Validation of the BOADICEA model for epithelial tubo-ovarian cancer risk prediction in UK Biobank

Menée à partir de données de la "UK Biobank" portant sur 199 429 femmes d'origine européenne et sans antécédents de cancer, cette étude met en évidence la performance d'un modèle, basé sur des facteurs de risque, les antécédents familiaux, la présence de variants pathogènes au niveau de six gènes de suceptibilité et les résultats d'un score de risque polygénique, pour prédire le risque à 10 ans de cancer épithélial tubo-ovarien (733 cas)

British Journal of Cancer, sous presse, 2024, article en libre accès

Résumé en anglais

Background : The clinical validity of the multifactorial BOADICEA model for epithelial tubo-ovarian cancer (EOC) risk prediction has not been assessed in a large sample size or over a longer term.

Methods : We evaluated the model discrimination and calibration in the UK Biobank cohort comprising 199,429 women (733 incident EOCs) of European ancestry without previous cancer history. We predicted 10-year EOC risk incorporating data on questionnaire-based risk factors (QRFs), family history, a 36-SNP polygenic risk score and pathogenic variants (PV) in six EOC susceptibility genes (BRCA1, BRCA2, RAD51C, RAD51D, BRIP1 and PALB2).

Results : Discriminative ability was maximised under the multifactorial model that included all risk factors (AUC = 0.68, 95% CI: 0.66–0.70). This model was well calibrated in deciles of predicted risk with calibration slope=0.99 (95% CI: 0.98–1.01). Discriminative ability was similar in women younger or older than 60 years. The AUC was higher when analyses were restricted to PV carriers (0.76, 95% CI: 0.69–0.82). Using relative risk (RR) thresholds, the full model classified 97.7%, 1.7%, 0.4% and 0.2% women in the RR < 2.0, 2.0 ≤ RR < 2.9, 2.9 ≤ RR < 6.0 and RR ≥ 6.0 categories, respectively, identifying 9.1 of incident EOC among those with RR ≥ 2.0.

Discussion : BOADICEA, implemented in CanRisk (www.canrisk.org), provides valid 10-year EOC risks and can facilitate clinical decision-making in EOC risk management.