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Meta-Analysis
. 2017 Sep 1;7(9):e016461.
doi: 10.1136/bmjopen-2017-016461.

Estimating the prevalence of heterozygous familial hypercholesterolaemia: a systematic review and meta-analysis

Affiliations
Meta-Analysis

Estimating the prevalence of heterozygous familial hypercholesterolaemia: a systematic review and meta-analysis

Leo E Akioyamen et al. BMJ Open. .

Abstract

Objectives: Heterozygous familial hypercholesterolaemia (FH) confers a significant risk for premature cardiovascular disease (CVD). However, the estimated prevalence of FH varies substantially among studies. We aimed to provide a summary estimate of FH prevalence in the general population and assess variations in frequency across different sociodemographic characteristics.

Setting, participants and outcome measures: We searched MEDLINE, EMBASE, Global Health, the Cochrane Library, PsycINFO and PubMed for peer-reviewed literature using validated strategies. Results were limited to studies published in English between January 1990 and January 2017. Studies were eligible if they determined FH prevalence using clinical criteria or DNA-based analyses. We determined a pooled point prevalence of FH in adults and children and assessed the variation of the pooled frequency by age, sex, geographical location, diagnostic method, study quality and year of publication. Estimates were pooled using random-effects meta-analysis. Differences by study-level characteristics were investigated through subgroups, meta-regression and sensitivity analyses.

Results: The pooled prevalence of FH from 19 studies including 2 458 456 unique individuals was 0.40% (95% CI 0.29% to 0.52%) which corresponds to a frequency of 1 in 250 individuals. FH prevalence was found to vary by age and geographical location but not by any other covariates. Results were consistent in sensitivity analyses.

Conclusions: Our systematic review suggests that FH is a common disorder, affecting 1 in 250 individuals. These findings underscore the need for early detection and management to decrease CVD risk.

Keywords: familial hypercholesterolemia; frequency; meta-analysis; prevalence; systematic review.

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Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Flow of studies included in systematic review of heterozygous familial hypercholesterolaemia prevalence. FH, familial hypercholesterolaemia.
Figure 2
Figure 2
Forest plot of overall pooled prevalence (%) of heterozygous familial hypercholesterolaemia. I2, between-study heterogeneity; LCL, lower confidence limit; POP, population; PREV, prevalence; UCL, upper confidence limit; WGHT, weight under the random-effects model. Note: prevalence estimates were derived using the double-arcsine method, back-transformed and expressed as percentages for ease of interpretation.
Figure 3
Figure 3
Age-stratified pooled familial hypercholesterolaemia (FH) prevalence estimates and 95% CIs. figure 3Error bars are representative of 95% CIs for each pooled estimate. Lower CIs are omitted; all cross 0%. I2, between-study heterogeneity; LCL, lower confidence limit; UCL, upper confidence limit.
Figure 4
Figure 4
(A) Forest plot of pooled prevalence (%) of heterozygous FH in the male population. (B) Forest plot of pooled prevalence (%) of FH in the female adult population. (C) Forest plot of pooled OR of male:female FH prevalence. FH, familial hypercholesterolaemia; I2, between-study heterogeneity; LCL, lower confidence limit; POP, population; PREV, prevalence; UCL, upper confidence limit; WGHT, weight under the random-effects model. Note: prevalence estimates were derived using the double-arcsine method, back-transformed and expressed as percentages for ease of interpretation.
Figure 5
Figure 5
Forest plot of overall pooled prevalence (%) of heterozygous familial hypercholesterolaemia stratified by population geography. I2, between-study heterogeneity; LCL, lower confidence limit; POP, population; PREV, prevalence; UCL, upper confidence limit; WGHT, weight under the random-effects model. Note: prevalence estimates were derived using the double-arcsine method, back-transformed and expressed as percentages for ease of interpretation.

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