Literature DB >> 27478447

Prevalence of familial hypercholesterolemia: a meta-analysis of six large, observational, population-based studies in Poland.

Andrzej Pajak1, Krystyna Szafraniec1, Maciej Polak1, Wojciech Drygas2, Walerian Piotrowski3, Tomasz Zdrojewski4, Piotr Jankowski5.   

Abstract

INTRODUCTION: Familial hypercholesterolemia (FH) is a severely underdiagnosed and undertreated genetic disorder. Little is known about regional variation in the prevalence of FH, and information for Central and Eastern Europe (CEE) is scarce. This paper assesses the prevalence of FH and related cardiovascular disease (CVD) risk factors in Poland.
MATERIAL AND METHODS: We performed a meta-analysis of six population-based studies in Poland. The FH was assessed using the Dutch Lipids Clinics Network (DLCN) criteria. The categories "definite" (> 8 points) and "probable" (6-8 points) were combined into "potential FH". Combined estimates of proportions across studies were pooled by meta-analysis with a random effects model.
RESULTS: A total of 37,889 persons aged 20-79 years were included in the analysis. The distribution of DLCN scores was skewed, and there were only 7 cases of definite FH. Prevalence of potential FH was 404/100,000 people (95% CI = 277-531/100,000). Familial hypercholesterolemia was more prevalent in women than in men, and the prevalence was the highest in the age group 45-54 years in men and 55-64 years in women. After adjustment for age and sex, compared to participants with normal cholesterol, persons with potential FH had twice the prevalence of hypertension (p < 0.01); smoking was more prevalent by about 80% (p < 0.01) and hypertriglyceridemia was nine times more frequent (p < 0.001). There was no difference in the prevalence of low high-density lipoprotein (HDL)-cholesterol or diabetes.
CONCLUSIONS: We believe that our study might facilitate the planning of a strategy to manage the disease at a population level, i.e. to develop a national strategy for the detection, diagnosis, and treatment of FH.

Entities:  

Keywords:  Dutch Lipids Clinics Network criteria; epidemiology; familial hypercholesterolemia; prevalence; risk factors

Year:  2016        PMID: 27478447      PMCID: PMC4947614          DOI: 10.5114/aoms.2016.59700

Source DB:  PubMed          Journal:  Arch Med Sci        ISSN: 1734-1922            Impact factor:   3.318


Introduction

Familial hypercholesterolemia (FH) is an autosomal dominant condition characterized by the life-course elevated blood low-density lipoprotein (LDL)-cholesterol concentration. In most cases, mutations of the gene for the LDL receptor (LDLR) or for apoprotein B (ApoB) or for proprotein convertase subtilisin/kexin type 9 (PCSK9) are found, but other forms of genetic mutations can also exist as very rare mutations of the LDLR adaptor protein 1 pathway. A vast majority of people with FH are heterozygotes. Heterozygous mutations of LDLR are present in about 90% of FH cases, while ApoB and PCSK9 were found in 5% and 1%, respectively [1-3]. Familial hypercholesterolemia has been well recognized for over 50 years, but it has gained attention recently for several important reasons. First, it is related to early atherosclerosis and premature coronary heart disease (CHD) and people with heterozygous FH are automatically considered as high-risk patients [4, 5]. Second, in many countries, the condition remains severely underdiagnosed and undertreated. Out of 22 countries, in more than half the estimates of the proportion of individuals diagnosed with FH were not higher than 1% of all cases, and only in five countries did the proportion exceed 5%, reaching the absolutely exceptional maximum of 71% in the Netherlands [3]. Only about half of FH patients were receiving appropriate therapy [4, 6]. Furthermore, FH patients were more likely to smoke and to have a high concentration of blood triglycerides and lower chance of having blood pressure within the recommended limits [6]. Statins are considered to be the first-line therapy for patients with FH [7-9], but low-potency statins or moderate doses of higher potency statins are not effective enough. In consequence, higher doses of high-potency statins are often needed to reach the goal of lowering LDL-C levels by 50% at least. Combined treatment with ezetimibe, ER niacin, bile acid binding agents, or anti-PCSK9 antibodies is also postulated [10-12]. The problem of statin intolerance is of particular importance as it affects 10–15% of patients treated with statins in general, with some complications having been reported more with the use of synthetic, potent, and more lipophilic statins [13]. All this suggests that FH requires a specific detection and treatment strategy that is firmly based on epidemiological evidence. It used to be generally believed that homozygous FH occurs in about 1/100,000 people, and heterozygous FH in about 1/500. However, these numbers were questioned because they were derived mainly from old clinical data. More recent studies indicated that the prevalence may reach 1/200 [3]. Data on prevalence of FH are not available for most countries because there is a lack of national registers or screening strategies in action. Furthermore, uniform criteria for the diagnosis of FH are not agreed, and there are three sets of criteria at least in broader use depending on the region of the world [2]. Genetic testing would be particularly beneficial to confirm the diagnosis in every individual case, but genetic screening was not found to be a cost-effective tool [14, 15]. The spectrum of FH mutations in Europe varies by country [2]. It is likely that there is also regional variation in the prevalence of FH in general. Information for Eastern Europe is scarce. Even the flagship report on FH of the European Atherosclerosis Society does not provide an estimate for diagnosed FH for a single Central or East European (CEE) country [3]. The findings in patients after hospitalization due to CHD indicate that the prevalence of FH seems to be high in CEE countries including Poland, in which 11.4% of patients were found to have definite or probable FH [6]. In Poland, several large population-based studies have been conducted, but the problem of FH was not addressed in any of them, as each of these studies had too low statistical power to deliver a more precise estimate. The goal of this study was to assess the prevalence of FH and related cardiovascular disease (CVD) risk factors by a meta-analysis of the results of six large, population-based, observational studies carried out in Poland, using available data on phenotype of FH.

