Variant classification changes over time in the clinical molecular diagnostic laboratory setting
Bibliographic record
Abstract
BACKGROUND: Variant classification in the setting of germline genetic testing is necessary for patients and their families to receive proper care. Variants are classified as pathogenic (P), likely pathogenic (LP), uncertain significance (VUS), likely benign (LB) and benign (B) using the standards and guidelines recommended by the American College of Medical Genetics and the Association for Molecular Pathology, with modifications for specific genes. As the literature continues to rapidly expand, and evidence continues to accumulate, prior classifications can be updated accordingly. In this study, we aim to characterise variant reclassifications in Ontario. METHODS: DNA samples from patients seen at hereditary cancer clinics in Ontario from January 2012 to April 2022 were submitted for testing. Patients met provincial eligibility criteria for testing for hereditary cancer syndromes or polycystic kidney disease. Reclassification events were determined to be within their broader category of significance (B to LB or vice versa, or P to LP or vice versa) or outside of their broader category as significance (ie, significant reclassifications from B/LB or VUS or P/LP, from P/LP to VUS or B/LB, or from VUS to any other category). RESULTS: Of the 8075 unique variants included in this study, 23.7% (1912) of variants were reassessed, and 7.2% (578) of variants were reclassified. Of these, 351 (60.7%) variants were reclassified outside of their broader category of significance. Overall, the final classification was significantly different for 336 (58.1%) variants. Importantly, most reclassified variants were downgraded to a more benign classification (n=245; 72.9%). Of note, most reclassified VUS was downgraded to B/LB (n=233; 84.7%). CONCLUSIONS: The likelihood for reclassification of variants on reassessment is high. Most reclassified variants were downgraded to a more benign classification. Our findings highlight the importance of periodic variant reassessment to ensure timely and appropriate care for patients and their families.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".