The optimal strategy will depend on multiple factors including the willingness to pay per QALY, the colonoscopy capacity, and the accepted budget impact.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.006 | 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".