Role of molecular diagnostic testing in familial adenomatous polyposis and hereditary nonpolyposis colorectal cancer families
Bibliographic record
Abstract
PURPOSE: Genetic tests are available for familial adenomatous polyposis and hereditary nonpolyposis colorectal cancer. The goal of this review was to develop an algorithm for application of molecular diagnostic techniques to the management of hereditary colorectal carcinoma and to familiarize the clinician with the vocabulary of molecular genetic testing for hereditary colorectal carcinoma. METHODS: Studies examining the clinical use of genetic testing for hereditary colorectal carcinoma syndromes are evaluated. Recent advances in molecular genetic technology are reviewed, and clinical management as practiced here and elsewhere is outlined. RESULTS: This review is a guide to the most reliable molecular diagnostic techniques. Three key questions are answered: who, when, and how to test. CONCLUSIONS: When integrated with existing testing protocols for colorectal carcinoma and when applied with appropriate caveats, particularly regarding interpretation of negative results, genetic testing can result in improved management of patients and families.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".