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Enhanced identification of familial hypercholesterolemia using central laboratory algorithms.
Ibrahim, Shirin; Nurmohamed, Nick S; Nierman, Melchior C; de Goeij, Jim N; Zuurbier, Linda; van Rooij, Jeroen; Schonck, Willemijn A M; de Vries, Jard; Hovingh, G Kees; Reeskamp, Laurens F; Stroes, Erik S G.
Afiliação
  • Ibrahim S; Department of Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
  • Nurmohamed NS; Department of Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands; Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
  • Nierman MC; Department of Thrombosis and Anticoagulation, Atalmedial Medical Diagnostic Centers, Amsterdam, the Netherlands.
  • de Goeij JN; Department of Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
  • Zuurbier L; Department of Human Genetics, Amsterdam UMC, Amsterdam, the Netherlands.
  • van Rooij J; Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands.
  • Schonck WAM; Department of Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
  • de Vries J; Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands.
  • Hovingh GK; Department of Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
  • Reeskamp LF; Department of Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
  • Stroes ESG; Department of Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands. Electronic address: e.s.stroes@amsterdamumc.nl.
Atherosclerosis ; 393: 117548, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38643673
ABSTRACT
BACKGROUND AND

AIMS:

Familial hypercholesterolemia (FH) is a highly prevalent genetic disorder resulting in markedly elevated LDL cholesterol levels and premature coronary artery disease. FH underdiagnosis and undertreatment require novel detection methods. This study evaluated the effectiveness of using an LDL cholesterol cut-off ≥99.5th percentile (sex- and age-adjusted) to identify clinical and genetic FH, and investigated underutilization of genetic testing and undertreatment in FH patients.

METHODS:

Individuals with at least one prior LDL cholesterol level ≥99.5th percentile were selected from a laboratory database containing lipid profiles of 590,067 individuals. The study comprised three phases biochemical validation of hypercholesterolemia, clinical identification of FH, and genetic determination of FH.

RESULTS:

Of 5614 selected subjects, 2088 underwent lipid profile reassessment, of whom 1103 completed the questionnaire (mean age 64.2 ± 12.7 years, 48% male). In these 1103 subjects, mean LDL cholesterol was 4.0 ± 1.4 mmol/l and 722 (65%) received lipid-lowering therapy. FH clinical diagnostic criteria were met by 282 (26%) individuals, of whom 85% had not received guideline-recommended genetic testing and 97% failed to attain LDL cholesterol targets. Of 459 individuals consenting to genetic validation, 13% carried an FH-causing variant, which increased to 19% in clinically diagnosed FH patients.

CONCLUSIONS:

The identification of a substantial number of previously undiagnosed and un(der)treated clinical and genetic FH patients within a central laboratory database highlights the feasibility and clinical potential of this targeted screening strategy; both in identifying new FH patients and in improving treatment in this high-risk population.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Testes Genéticos / Hiperlipoproteinemia Tipo II / LDL-Colesterol Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Testes Genéticos / Hiperlipoproteinemia Tipo II / LDL-Colesterol Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2024 Tipo de documento: Article