New Case Detection by Cascade Testing in Familial Hypercholesterolemia

Author:

Lee Christopher1,Rivera-Valerio Miriannie1,Bangash Hana1,Prokop Larry1,Kullo Iftikhar J.1

Affiliation:

1. Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.

Abstract

Background: The prevalence of familial hypercholesterolemia is 1 in 250, but <10% of patients are diagnosed. Cascade testing enables early detection of cases through systematic family tracing. Establishment of familial hypercholesterolemia cascade testing programs in the US could be informed by approaches used elsewhere. Methods: We conducted a systematic review of published studies in the English language of cascade testing for familial hypercholesterolemia, which reported the number of index cases and number of relatives tested and specified methods of contacting relatives and testing modalities methods utilized. For each study, we calculated yield (proportion of relatives who test positive) and new cases per index case, to facilitate comparison. Results: We identified 10 studies from the literature that met inclusion criteria; the mean number of probands and relatives per study was 242 and 826, respectively. The average yield was 44.76% with a range of 30% to 60.5%, and the mean new cases per index case was 1.65 with a range of 0.22 to 8.0. New cases per index case tended to be greater in studies that used direct contact versus indirect contact (2.06 versus 0.86), tested beyond first-degree relatives versus only first-degree relatives (3.65 versus 0.80), used active sample collection versus collection at clinic (4.11 versus 1.06), and utilized genetic testing versus biochemical testing (2.47 versus 0.42). Conclusions: New case detection in familial hypercholesterolemia cascade testing programs tended to be higher with direct contact of relatives, testing beyond first-degree relatives, in-home–based sample collection, and genetic testing. These findings should be helpful for establishing cascade testing programs in the United States.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

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