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BACKGROUND: Familial Hypercholesterolaemia (FH), an inherited lipid disorder causing premature heart disease, is severely underdiagnosed. AIM: To evaluated the accuracy of a clinical tool (FAMCAT) for identifying FH in primary care. DESIGN AND SETTING: Retrospective cohort study of 1,030,183 patients, from the UK Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database, aged over 16 years. METHOD: The FAMCAT algorithm was compared to methods of FH detection recommended by national guidelines (Simon-Broome and Dutch Lipid Clinic Score diagnostic criteria and cholesterols levels >99th centile). Discrimination and calibration were assessed by area under the receiver operating curve (AUC) and comparing observed versus predicted cases. RESULTS: 1,707 patients had a diagnosis of FH. FAMCAT showed high levels of discrimination (AUC 0.844, 95% CI 0.834-0.854), performing significantly better than Simon-Broome criteria (AUC 0.730, 95% CI 0.719-0.741), Dutch Lipid Clinic Score (AUC 0.766, 95% CI 0.755-0.778), and screening cholesterols >99th centile (AUC 0.579, 95% CI 0.571-0.588). Inclusion of premature myocardial infarction and fitting cholesterol as a continuous variable improved the accuracy of FAMCAT (AUC 0.894, 95% CI, 0.885-0.903). CONCLUSION: Better performance of the FAMCAT algorithm, compared to other approaches for case-finding of FH in primary care, has been confirmed in a separate population cohort.

Original publication

DOI

10.3399/bjgpopen20X101114

Type

Journal article

Journal

BJGP Open

Publication Date

03/11/2020

Keywords

case-finding, familial hypercholesterolaemia, general practice