Material and methods

We used data from six population studies, carried out in Poland in well-defined populations, in which at least 2,000 participants were examined. Detailed descriptions of the methods used in particular studies have been published elsewhere [16-23]. The list of populations studied and the information on recruitment and participation are presented in Table I.
Table I

Description of the study populations, selection, and participation rates of the study samples

Study nameStudy populationSamplingYears of observationTotal examinedParticipation rate (%)Included in meta-analysis
N%Age% men
POL-MONICA KrakowResidents of Tarnobrzeg Voivodship (province)Random sampling after stratification by sex and 10-year age groups1983–19841987–19881992–19935362817374515996.235–6446.5
POL-MONICA WarszawaResidents of two districts in Warsaw, capital cityRandom sampling after stratification by sex and 10-year age groups1984198819935618747074538595.935–6449.2
WOBASZResidents of PolandThree-stage sampling2003–200414769771401194.920–7447.0
Pilot HAPIEEResidents of Krakow townRandom sampling after stratification by sex and 5-year age groups2001–2002231065204388.445–6449.8
HAPIEEResidents of Krakow townRandom sampling after stratification by sex and 5-year age groups2003–2005929661912898.245–7048.3
NATPOL 2011Residents of PolandThree-stage sampling2011241366216389.620–7448.2
Description of the study populations, selection, and participation rates of the study samples For the present analysis, FH was assessed using the Dutch Lipids Clinics Network (DLCN) criteria for diagnosis of heterozygous FH in adults [3, 24]. Participants were classified as follows: “definite FH” if they scored > 8 points, “probable FH” if they scored 6–8 points, and “possible FH” if they scored 3–5 points. In addition, categories “definite FH” and “probable FH” were combined into “potential FH.” The category “normal blood cholesterol” was defined as having total cholesterol (TC) < 5 mmol/l and LDL-C < 3 mmol/l and not being on blood lipid-lowering treatment. In all studies, data on tendon xanthomas and arcus cornealis in participants or their families as well as data on first-degree relatives and children with LDL-C > 95th percentile by age and gender were not available. Also, no molecular genetic testing was available, so the final classification was based on phenotype characteristics, i.e. blood LDL-cholesterol and family or personal history of CHD and other acute atherosclerosis manifestations. The methods of blood processing and lipid determination are presented in Table II. In all studies, the information on family and personal history was collected by interview according to the questionnaire. All the available and relevant information on personal and family history of early CHD, stroke, and peripheral arterial disease (PAR) was used. Table III presents the information obtained to be used in the DLCN classification of FH.
Table II

Methods of blood lipid determination

Study nameMaterialTCHDL-CTGLDL-C
POL-MONICA KrakowPlasma (frozen)Manual, direct (Liebermann-Burchard procedure)Manual, direct (Liebermann-Burchard procedure), after precipitation with MnCL2 and heparinManual, enzymaticCalculated (Friedewald's formula)
POL-MONICA WarszawaPlasma (frozen)Manual, direct (Liebermann-Burchard procedure)Manual, direct (Liebermann-Burchard procedure) after precipitation with MnCL2 and heparinManual, enzymaticCalculated (Friedewald's formula)
WOBASZSerum (frozen)Enzymatic-colorimetric test (CHOD/PAP) with cholesterol esterase, cholesterol oxidase, and 4-aminoantipyrine (Roche kit); INTEGA 400 automatic analyzerMonochromatic colorimetric test with cholesterol esterase and cholesterol oxidase modified PEG after precipitation with MnCL2 and heparin (Roche kit); INTEGA 400 automatic analyzerEnzymatic-colorimetric (GPO/PAD) with glycerol phosphate oxidase and 4-aminoantipyrine (Roche kit); INTEGA 400 automatic analyzerCalculated (Friedewald's formula); if TG > 400 mg/dl monochromatic colorimetric test
Pilot HAPIEEPlasmaOxidation method with the MP3 Boehringer Mannheim chemical reagent kit in the Technicon RA-I000 automatic analyzerOxidation method with the MP3 Boehringer Mannheim chemical reagent kit in the Technicon RA-I000 automatic analyzer after precipitation with MnCL2 and heparinOxidation method with TG 30 Cormay chemical reagent kitCalculated (Friedewald's formula)
HAPIEEPlasmaOxidation method with the MP3 Boehringer Mannheim chemical reagent kit in the Technicon RA-I000 automatic analyzerOxidation method with the MP3 Boehringer Mannheim chemical reagent kit in the Technicon RA-I000 automatic analyzer after precipitation with MnCL2 and heparinOxidation method with TG 30 Cormay chemical reagent kitCalculated (Friedewald's formula)
NATPOL 2011Fasting serum (frozen)Enzymatic/cholesterol esterase and cholesterol oxidases; Architect c8000 chemistry analyzer, Abbott LaboratoriesDirect method – Accelerator Selective Detergent (ASD) with accelerated non-HDL-C oxidation and HDL-C dissolving; Architect c8000 chemistry analyzer, Abbott LaboratoriesEnzymatic/glycerol kinase and glycerol phosphate oxidase; Architect c8000 chemistry analyzer, Abbott LaboratoriesCalculated (Friedewald's formula)
Table III

