Recognition of Lynch Syndrome Amongst Newly Diagnosed Colorectal Cancers at St. Paul’s Hospital
Bibliographic record
Abstract
BACKGROUND: Lynch Syndrome (LS) is the most common cause of inherited colorectal cancer (CRC). In British Columbia, most centres still use clinical criteria (Amsterdam II, Revised Bethesda, or the BC Cancer Agency's criteria) to determine who should undergo further first-line testing in the form of microsatellite instability or immunohistochemistry staining. Given the limitations with this strategy, LS is thought to be underrecognized. OBJECTIVE: To investigate whether LS is truly underrecognized when compared to the reported prevalence. METHODS: A retrospective chart review of all CRC cases diagnosed at St. Paul's Hospital from 2010 to 2013 was conducted. RESULTS: 246 patients met inclusion criteria. 76% (83/109) with a family history of malignancy were unable to recall the specific malignancy or age of diagnosis. 18% (43/235) were only asked about a history of gastrointestinal related malignancy and 26% (65/246) met at least one of the three criteria but only 21% (13/63) received further investigation. Only 1.6% (4/246) had LS compared to the reported prevalence of 2-5% of all CRC cases. CONCLUSION: This data supports our hypothesis that LS is underrecognized. Issues at the patient, physician, and systems level need to be evaluated to determine where the limitations preventing appropriate testing are occurring.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".