A Canadian Provincial Screening Program for Lynch Syndrome
Bibliographic record
Abstract
INTRODUCTION: Manitoba implemented the first Canadian provincial program of reflex screening through mismatch repair immunohistochemistry (MMR-IHC) for all colorectal cancers diagnosed at age 70 years or younger in December 2017. We evaluated compliance to universal reflex testing and for referrals to Genetics for individuals with MMR-deficient tumors. METHODS: We searched the provincial pathology database with "adenocarcinoma" in the colorectal specimen pathology reports between March 2018 and December 2020. We cross-referenced with paper and electronic records in the Program of Genetics and Metabolism to determine whether patients with MMR-deficient tumors had been referred for Genetic assessment and what proportion of patients and first-degree relatives accepted an appointment and genetic testing. We performed logistic regression analysis to identify predictors of testing. RESULTS: We identified 3,146 colorectal adenocarcinoma specimens (biopsies and surgical resections) from 1,692 unique individuals (mean age 68.66 years, male 57%). Of those aged 70 years or younger (n = 936), 89.4% received MMR-IHC screening. Individual pathologists (categorized by the highest, average, and lowest screening rates) were the biggest predictors of MMR-IHC screening on multivariable analysis (highest vs lowest: odds ratio 17.5, 95% confidence interval 6.05-50.67). While only 53.4% (n = 31) of 58 screen-positive cases were referred by pathologists for genetic assessment, other clinicians referred an additional 22.4% (n = 13), resulting in 75.8% overall referral rate of screen-positive cases. Thirteen (1.4%) patients (1.1%, aged 70 years or younger) were confirmed to experience Lynch syndrome through germline testing, and 8 first-degree relatives (an average of 1.6 per patient) underwent cascade genetic testing. DISCUSSION: The first Canadian Lynch syndrome screening program has achieved high rates of reflex testing.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".