Information on family and personal history of early coronary heart disease (CHD), cerebrovascular disease, and peripheral artery disease (PAR)

Study nameFamily history of early CHDPersonal history of early CHD, cerebrovascular disease, and PAR
MICHDAngina pectorisCABG or PCIPARCerebrovascular disease
POL-MONICA KrakowHistory of heart disease or death due to HA in parents[] or death due to HA (MI or acute IHD) or CHD in parents, siblings, or children below age 60 yearsHistory of chest pain followed by medical diagnosis of HA, i.e. MI, CHD, acute or chronic coronary insufficiency[]Positive rose angina questionnaire[]Not availablePositive history of IC (standard questionnaire)[]History of brain stroke, brain hemorrhage or brain ischemia[]
POL-MONICA Warszawa
WOBASZDeath from HA or history of MI or brain stroke in parents[]History of hospitalization due to MI or acute CHD or medical diagnosis of past MI[]History of hospitalization due to chronic CHD or heart insufficiency[]Positive rose angina questionnaire[]History of hospitalization due to PCI or CABG[]History of medical diagnosis or PAR[]History of hospitalization due to brain stroke[]
Pilot HAPIEEHistory of MI, AP, or IHD in parents aged below 60 yearsHistory of medical diagnosis of MI[]History of medical diagnosis of AP or IHD[]Not availableNot availableHistory of medical diagnosis of brain stroke[]
HAPIEEHistory of MI, AP or IHD in parents aged below 60 yearsHistory of medical diagnosis of MI[] or incident MI[]Not availablePositive rose angina questionnaire[] or history of medical diagnosis of AP[]5 years incidenceHistory of medical diagnosis of brain stroke[] or history of brain stroke[]
NATPOL 2011History of CHD, AP, MI, or brain stroke in parents or siblings aged below 65 years in women/55 years in menHistory of medical diagnosis of MI[]History of medical diagnosis of CHD[]Positive Rose angina questionnaire[]History of PCI or CABG[]History of PAR[]History of medical diagnosis of brain stroke (brain hemorrhage, brain ischemia)[]

In men aged below 55 years and in women aged below 60 years at the date of examination

at age below 55 years in men and 60 years in women

AP – angina pectoris, HA – heart attack, MI – myocardial infarction, IHD – ischemic heart disease, PCI – percutaneous intervention, CABG – coronary artery bypass grafting, IC – intermittent claudication.

Methods of blood lipid determination Information on family and personal history of early coronary heart disease (CHD), cerebrovascular disease, and peripheral artery disease (PAR) In men aged below 55 years and in women aged below 60 years at the date of examination at age below 55 years in men and 60 years in women AP – angina pectoris, HA – heart attack, MI – myocardial infarction, IHD – ischemic heart disease, PCI – percutaneous intervention, CABG – coronary artery bypass grafting, IC – intermittent claudication.

Statistical analysis

In the first stage, calculations in each of the studies were conducted separately. Proportions in persons with FH and in persons with normal blood cholesterol were standardized directly to the sex-specific age distribution of the Polish population at the end of 2013. Then, combined estimates of proportions across studies were pooled by meta-analysis technique. In the presence of heterogeneity within and between studies, random effects methodology was chosen to obtain pooled prevalence [25]. The prevalence of FH by sex and age strata was obtained by much the same procedure except for the two extreme age groups (20–34 years, 65 years and over), in which fixed effect meta-analysis was applied. A similar two-step approach was performed to determine the association between FH and CVD risk factors. First, a set of multiple regressions was carried out with risk factors as dependent variables and the FH vs. healthy group as the independent variable, adjusted for age and sex. The second step was to implement random effects model meta-analysis to calculate the combined measure of association across the studies. The statistical calculations were performed with IBM SPSS Statistics 22 for Windows except the meta-analysis procedure. The R Metafor package [26] was used to pool estimates across the studies p < 0.05 was considered statistically significant.

