Detection of familial hypercholesterolaemia: external validation of the FAMCAT clinical case-finding algorithm to identify patients in primary care

Weng, Stephen; Kai, Joe; Akyea, Ralph; Qureshi, Nadeem

Abstract

Background: The vast majority of individuals with familial hypercholesterolaemia (FH) in the general population remain unidentified worldwide. Recognising patients most at risk of having the condition, to enable targeted specialist assessment and treatment, could prevent major coronary morbidity and mortality. We evaluated the performance of a clinical case-finding algorithm for FH (FAMCAT), and compared it to currently recommended methods for FH detection in primary care.

Methods: The FAMCAT regression equations were applied to a retrospective cohort of 747,000 patients, aged over 16 years with cholesterol assessed, who were randomly selected from 1500 primary care practices across the United Kingdom contributing to the QResearch® database, from 1 January 1999 to 1 September 2017. There were 1,219 cases of FH identified during this period. We compared the performance of FAMCAT to other established clinical case-finding approaches recommended internationally (Simon-Broome, Dutch Lipid Clinic Score Network, MEDPED, and cholesterols levels over 99th centile). Discrimination was assessed by area under the receiver operating curve (AUROC). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were provided.

Findings: FAMCAT showed high levels of AUROC discrimination (0.832, 95% CI 0.820 – 0.845), performing significantly better than Simon-Broome criteria (0.694, 95% CI 0.681 – 0.703), Dutch Lipid Clinic Score (0.724, 95% CI 0.710 – 0.738), MEDPED (0.624, 95% CI 0.609 – 0.638), and screening cholesterols > 99th centile (0.581, 95% CI 0.570 – 0.591). Using a 1/500 probability threshold (prevalence of FH), FAMCAT achieved a sensitivity of 84% (1,028 predicted/1,219 observed cases) and specificity of 60% (443,949 predicted/746,993 observed non-cases), with a corresponding PPV of 0.34% and NPV of nearly 100%.

Interpretation: FAMCAT identifies FH with significantly greater accuracy than currently recommended approaches, and should be considered for clinical case-finding of patients at highest likelihood of having FH in primary care.

Citation

Weng, S., Kai, J., Akyea, R., & Qureshi, N. (2019). Detection of familial hypercholesterolaemia: external validation of the FAMCAT clinical case-finding algorithm to identify patients in primary care. Lancet Public Health, 4(5), e256-e264. https://doi.org/10.1016/S2468-2667%2819%2930061-1

• Journal Article Type: Article
• Acceptance Date: Mar 28, 2019
• Online Publication Date: May 1, 2019
• Publication Date: May 1, 2019
• Deposit Date: Apr 4, 2019
• Publicly Available Date: Apr 8, 2019
• Journal: The Lancet Public Health
• Electronic ISSN: 2468-2667
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 4
• Issue: 5
• Article Number: e256
• Pages: e256-e264
• DOI: https://doi.org/10.1016/S2468-2667%2819%2930061-1
• Public URL: https://nottingham-repository.worktribe.com/output/1739230
• Publisher URL: https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(19)30061-1/fulltext#articleInformation
• Additional Information: This article is maintained by: Elsevier; Article Title: Detection of familial hypercholesterolaemia: external validation of the FAMCAT clinical case-finding algorithm to identify patients in primary care; Journal Title: The Lancet Public Health; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/S2468-2667(19)30061-1; CrossRef DOI link to the associated document: https://doi.org/10.1016/S2468-2667(19)30055-6; Content Type: article; Copyright: © 2019 The Author(s). Published by Elsevier Ltd.
• Contract Date: Apr 8, 2019