Universal Lynch Syndrome Screening in Newly Diagnosed Colorectal Cancer: Impact of an Alberta-wide Screening Program
Bibliographic record
Abstract
Lynch Syndrome (LS) is the most common cause of inherited colorectal cancer (CRC) and is thought to be present in 2-5% of new CRC diagnoses. LS is caused by a germline mutation in one of the DNA Mismatch Repair (MMR) genes and can be diagnosed through germline genetic testing. Universal tumor screening in all new CRCs using Immunohistochemistry (IHC) to assess for loss of MMR-protein expression allows for identification of individuals at increased risk for underlying LS who would benefit from genetic testing. This thesis reports the results of one study performed with the aim of evaluating the early-phase impact of Alberta’s province-wide universal LS screening program for all new CRCs on rates of germline genetic testing for LS as well as key clinical outcomes and wait-times in Alberta’s LS screening and diagnostic pathway. Our retrospective review of quality assurance data showed an increase in the number of CRCs screened per month, increased proportion of women and people living outside urban centers being screened for LS, as well as an increased odds of being referred to medical genetics after program implementation. An absolute reduction in mean time from cancer diagnosis to all key clinical touchpoints was seen (not statistically significant). After implementation there was no significant difference in screen positive patients being seen by medical genetics or undergoing genetic testing which is suggestive of additional barriers not addressed by universal tumor screening alone. Together, these findings demonstrate a likely net positive impact from universal screening worthy of continued provincial funding but with a need for prospective data collection and monitoring to identify and address barriers encountered by patients who would benefit from medical genetics consultation, germline genetic testing, and enrollment in high-risk cancer screening.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".