Results

Out of 39,768 participants examined in six studies, 37,889 individuals (47.8% men) were included in the present meta-analysis. About 1,885 (4.7%) participants were excluded, mainly because of missing LDL-C (1,343 persons) or the age being outside the range specific for each study at the date of examination (542 persons). The detailed recruitment and participation numbers by study are given in Table I. Severe hypercholesterolemia was not frequently found in the pooled sample included in the analysis. Very high LDL-cholesterol (≥ 6.5 mmol/l) was found only in 4.34‰ (95% CI: 3.19–5.48‰) and LDL-C ≥ 5 mmol/l was found in 5.79% (95% CI: 4.52–7.05%) of all participants. The distribution of the DLCN scores was skewed, and about half of all participants had a DLCN score of zero (Figure 1). In all 37,889 individuals studied, there were only 7 cases of DLCN score > 8 points. Potential FH, i.e. definite and probable FH combined (score ≥ 6 points), was more prevalent. The average prevalence was 404/100,000 people (95% CI: 277–531/100,000). However, the estimate of the average prevalence varied by study, with the minimum of 231/100,000 and maximum of 548/100,000 (Table IV).
Figure 1

Distribution of Dutch Lipid Consensus Network (DLCN) score

Table IV

Prevalence of potential (definite and probable combined) and possible familial hypercholesterolemia (FH) according to the Dutch Lipids Clinics Network (DLCN) criteria

Study namePotential FHPossible FH
95% CI%95% CI
POL-MONICA Krakow4.462.64–6.2812.111.2–13.0
POL-MONICA Warszawa5.013.13–6.9013.512.6–14.5
WOBASZ2.461.63–3.288.17.6–8.5
Pilot HAPIEE5.382.21–8.5612.911.4–14.3
HAPIEE5.483.96–6.9912.211.5–12.9
NATPOL 20112.310.29–4.345.94.9–6.9
Total4.042.77–5.3110.48.9–12.7
Distribution of Dutch Lipid Consensus Network (DLCN) score Prevalence of potential (definite and probable combined) and possible familial hypercholesterolemia (FH) according to the Dutch Lipids Clinics Network (DLCN) criteria In Table V, the prevalence of potential and possible FH is presented by sex and by age group. Familial hypercholesterolemia was more prevalent in women than in men, and the prevalence was the highest in the age group 45–54 years in men and 55–64 years in women. At age 65 years and older in men, the prevalence of FH was almost three times lower than the peak, and at age 65 years and older in women it was twice as low as the peak.
Table V

Percentage of potential (definite and probable combined) and possible familial hypercholesterolemia (FH) by sex and age group

Age groupMenWomenTotal
Potential FHPossible FHPotential FHPossible FHPotential FHPossible FH
%95% CI%95% CI%95% CI%95% CI%95% CI%95% CI
20–3401.740.93–2.5501.340.60–2.1001.611.24–1.96
35–440.100.0001–0.216.245.33–7.150.240.0001–0.506.172.66–9.680.180.08–0.296.133.84–8.41
45–540.330.18–0.4811.729.60–13.840.710.51–0.9213.5910.40–16.780.540.41–0.6712.6510.10–15.20
55–640.190.08–0.318.426.69–10.160.770.54–1.0016.5514.51–18.580.490.36–0.6312.5410.80–14.27
≥ 650.090.0001–0.247.251.35–13.110.370.10–0.6411.768.75–14.780.250.09–0.4110.107.11–13.10
Percentage of potential (definite and probable combined) and possible familial hypercholesterolemia (FH) by sex and age group In Table VI, the characteristics of participants with potential and possible FH are compared with persons with normal blood cholesterol, i.e. TC < 5 mmol/l and LDL-C < 3 mmol/l. Persons with FH were older and included a higher proportion of women. By definition, positive history of CHD and other acute manifestations of atherosclerosis were more frequent in participants with FH. Still, about 10% of participants with normal blood cholesterol had a history of stroke or acute or chronic CHD.
Table VI

Descriptive statistics for participants with potential (definite and probable combined) and possible familial hypercholesterolemia (FH) according to the Dutch Lipids Clinics Network (DLCN) criteria and for participants with normal blood cholesterol (TC < 5 mmol/l and LDL-C < 3 mmol/l)

