Tracking uncertainty in germline genetic testing for hereditary cancer syndromes: Sources, attributes, and resolution of variants of uncertain significance in over 1 million individuals.
Bibliographic record
Abstract
10513 Background: Genetic testing for hereditary cancer syndromes has diagnostic, prognostic and therapeutic implications; however, variant(s) of uncertain significance (VUS) are not clinically actionable. As such, VUS are a challenge to the entire medical community. Additionally, individuals from underrepresented race, ethnicity, and ancestry (REA) groups are disproportionately impacted by VUS. This study reports on the prevalence of VUS in patients referred for genetic testing for hereditary cancer syndromes and the results of reclassification. Methods: Patients were referred for diagnostic multigene panel testing for hereditary cancer from September 2014 to September 2022. Variants were classified as benign (B), likely benign (LB), VUS, likely pathogenic (LP), or pathogenic (P) using Sherloc, a validated system based on guidelines from ACMG/AMP. Both the number of unique VUS (uVUS) and the number of times they were observed in individuals (oVUS) were counted. All-time uVUS were separated as being reclassified and non-reclassified, and the relative contribution of evidence types used for reclassification was analyzed. Results: During this 8-year period, 1,122,444 unrelated individuals were tested for hereditary cancer with a mean number of 53 genes tested per individual. Results showed a mean of 0.45 oVUS per individual; 30.6% of individuals without a P/LP variant had at least 1 oVUS. The rate of oVUS normalized to the number of genes tested was highest in French Canadian and lowest in Ashkenazi Jewish individuals, as the mean number of genes sequenced to observe one VUS was 39.8 and 59.4, respectively. White individuals had a lower oVUS rate of 31.4% than Sephardic Jewish (53.8%), Asian (48.3%), Black (40.5%), Hispanic (37.6%), and additional underrepresented REA groups. In total, 7,542 (7.3%) of 103,767 uVUS were reclassified, affecting 88,877 individuals (7.9%); 5,864 (77.8%) of the reclassified uVUS were downgraded to B/LB, and 1,678 (22.2%) were upgraded to LP/P. Evidence from clinical observation contributed the most for upgrading uVUS (16.0-fold compared to non-reclassified uVUS), while evidence from experimental studies contributed the most to downgrading uVUS (23.9-fold). Conclusions: Experimental studies and clinical evidence were the most impactful types of evidence for reclassifications. This highlights the partnership among researchers, clinicians, and laboratories to resolve VUS. Further representation of diverse REA groups in genomic databases is needed to address the disparities in VUS rates, and additional research is needed into methods that could expedite the resolution of VUS so that patients can make more informed decisions.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".