High prevalence of adenomatous colorectal polyps in young cancer survivors treated with abdominal radiation therapy: results of a prospective trial
Bibliographic record
Abstract
OBJECTIVE: Cancer survivors treated with abdominal/pelvic radiation therapy (ART) have increased the risks of colorectal cancer (CRC), although evidence supporting early CRC screening for these patients is lacking. We sought to determine whether there is an elevated prevalence of adenomatous colorectal polyps in young survivors prior to the age when screening would be routinely recommended. DESIGN: We conducted a prospective study of early colonoscopic screening in cancer survivors aged 35-49 who had received ART ≥10 years previously. The planned sample size was based on prior studies reporting a prevalence of adenomatous polyps of approximately 20% among the average-risk population ≥50 years of age, in contrast to ≤10% among those average-risk people aged 40-50 years, for whom screening is not routinely recommended. RESULTS: Colonoscopy was performed in 54 survivors, at a median age of 45 years (range 36-49) and after median interval from radiation treatment of 19 years (10.6-43.5). Forty-nine polyps were detected in 24 patients, with 15 patients (27.8%; 95% CI 17.6% to 40.9%) having potentially precancerous polyps. Fifty-three per cent of polyps were within or at the edge of the prior ART fields. CONCLUSIONS: Young survivors treated with ART have a polyp prevalence comparable with the average-risk population aged ≥50 years and substantially higher than previously reported for the average-risk population aged 40-50 years. These findings lend support to the early initiation of screening in these survivors. CLINICAL TRIAL REGISTRATION NUMBER: NCT00982059; results.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".