ParameterPotential FHPossible FHNormal blood lipids
Mean or%95% CIMean or%95% CIMean or%95% CI
Mean age [years]53.852.8–54.853.451.7–55.146.239.7–52.7
Men (%)27.320.3–34.439.636.3–43.049.346.1–52.5
Mean BMI [kg/m2]27.827.0–28.528.128.0–28.326.125.2–27.1
Current smokers (%)41.333.5–49.134.528.2–40.936.031.1–40.9
Diabetes (%)1.8< 0.1–3.98.14.7–11.65.61.7–9.5
Hypertension (%)68.660.9–76.362.961.3–64.441.130.4–51.9
History of CVD (%)70.156.9–83.248.939.3–58.512.17.4–16.8
History of MI (%)32.115.0–49.216.79.9–23.43.21.7–4.7
History of CABG or PCI (%)6.5< 0.1–15.43.21.8–4.70.60.1–1.0
History of AP (%)49.329.3–69.335.023.6–46.48.64.6–12.5
History of brain stroke (%)3.2< 0.1–6.62.92.3–3.41.30.9–1.7
History of PAR (%)2.5< 0.1–5.84.52.3 –6.71.20.7–1.6
CVD and diabetes (%)1.8< 0.1–4.04.92.8–7.01.50.5–2.5
Lipid-lowering treatment (%)14.13.6–24.616.98.6–25.2
Mean TC [mmol/l]8.78.2–9.26.86.6–7.04.34.3–4.4
Mean HDL-C [mmol/l]1.41.4–1.51.41.4–1.41.41.4–1.49
Mean LDL-C [mmol/l]6.46.0–6.94.64.4–4.82.42.3–2.4
TG (median, min–max) [mmol/l]1.90.4–4.41.60.3–4.71.00.2–4.5

BMI – body mass index, CVD – cardiovascular disease, AP – angina pectoris, HA – heart attack, MI – myocardial infarction, PCI – percutaneous intervention, CABG – coronary artery bypass grafting, PAR – peripheral artery disease, TC – total cholesterol, HDL-C – high-density lipoprotein cholesterol, LDL – low-density lipoprotein cholesterol, TG – triglycerides.

Descriptive statistics for participants with potential (definite and probable combined) and possible familial hypercholesterolemia (FH) according to the Dutch Lipids Clinics Network (DLCN) criteria and for participants with normal blood cholesterol (TC < 5 mmol/l and LDL-C < 3 mmol/l) BMI – body mass index, CVD – cardiovascular disease, AP – angina pectoris, HA – heart attack, MI – myocardial infarction, PCI – percutaneous intervention, CABG – coronary artery bypass grafting, PAR – peripheral artery disease, TC – total cholesterol, HDL-C – high-density lipoprotein cholesterol, LDL – low-density lipoprotein cholesterol, TGtriglycerides. Participants with potential and with possible FH had higher exposure to some other risk factors. After adjustment for age and sex, compared to participants with normal cholesterol, persons with potential FH had twice as high prevalence of hypertension; smoking was more prevalent by about 80% and hypertriglyceridemia nine times more frequent. The prevalence of these risk factors was also higher in participants with possible FH; in particular, the prevalence of hypertriglyceridemia was four times higher compared to participants with normal blood cholesterol. Also, in participants with possible FH, higher prevalence of obesity was found. The prevalence of low HDL-cholesterol and diabetes was similar in participants with FH and in participants with normal blood cholesterol (Table VII).
Table VII

Relation between familial hypercholesterolemia (FH) and prevalence of other cardiovascular disease (CVD) risk factors (reference group = participants with TC < 5 mmol/l and LDL < 3 mmol/l and not on blood lipid lowering treatment)

ParameterPotential FHPossible FH
OR*95% CIP-valueOR*95% CIP-value
BMI ≥ 30 kg/m21.160.80–1.680.441.251.10–1.410.0006
Smoking1.751.23–2.480.0021.271.16–1.39< 0.0001
Diabetes2.260.85–6.000.101.170.91–1.500.21
Hypertension2.021.95–3.430.0091.761.57–1.97< 0.0001
Low HDL-C1.660.84–3.270.141.311.08–1.600.006
TG > 1.7 mmol/l9.056.10–13.44< 0.00014.373.71–5.14< 0.0001

BMI – body mass index, TC – total cholesterol, HDL-C – high-density lipoprotein cholesterol, LDL – low-density lipoprotein cholesterol, TG – triglycerides

Adjusted for age and sex.

Relation between familial hypercholesterolemia (FH) and prevalence of other cardiovascular disease (CVD) risk factors (reference group = participants with TC < 5 mmol/l and LDL < 3 mmol/l and not on blood lipid lowering treatment) BMI – body mass index, TC – total cholesterol, HDL-C – high-density lipoprotein cholesterol, LDL – low-density lipoprotein cholesterol, TGtriglycerides Adjusted for age and sex.

