S0316 Implementation of a Simple Colon Cancer Risk Assessment Tool in a Gastroenterology Office Setting Improved Identification of Patients at Risk of Lynch Syndrome
Bibliographic record
Abstract
INTRODUCTION: Lynch syndrome (LS) is the most common cause of hereditary colorectal cancer (CRC), with a reported prevalence of 2%–5% of all CRC cases. Recent research from our institution indicates that LS is underrecognized using current screening practices. A 3 question CRC Risk Assessment Tool, identified 77% of individuals with known LS undergoing colonoscopy. We assessed if implementation of this validated questionnaire at a busy gastroenterology office would improve identification of patients at higher risk for LS. METHODS: Adult gastroenterology outpatients attending consultation with one of seven gastroenterologists were asked to complete the CRC Risk Assessment Tool prior to their consultation. Those who had previously been referred for genetic testing were excluded. The gastroenterologists whose patients were recruited were unaware of the study and were blinded to the survey results. Each subject was asked the following three questions: (1) Do you have a first-degree relative with CRC or LS-related cancer diagnosed before age 50? (2) Have you had CRC or polyps diagnosed before age 50? (3) Do you have ≥3 relatives with CRC? Answering yes to any question was considered a positive screen. Each patient’s consultation was reviewed and appropriate referral for genetic testing was documented. RESULTS: A total of 655 patients were screened using the CRC Risk Assessment Tool, with 33 (5.0%) screening positive for question “Do you have a first-degree relative with CRC or LS-related cancer diagnosed before age 50?”, 71 (10.8%) screening positive for, “Have you had CRC or polyps diagnosed before age 50?” and 17 (2.6%) screening positive for “Do you have ≥3 relatives with CRC?.” In total, 106 (15.9%) of individuals surveyed screened positive indicating higher risk for LS. Only one of these patients was referred for genetic testing. CONCLUSION: Utilization of the CRC Risk Assessment Tool as part of regular patient intake in a gastroenterology office was feasible and improved identification of patients at higher risk for LS. Future steps involve instituting an educational program and reassessing the use of our CRC Risk Assessment Tool to ensure improvement in patient care.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".