Predicting genetically defined familial hypercholesterolemia with the FAMCAT algorithm in an Australian tertiary clinic.

BACKGROUND: Familial hypercholesterolemia (FH) is a monogenic disorder associated with premature coronary artery disease. The Dutch Lipid Clinic Network (DLCN) and Familial Hypercholesterolemia Case Ascertainment Tool (FAMCAT) are tools used to identify individuals with possible FH. Although FAMCAT performs well in primary care, its accuracy for genetically confirmed FH in tertiary care settings remains unclear. This study assessed the performance of FAMCAT in an Australian tertiary lipid clinic. OBJECTIVE: This study assessed the performance of FAMCAT in identifying patients with genetically confirmed FH in an Australian tertiary lipid clinic. METHODS: This cross-sectional study included unrelated adult patients referred for FH genetic testing. FAMCAT and DLCN scores were calculated, and their discriminatory ability was evaluated using area under the receiver operating characteristic curve (AUROC) analysis. RESULTS: Of 885 patients, 267 (30%) had genetically confirmed heterozygous FH. In univariate regression analysis, FAMCAT and DLCN scores were significant predictors of an FH-causing variant with an odds ratio of 1.13 (95% CI 1.09-1.17; P < .001) and 1.49 (95% CI 1.41-1.58; P < .001), respectively. These associations remained significant after adjusting for smoking, hypertension, and obesity. The AUROC for FAMCAT (0.748; 95% CI, 0.712-0.784) was significantly lower than that of DLCN (0.816; 95% CI, 0.784-0.847; P < .01). Although FAMCAT and DLCN definite FH category had comparable sensitivity (67.0% vs 65.2%), FAMCAT had a lower specificity (73.3% vs 83.5%), positive predictive value (52.0% vs 63.0%), and Youden index (0.402 vs 0.487). CONCLUSIONS: The DLCN criteria performed better in identifying FH genetic variants in this Australian lipid clinic. The FAMCAT algorithm showed good discriminatory accuracy and could help prioritize patients referred for specialist review and/or genetic testing. Improved family history documentation may further enhance the diagnostic accuracy of both tools.