Discussion

We found that the prevalence of FH in Poland was between 277 and 531/100,000 people. The average estimate was 404/100,000, which equates to approximately 1/250 people. To our best knowledge, this is the first estimate of the prevalence of FH in Poland, which is based on the results of larger studies carried out in well-defined populations. Furthermore, the studies included in the present meta-analysis used the standardized methods of observations, and in some cases, the methods were standardized across these studies to obtain comparable results. For example, the POL-MONICA Krakow and Warsaw studies used the same questionnaires and blood collection procedures, and laboratory procedures were subjected to the same external quality control programs carried out by the CDC in Atlanta (USA) and by the MONICA Project Lipid Reference Center [16-18]. The WOBASZ Study used questionnaires largely based on POL-MONICA experiences, and biochemical analyses were carried out in the same laboratory as in POL-MONICA Warsaw. The methods in HAPIEE Krakow and the Pilot HAPIEE study were the same, and biochemical analyses were done in a laboratory that participated in the POL-MONICA Krakow study. Also, the strength of the analysis is that we were able to include data from two studies in which samples studied were selected from the total Polish population (WOBASZ and NATPOL 2011). There are, however, certain limitations in the interpretation of the results. The first is that none of the studies included in the meta-analysis was designed to assess FH according to the DLCN or any other standard set of diagnostic criteria. The information on phenotype and family history in particular varied between the studies. This could bias the final results, resulting in decreased numbers of people classified with definite or probable FH. The samples studied differed in age. Including the age group below 35 years could result in a decrease in the number of detected cases, as in heterozygous FH the onset of CHD frequently appears after the age of 35 years. On the other hand, in the older age group, the proportion of persons with FH was smaller because of lower life expectancy and higher frequency of the use of blood lipid-lowering agents. Indeed, in studies which involved samples with a broader age span (WOBASZ and NATPOL 2011), the rates of FH were lower. In participants aged 60–79 years (NATPOL 2011 study), the proportion of people taking statins was three times higher than the average for the total sample [22]. Blood lipid-lowering treatment could also lower the rates of FH in general. This would not be a problem of the early studies as treatment for hypercholesterolemia was infrequent, even marginal. The advantage of using data from the older studies might be that the bias due to the lipid-lowering treatment would be smaller than in more current observations. Indeed, in the later studies, the proportions of treated people were higher than in the old studies, but treatment of hypercholesterolemia was still not a standard practice. In the WOBASZ study (a representative sample for Poland), only 12% of people with hypercholesterolemia received treatment, and out of them, the treatment goals were reached only in every fifth person [19]. In the most recent study (NATPOL 2011), the proportion was similar [22]. It is likely that the effect of blood lipid-lowering treatment on our results was rather small. In the Finnish population study, mutation carriers who were treated with lipid-lowering medication had similar LDL-C to carriers who were not treated [27]. Also, lack of information on genetic mutations might be of smaller importance, as in the untreated, predominantly middle-age population, cases of FH with normal blood LDL-C or only slightly over the normal values should be very rare. Like in the other studies, there were differences in FH prevalence according to age [4, 6, 28, 29], which could be explained by the impact of increasing age and weight on LDL-C when using DLCN criteria. Higher prevalence in women was also found in some studies [4, 6, 30] but not in all [28-30]. Besides the effects of age and weight, these observations can also be explained by the differences in life expectancy between men and women. Familial hypercholesterolemia was found to be related to higher exposure to other CVD risk factors. Our study design does not allow for conclusions on causality, but these results call for intensifying the intervention in clinical practice. Direct comparisons between our findings and the results of other studies are difficult due to the differences in the design and methods used. Most evidence on the prevalence of FH is based on data from registers whose coverage is difficult to control [31]. In a few studies, the studied samples were representative of a larger population, but they were rarely large enough to provide reliable estimates of the prevalence. Our estimate is slightly lower compared to the results of the well-designed and frequently cited Danish study and close to the estimate of the European Atherosclerosis Society [3, 4]. Also, our results are close to the results obtained using similar methods from the US NHANES 2001–2012 datasets (nearly 60,000 persons) and similar to results of the studies from Australia and China (18,000 and 10,000 persons respectively) [28-30]. Our estimate of the prevalence is twice as high compared to the Finnish study (over 28,000 persons), which was based on finding genetic mutations which are present in about 70% of all FH cases in Finland [27]. Observations from the younger groups of the Polish population, i.e. below the age of 20 years, would add complementary information leading to better assessment of FH in the Polish population. However, it is unlikely that it will be accomplished in the near future, as cholesterol screening is not recommended for people below the age of 18 years. The postulated tool for the detection of FH is cascade screening. This is based on detailed examinations of the first- and second-degree relatives of the probands (index cases). The latter might emerge from either by-chance examination or from the population screening, which would provide information on blood cholesterol, premature CHD, and cardiac deaths in family members or tendon xanthomas in the proband or his/her family member [3, 5, 8, 32]. We believe that our study allows for a better understanding of how many cases of FH can emerge from the population cholesterol screening facilitating the planning of a strategy to manage the disease at a population level. We hope that our results will draw the attention of health managers and clinicians, particularly primary care physicians involved in population cholesterol screening in the group of people with potential FH. In Poland, a country with 38 million residents, the size of this group is about 150,000 ±50,000 adult people. These people require special diagnostics which would involve not only themselves but also all of their first- and second-degree relatives and which would include genetic testing and other more sophisticated biochemical diagnostics. Furthermore, it could be expected that many of them would require intensive treatment with high doses of highly potent statins alone or in combination with other lipid-lowering agents including new generations of efficacious drugs [24, 33]. All these points need to be addressed urgently, to develop a national strategy for the detection, diagnosis, and treatment of FH.
  30 in total

1.  Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report.

