Cost-Effectiveness of Colonoscopy-Based Colorectal Cancer Screening in Childhood Cancer Survivors
Bibliographic record
Abstract
BACKGROUND: Childhood cancer survivors (CCS) are at increased risk of developing colorectal cancer (CRC) compared to the general population, especially those previously exposed to abdominal or pelvic radiation therapy (APRT). However, the benefits and costs of CRC screening in CCS are unclear. In this study, we evaluated the cost-effectiveness of early-initiated colonoscopy screening in CCS. METHODS: We adjusted a previously validated model of CRC screening in the US population (MISCAN-Colon) to reflect CRC and other-cause mortality risk in CCS. We evaluated 91 colonoscopy screening strategies varying in screening interval, age to start, and age to stop screening for all CCS combined and for those treated with or without APRT. Primary outcomes were CRC deaths averted (compared to no screening) and incremental cost-effectiveness ratios (ICERs). A willingness-to-pay threshold of $100 000 per life-years gained (LYG) was used to determine the optimal screening strategy. RESULTS: Compared to no screening, the US Preventive Services Task Force's average risk screening schedule prevented up to 73.2% of CRC deaths in CCS. The optimal strategy of screening every 10 years from age 40 to 60 years averted 79.2% of deaths, with ICER of $67 000/LYG. Among CCS treated with APRT, colonoscopy every 10 years from age 35 to 65 years was optimal (CRC deaths averted: 82.3%; ICER: $92 000/LYG), whereas among those not previously treated with APRT, screening from age 45 to 55 years every 10 years was optimal (CRC deaths averted: 72.7%; ICER: $57 000/LYG). CONCLUSIONS: Early initiation of colonoscopy screening for CCS is cost-effective, especially among those treated with APRT.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".