Simon Broome Research Articles

Case detection of familial hypercholesterolemia using various criteria during an annual health examination in the workplace

BackgroundEarly diagnosis and appropriate treatment of subjects with familial hypercholesterolemia (FH) could prevent cardiovascular disease (CAD). ObjectiveWe aimed to identify potential cases of FH during a workplace screening and to explore their clinical data. MethodPersonnel who attended an annual health examination were invited to answer a questionnaire and to provide consent to review their laboratory results. FH was clinically diagnosed using any one of the three standard criteria: Dutch Lipid Clinic Network (DLCN), Simon Broome (SB), and Make Early Diagnosis to Prevent Early Deaths (MEDPED). Clinical characteristics were compared between FH and unlikely FH subjects. ResultsAmong 6607 participants, potential cases of FH were identified in 2.5 % by DLCN, 4.0 % by SB, and 0.8 % by MEDPED alone. Premature CAD, hypertension, and current smoking were significantly more common in potential FH subjects than in unlikely FH subjects. Potential FH subjects also had significantly higher body mass index, waist circumference, blood pressure, fasting plasma glucose and triglyceride levels than unlikely FH subjects. Among potential FH subjects, lipid-lowering medication was used in 28.4 %. The achievement of the LDL-C goal (<100 mg/dL) in potential FH subjects was significantly lower than that in unlikely FH subjects (15 % vs. 28 %, respectively, P = 0.005) despite a higher rate of high-intensity statin use (25 % vs. 10 %, respectively, P = 0.002). ConclusionThe workplace screening of FH detected a significant number of potential FH subjects with higher cardiovascular risk. This strategy identified individuals for whom intensification of both lifestyle modifications and pharmacological treatment should be a priority.

Familial Hypercholesterolaemia Patients with LDLR Mutation Among Asian Population in Southeast Asian Countries: Systematic Review

Familial hypercholesterolaemia (FH) is a genetic disorder associated with premature cardiovascular diseases; however, the majority of patients remain undertreated. This systematic review aimed to determine the prevalence of FH patients with low-density lipoprotein receptor (LDLR) gene pathogenic variants (PV) among the Asian population in Southeast Asian countries. Our search yielded 1,120 citations, with 28 deemed possibly suitable based on title and abstract screening. However, only six studies that utilised the Dutch Lipid Clinic Network (DLCN) or Simon Broome (SB) criteria were eligible to be included. These studies provided prevalence figures for clinically diagnosed FH patients, with a total of 17.1% (n=1,005/5,874); this rate was represented by three Malaysian studies, which estimated that 36–76% of clinically diagnosed FH patients had LDLR PV. Most patients reported having pre-existing cardiovascular disease, a family history of premature coronary artery disease and tendon xanthomata. This study found that the prevalence of LDLR PV among genetically confirmed FH patients in Southeast Asia is 20.5% (n=286/5,874). Genetically confirmed FH patients are at a higher risk of developing premature coronary artery disease, requiring more aggressive lipid-lowering treatment. Therefore, identifying LDLR PV among the population is essential for early FH diagnosis and treatment. KEYWORDS Arterial disease, autosomal dominant, LDL receptor, LDLR prevalence, pathogenic variants, premature CAD, Undertreated

Clinical and genetic diagnosis of familial hypercholesterolaemia in patients undergoing coronary angiography: the Ludwigshafen Risk and Cardiovascular Health Study.

To investigate the prevalence of familial hypercholesterolaemia (FH) and compare the performance of clinical criteria and genetic testing in patients undergoing coronary angiography. The prevalence of FH was determined with the Dutch Lipid Clinical Network (DLCN), US-MEDPED, Simon Broome (SB) criteria, the 'Familial Hypercholesterolaemia Case Ascertainment Tool' (FAMCAT), and a clinical algorithm. Genetic screening was conducted with a custom array from Affymetrix (CARRENAL array) harboring 944 FH mutations. The study cohort consisted of 3267 patients (78.6% with coronary artery disease [CAD]). FH was diagnosed in 2.8%, 2.2%, 3.9%, and 7.9% using the DLCN, US-MEDPED, SB criteria, and the FAMCAT. The clinical algorithm identified the same patients as the SB criteria. Pathogenic FH mutations were found in 1.2% (1.2% in patients with CAD, 1.0% in patients without CAD). FH was more frequently diagnosed in younger patients. With genetic testing as reference, the clinical criteria achieved areas under the ROC curve (AUCs) in the range of 0.56-0.68. Using only LDL-C corrected for statin intake, an AUC of 0.68 was achieved. FH is up to fourfold more prevalent in patients undergoing coronary angiography than in contemporary cohorts representing the general population. Different clinical criteria yield substantially different diagnosis rates, overestimating the prevalence of FH compared to genetic testing. LDL-C testing alone may be sufficient to raise the suspicion of FH, which then needs to be corroborated by genetic testing.

