TUMOUR PATHOLOGY PREDICTS MICROSATELLITE INSTABILITY IN A POPULATION-BASED SERIES OF COLORECTAL CANCER CASES
Bibliographic record
Abstract
Background: Lynch Syndrome is an autosomal dominant trait that accounts forapproximately 3% of all cases of colorectal cancer (CRC). It is caused by mutations in DNA mismatch repair (MMR) genes, most commonly MLH1 or MSH2. These MMR defects cause high levels of microsatellite instability (MSI-H) in the tumours. MSI testing of all CRCs to identify potential Lynch Syndrome cases is not practical, so the Bethesda Guidelines, which use clinical and pathological features, were created to identify those tumours most likely to be MSI-H^1. In 2007 Jenkins et. al. created MsPath, a tool based on the pathological features described in the rarely used 3^rd Bethesda criterion, to improve prediction of MSI-H tumours among CRC cases diagnosed before age 60 years^2. Methods: We collected a population-based cohort of 716 CRC cases diagnosed before age 75 years in Newfoundland. For each of these cases we collected family history, performed MSI analysis, and scored a number of pathological features for the purpose of evaluating the accuracy of the Bethesda Criteria and MsPath at predicting MSI-H tumours. Results: Our work validates the MsPath tool in the Newfoundland population for the same age group used to create the tool. We found it identified MSI-H cases with a sensitivity of 95% and specificity of 35% in our population of CRCcases diagnosed before age 60 years (n=290). We also tested this tool on our older population of CRCcases, diagnosed at ages 60 to 74 years (n=426). We found it to be at least as predictive in this population,with a sensitivity of 95% and a specificity of 42%. We then used our entire cohort (N=716) to compare MsPath with the other Bethesda criteria.Bethesda criteria 1, 2, 4 and 5 together predicted MSI-H cases with a sensitivity of 67% and a specificity of 51%. MsPath was better at identifying these cases, with a sensitivity of 95% and a specificity of 39%. Conclusions: We conclude that MsPath can be extended to include patients diagnosed with CRC before age 75 years. As well, we have found that MsPath is a better predictive tool than the Revised Bethesda Guidelines for identifying MSI-H cases within a population-based setting of colorectal cancer. References: 1. Umar, A. et. al. J Natl Cancer Inst 2004;96:261-8 2.Jenkins, M.A. et. al. Gastroenterology 2007;133:48-56
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".