Comparison of Prediction Models for XXXX Among Individuals With @entity14 .

@entity1 @entity6756 @entity4309 @entity5 @entity4311 @entity5527 @entity14 @entity4638
BACKGROUND: Recent guidelines recommend the @entity4309 prediction models MMRPredict, MMRPro, and PREMM1,2,6 for the identification of MMR gene mutation carriers. We compared the predictive performance and clinical usefulness of these prediction models to identify mutation carriers. METHODS: Pedigree data from @entity14 @entity1 in 11 North American, European, and Australian cohorts (6 clinic- and 5 population-based sites) were used to calculate predicted probabilities of pathogenic @entity6756 , @entity4311 , or @entity4638 gene mutations by each model and gene-specific predictions by MMRPro and PREMM1,2,6. We examined discrimination with area under the receiver operating characteristic curve (AUC), calibration with observed to expected (O/E) ratio, and clinical usefulness using decision curve analysis to select @entity1 for further evaluation. All statistical tests were two-sided. RESULTS: Mutations were detected in 539 of 2304 (23%) individuals from the clinic-based cohorts (237 @entity6756 , 251 @entity4311 , 51 @entity4638 ) and 150 of 3451 (4.4%) individuals from the population-based cohorts (47 @entity6756 , 71 @entity4311 , 32 @entity4638 ). Discrimination was similar for clinic- and population-based cohorts: AUCs of 0.76 vs 0.77 for MMRPredict, 0.82 vs 0.85 for MMRPro, and 0.85 vs 0.88 for PREMM1,2,6. For clinic- and population-based cohorts, O/E deviated from 1 for MMRPredict (0.38 and 0.31, respectively) and MMRPro (0.62 and 0.36) but were more satisfactory for PREMM1,2,6 (1.0 and 0.70). MMRPro or PREMM1,2,6 predictions were clinically useful at thresholds of 5% or greater and in particular at greater than 15%. CONCLUSIONS: MMRPro and PREMM1,2,6 can well be used to select @entity14 @entity1 from genetics clinics or population-based settings for @entity5 and/or germline testing at a 5% or higher risk. If no @entity5527 is detected and risk exceeds 15%, we suggest considering additional genetic etiologies for the cause of @entity5 in the family.
