Tracking uncertainty in germline genetic testing for hereditary cancer syndromes: Sources, attributes, and resolution of variants of uncertain significance in over 1 million individuals.
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».