Benefits, Harms, and Burden of Colorectal Cancer Screening Among Childhood Cancer Survivors Previously Treated With Abdominopelvic Radiation
Bibliographic record
Abstract
PURPOSE: Childhood cancer survivors treated with abdominopelvic radiation (RT) are at increased risk of colorectal cancer (CRC), yet adherence to Children's Oncology Group screening guidelines remains low. Estimating the benefits, burdens, and costs of all guideline-recommended screening modalities, including those not previously evaluated, may help identify strategies that align with survivors' preferences and access, potentially improving adherence. METHODS: Using data from the Childhood Cancer Survivor Study and published studies, we adapted a CRC simulation model to evaluate CRC screening among 5-year survivors. Strategies included colonoscopy, multitarget stool DNA (mtsDNA), and fecal immunochemical testing (FIT) at various intervals, starting at age 25-45 years. Outcomes included CRC cases and deaths, additional colonoscopies per additional life-year gained (burden-to-benefit ratio [BBR]), and cost per quality-adjusted life-year gained (QALYG; incremental cost-effectiveness ratios [ICERs]). RESULTS: average-risk individuals). Without screening, an estimated 75 per 1,000 survivors would be diagnosed with CRC in their lifetime and 30 would die from CRC. Screening averted 47-73 cases and 23-29 CRC deaths per 1,000. Based on average-risk BBR benchmarks, the optimal strategies by modality were colonoscopy every 10 years starting at age 30 years, mtsDNA every 3 years starting at age 30 years, and FIT every 3 years starting at age 25 years (then annually as of age 45 years, as recommended for average-risk individuals). ICERs were $146,000 in US dollars (USD)/QALYG, $166,000 (USD)/QALYG, and $123,000 (USD)/QALYG, respectively. CONCLUSION: Early initiation of screening with colonoscopy or stool-based tests may substantially reduce CRC incidence and early mortality among survivors treated with abdominopelvic RT, with reasonable burden-to-benefit trade-offs, and be considered cost-effective. These findings can facilitate clinician-survivor discussions on CRC screening and inform guideline refinements.
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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 | 0.001 | 0.006 |
| 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) | 0.003 | 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".