Authors: 
Journal:  Circulation       Date:  2002-12-17       Impact factor: 29.690

2.  Prevalence and treatment of familial hypercholesterolaemia in Australian communities.

Authors:  Gerald F Watts; Jonathan E Shaw; Jing Pang; Dianna J Magliano; Garry L R Jennings; Melinda J Carrington
Journal:  Int J Cardiol       Date:  2015-03-03       Impact factor: 4.164

3.  Prevalence and management of familial hypercholesterolaemia in coronary patients: An analysis of EUROASPIRE IV, a study of the European Society of Cardiology.

Authors:  Guy De Backer; Joost Besseling; John Chapman; G Kees Hovingh; John J P Kastelein; Kornelia Kotseva; Kausik Ray; Željko Reiner; David Wood; Dirk De Bacquer
Journal:  Atherosclerosis       Date:  2015-04-30       Impact factor: 5.162

4.  [Prevalence of dyslipidemia in men and women between the ages of 20-74 in Poland. Results of the WOBASZ program].

Authors:  Andrzej Pajak; Ewa Wiercińska; Maria Polakowska; Krystyna Kozakiewicz; Krystyna Kaczmarczyk-Chałas; Andrzej Tykarski; Danuta Gaździk; Tomasz Zdrojewski
Journal:  Kardiol Pol       Date:  2005       Impact factor: 3.108

5.  Cost effectiveness analysis of different approaches of screening for familial hypercholesterolaemia.

Authors:  Dalya Marks; David Wonderling; Margaret Thorogood; Helen Lambert; Steve E Humphries; H Andrew W Neil
Journal:  BMJ       Date:  2002-06-01

6.  [Monitoring trends in cardiovascular disease incidence and mortality and their determinants: "Pol-Monica" longitudinal study. II. Materials and methods].

Authors:  S Rywik; J Sznajd; W Kulesza; M Magdoń; H Przestalska-Malkin; A Pajak; H Wagrowska; M Malczewska-Malec; W Kupść; B Idzior-Waluś
Journal:  Przegl Lek       Date:  1985

7.  ESC/EAS Guidelines for the management of dyslipidaemias: the Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and the European Atherosclerosis Society (EAS).

Authors:  Zeljko Reiner; Alberico L Catapano; Guy De Backer; Ian Graham; Marja-Riitta Taskinen; Olov Wiklund; Stefan Agewall; Eduardo Alegria; M John Chapman; Paul Durrington; Serap Erdine; Julian Halcox; Richard Hobbs; John Kjekshus; Pasquale Perrone Filardi; Gabriele Riccardi; Robert F Storey; David Wood
Journal:  Eur Heart J       Date:  2011-06-28       Impact factor: 29.983

8.  Anti-PCSK9 antibody effectively lowers cholesterol in patients with statin intolerance: the GAUSS-2 randomized, placebo-controlled phase 3 clinical trial of evolocumab.

Authors:  Erik Stroes; David Colquhoun; David Sullivan; Fernando Civeira; Robert S Rosenson; Gerald F Watts; Eric Bruckert; Leslie Cho; Ricardo Dent; Beat Knusel; Allen Xue; Rob Scott; Scott M Wasserman; Michael Rocco
Journal:  J Am Coll Cardiol       Date:  2014-03-30       Impact factor: 24.094

9.  Prevalence and control of cardiovascular risk factors in Poland. Assumptions and objectives of the NATPOL 2011 Survey.

Authors:  Tomasz Zdrojewski; Marcin Rutkowski; Piotr Bandosz; Zbigniew Gaciong; Tadeusz Jędrzejczyk; Bogdan Solnica; Michał Pencina; Wojciech Drygas; Bogdan Wojtyniak; Tomasz Grodzicki; Jerzy Piwoński; Bogdan Wyrzykowski
Journal:  Kardiol Pol       Date:  2013       Impact factor: 3.108

10.  Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus statement of the European Atherosclerosis Society.

