Cancer Risks for Relatives of Patients With Serrated Polyposis
Bibliographic record
Abstract
OBJECTIVES: Serrated polyposis (hyperplastic polyposis) is characterized by multiple polyps with serrated architecture in the colorectum. Although patients with serrated polyposis are known to be at increased risk of colorectal cancer (CRC) and possibly extracolonic cancers, cancer risk for their relatives has not been widely explored. The aim of this study was to estimate the risks of CRC and extracolonic cancers for relatives of patients with serrated polyposis. METHODS: A cohort of the 1,639 first- and second-degree relatives of 100 index patients with serrated polyposis recruited regardless of a family history of polyps or cancer from genetic clinics in Australia, New Zealand, Canada, and the USA, were retrospectively analyzed to estimate the country-, age-, and sex-specific standardized incidence ratios (SIRs) for relatives compared with the general population. RESULTS: A total of 102 CRCs were observed in first- and second-relatives (SIR 2.25, 95% confidence interval (CI) 1.75-2.93; P<0.001), with 54 in first-degree relatives (SIR 5.16, 95% CI 3.70-7.30; P<0.001) and 48 in second-degree relatives (SIR 1.38, 95% CI 1.01-1.91; P=0.04). Six pancreatic cancers were observed in first-degree relatives (SIR 3.64, 95% CI 1.70-9.21; P=0.003). There was no statistical evidence of increased risk for cancer of the stomach, brain, breast, or prostate. CONCLUSIONS: Our finding that relatives of serrated polyposis patients are at significantly increased risk of colorectal and pancreatic cancer adds to the accumulating evidence that serrated polyposis has an inherited component.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".