Selection of individuals for genetic testing for familial hypercholesterolaemia: development and external validation of a prediction model for the presence of a mutation causing familial hypercholesterolaemia
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AIMS: Familial hypercholesterolaemia (FH) is an autosomal dominant disease that warrants early diagnosis to prevent premature cardiovascular disease (CVD). However, genetic testing to make a definite diagnosis is costly, and careful selection of eligible subjects is important. Unfortunately, accuracy of current diagnostic criteria is poor, especially in young individuals. We therefore developed and validated a model to predict the presence of an FH causing mutation in persons referred by general practitioners. METHODS AND RESULTS: All participants in the Dutch FH screening programme from 1994 to 2014 were included in the development cohort. The validation cohort consisted of consecutive patients, suspected for FH, attending the outpatient lipid clinic in Saguenay (Quebec) from 1993 to 2014. Cross-sectional data were available on medical history, lipid profile, and DNA analysis. Multivariable logistic regression analysis was used for model development. The primary outcome was the presence of a deleterious FH mutation. The development cohort comprised 26 167 FH patients and 37 939 unaffected relatives. Our final model included age; sex; levels of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides; history and age of CVD; use of statins; smoking; alcohol; and presence of hypertension. The area under the receiver operating characteristic curve (AUC) was 85.4% (95% CI: 85.0-85.9). The calibration slope was 1.02 (where 1.00 is optimal). In the validation cohort (1436 FH patients and 1767 unaffected persons), the AUC was 95.4% (95% CI: 94.7-96.1%) and the calibration slope 1.06. CONCLUSION: Our model showed good discrimination and calibration. We specifically expect our model to be of added value for young persons set against current diagnostic criteria, since LDL-C and age are now used as continuous predictors. The equation will be available as an online calculator to estimate the probability of the presence of an FH mutation in individual patients. This tool might aid physicians in the decision for referral of patients for molecular testing.
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The risk of atherosclerotic cardiovascular disease in familial hypercholesterolemia can be largely ameliorated through early identification and treatment with lipid-lowering therapies.
“Importantly, the risk of ASCVD can be largely ameliorated through early identification and treatment with lipid-lowering therapies.1,4–6”
From Finding missed cases of familial hypercholesterolemia in health systems using machine learning (2019) · cites this paper as [4]
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- Authors
- Besseling, J., Reitsma, J. B., Gaudet, D., Brisson, D., Kastelein, J. J. P., Hovingh, G. K., & Hutten, B. A.
- Affiliations
- Amsterdam UMC Location University of Amsterdam (NL)
- University Medical Center Utrecht (NL)
- Université de Montréal (CA)
- Corresponding author
- Besseling, Joost
- ORCID
- Venue
- European Heart Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-04-03
- Volume
- 38
- Issue
- 8
- Pages
- ehw135
- ISSN
- 0195-668X (ISSN-L)
- 1522-9645
- OpenAlex
- W2325583450
- Cited by
- 60
- References
- 39
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 4 · 2023: 7 · 2022: 4 · 2021: 10 · 2020: 7 · 2019: 5 · 2018: 5 · 2017: 11 · 2016: 4
- FWCI
- 9.24
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- European Heart Journal (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Utrecht University Repository (Utrecht University) (submittedVersion)
- Topics
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipid metabolism and disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- familial hypercholesterolemia, genetic testing, LDL cholesterol, cardiovascular risk, young adults, lipid profile, cardiovascular disease history, statin use, hypertension, smoking, alcohol, external validation, screening programs
- MeSH terms
- Adult, Cardiovascular Diseases, Cross-Sectional Studies, Female, Heterozygote, Humans, Hyperlipoproteinemia Type II, Lipoproteins, HDL, Lipoproteins, LDL, Male, Models, Genetic, Mutation, Prognosis, Registries, Age of Onset, Patient Selection, Hydroxymethylglutaryl-CoA Reductase Inhibitors
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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