Authors:  Børge G Nordestgaard; M John Chapman; Steve E Humphries; Henry N Ginsberg; Luis Masana; Olivier S Descamps; Olov Wiklund; Robert A Hegele; Frederick J Raal; Joep C Defesche; Albert Wiegman; Raul D Santos; Gerald F Watts; Klaus G Parhofer; G Kees Hovingh; Petri T Kovanen; Catherine Boileau; Maurizio Averna; Jan Borén; Eric Bruckert; Alberico L Catapano; Jan Albert Kuivenhoven; Päivi Pajukanta; Kausik Ray; Anton F H Stalenhoef; Erik Stroes; Marja-Riitta Taskinen; Anne Tybjærg-Hansen
Journal:  Eur Heart J       Date:  2013-08-15       Impact factor: 29.983

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  15 in total

1.  PoLA/CFPiP/PCS Guidelines for the Management of Dyslipidaemias for Family Physicians 2016.

Authors:  Maciej Banach; Piotr Jankowski; Jacek Jóźwiak; Barbara Cybulska; Adam Windak; Tomasz Guzik; Artur Mamcarz; Marlena Broncel; Tomasz Tomasik; Jacek Rysz; Agnieszka Jankowska-Zduńczyk; Piotr Hoffman; Agnieszka Mastalerz-Migas
Journal:  Arch Med Sci       Date:  2016-12-19       Impact factor: 3.318

2.  PoLA/CFPiP/PCS/PSLD/PSD/PSH guidelines on diagnosis and therapy of lipid disorders in Poland 2021.

Authors:  Maciej Banach; Paweł Burchardt; Krzysztof Chlebus; Piotr Dobrowolski; Dariusz Dudek; Krzysztof Dyrbuś; Mariusz Gąsior; Piotr Jankowski; Jacek Jóźwiak; Longina Kłosiewicz-Latoszek; Irina Kowalska; Maciej Małecki; Aleksander Prejbisz; Michał Rakowski; Jacek Rysz; Bogdan Solnica; Dariusz Sitkiewicz; Grażyna Sygitowicz; Grażyna Sypniewska; Tomasz Tomasik; Adam Windak; Dorota Zozulińska-Ziółkiewicz; Barbara Cybulska
Journal:  Arch Med Sci       Date:  2021-11-08       Impact factor: 3.318

3.  Prevalence and Predictors of Cholesterol Screening, Awareness, and Statin Treatment Among US Adults With Familial Hypercholesterolemia or Other Forms of Severe Dyslipidemia (1999-2014).

Authors:  Emily M Bucholz; Angie Mae Rodday; Katherine Kolor; Muin J Khoury; Sarah D de Ferranti
Journal:  Circulation       Date:  2018-03-26       Impact factor: 29.690

4.  Diabetes mellitus and congestive heart failure: the prevalence of congestive heart failure in patients with and without diabetes in Poland.

Authors:  Waldemar Wierzba; Waldemar Karnafel; Andrzej Śliwczyński; Jarosław Pinkas; Mariusz Gujski
Journal:  Arch Med Sci       Date:  2018-04-06       Impact factor: 3.318

5.  Use of next-generation sequencing to detect LDLR gene copy number variation in familial hypercholesterolemia.

Authors:  Michael A Iacocca; Jian Wang; Jacqueline S Dron; John F Robinson; Adam D McIntyre; Henian Cao; Robert A Hegele
Journal:  J Lipid Res       Date:  2017-09-05       Impact factor: 5.922

6.  Clinical management of heterozygous familial hypercholesterolemia in a Polish outpatient metabolic clinic: a retrospective observational study.

Authors:  Longina Kłosiewicz-Latoszek; Barbara Cybulska; Janina Białobrzeska-Paluszkiewicz; Anna Jagielska; Jolanta Janowska; Dorota Danowska; Anna Reguła; Małgorzata Stroniawska-Woźniak
Journal:  Arch Med Sci       Date:  2017-11-30       Impact factor: 3.318

7.  Predictors of Family Enrollment in a Genetic Cascade Screening Program for Familial Hypercholesterolemia.

Authors:  Pãmela Rodrigues de Souza Silva; Cinthia Elim Jannes; Theo G M Oliveira; Luz Marina Gómez Gómez; José E Krieger; Raul D Santos; Alexandre Costa Pereira
Journal:  Arq Bras Cardiol       Date:  2018-08-23       Impact factor: 2.000

8.  Genotype distribution of hepatitis C virus in 952 cases from 2014 to 2016 in Hunan Province, China.

Authors:  Jian-Hua Lei; Xing Gong; Xin-Qiang Xiao; Zi Chen; Feng Peng
Journal:  Arch Med Sci       Date:  2017-10-12       Impact factor: 3.318

9.  Q192R polymorphism in the PON1 gene and familial hypercholesterolemia in a Saudi population.

Authors:  Khalid Khalaf Alharbi; May Salem Alnbaheen; Fawiziah Khalaf Alharbi; Rana M Hasanato; Imran Ali Khan
Journal:  Ann Saudi Med       Date:  2017 Nov-Dec       Impact factor: 1.526

Review 10.  Estimating the prevalence of heterozygous familial hypercholesterolaemia: a systematic review and meta-analysis.

Authors:  Leo E Akioyamen; Jacques Genest; Shubham D Shan; Rachel L Reel; Jordan M Albaum; Anna Chu; Jack V Tu
Journal:  BMJ Open       Date:  2017-09-01       Impact factor: 2.692

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