Reducing Premature Coronary Artery Disease in Malaysia by Early Identification of Familial Hypercholesterolemia Using the Familial Hypercholesterolemia Case Ascertainment Tool (FAMCAT): Protocol for a Mixed Methods Evaluation Study.

Familial hypercholesterolemia (FH) is predominantly caused by mutations in the 4 FH candidate genes (FHCGs), namely, low-density lipoprotein receptor (LDLR), apolipoprotein B-100 (APOB-100), proprotein convertase subtilisin/kexin type 9 (PCSK9), and the LDL receptor adaptor protein 1 (LDLRAP1). It is characterized by elevated low-density lipoprotein cholesterol (LDL-c) levels leading to premature coronary artery disease. FH can be clinically diagnosed using established clinical criteria, namely, Simon Broome (SB) and Dutch Lipid Clinic Criteria (DLCC), and can be identified using the Familial Hypercholesterolemia Case Ascertainment Tool (FAMCAT), a primary care screening tool. This study aims to (1) compare the detection rate of genetically confirmed FH and diagnostic accuracy between the FAMCAT, SB, and DLCC in the Malaysian primary care setting; (2) identify the genetic mutation profiles, including novel variants, in individuals with suspected FH in primary care; (3) explore the experience, concern, and expectation of individuals with suspected FH who have undergone genetic testing in primary care; and (4) evaluate the clinical utility of a web-based FH Identification Tool that includes the FAMCAT, SB, and DLCC in the Malaysian primary care setting. This is a mixed methods evaluation study conducted in 11 Ministry of Health primary care clinics located at the central administrative region of Malaysia. In Work stream 1, the diagnostic accuracy study design is used to compare the detection rate and diagnostic accuracy of the FAMCAT, SB, and DLCC against molecular diagnosis as the gold standard. In Work stream 2, the targeted next-generation sequencing of the 4 FHCGs is used to identify the genetic mutation profiles among individuals with suspected FH. In Work stream 3a, a qualitative semistructured interview methodology is used to explore the experience, concern, and expectation of individuals with suspected FH who have undergone genetic testing. Lastly, in Work stream 3b, a qualitative real-time observation of primary care physicians using the "think-aloud" methodology is applied to evaluate the clinical utility of a web-based FH Identification Tool. The recruitment for Work stream 1, and blood sampling and genetic analysis for Work stream 2 were completed in February 2023. Data collection for Work stream 3 was completed in March 2023. Data analysis for Work streams 1, 2, 3a, and 3b is projected to be completed by June 2023, with the results of this study anticipated to be published by December 2023. This study will provide evidence on which clinical diagnostic criterion is the best to detect FH in the Malaysian primary care setting. The full spectrum of genetic mutations in the FHCGs including novel pathogenic variants will be identified. Patients' perspectives while undergoing genetic testing and the primary care physicians experience in utilizing the web-based tool will be established. These findings will have tremendous impact on the management of patients with FH in primary care and subsequently reduce their risk of premature coronary artery disease. DERR1-10.2196/47911.

The effect of adjusting LDL-cholesterol for Lp(a)-cholesterol on the diagnosis of familial hypercholesterolaemia

Familial hypercholesterolaemia (FH) diagnostic tools help prioritise patients for genetic testing and include LDL-C estimates commonly calculated using the Friedewald equation. However, cholesterol contributions from lipoprotein(a) (Lp(a)) can overestimate 'true' LDL-C, leading to potentially inappropriate clinical FH diagnosis. To assess how adjusting LDL-C for Lp(a)-cholesterol affects FH diagnoses using Simon Broome (SB) and Dutch Lipid Clinic Network (DLCN) criteria. Adults referred to a tertiary lipid clinic in London, UK were included if they had undergone FH genetic testing based on SB or DLCN criteria. LDL-C was adjusted for Lp(a)-cholesterol using estimated cholesterol contents of 17.3%, 30% and 45%, and the effects of these adjustments on reclassification to 'unlikely' FH and diagnostic accuracy were determined. Depending on the estimated cholesterol content applied, LDL-C adjustment reclassified 8-23% and 6-17% of patients to 'unlikely' FH using SB and DLCN criteria, respectively. The highest reclassification rates were observed following 45% adjustment in mutation-negative patients with higher Lp(a) levels. This led to an improvement in diagnostic accuracy (46% to 57% with SB, and 32% to 44% with DLCN following 45% adjustment) through increased specificity. However all adjustment factors led to erroneous reclassification of mutation-positive patients to 'unlikely' FH. LDL-C adjustment for Lp(a)-cholesterol improves the accuracy of clinical FH diagnostic tools. Adopting this approach would reduce unnecessary genetic testing but also incorrectly reclassify mutation-positive patients. Health economic analysis is needed to balance the risks of over- and under-diagnosis before LDL-C adjustments for Lp(a) can be recommended.

Electronic health record-based facilitation of familial hypercholesterolaemia detection sensitivity of different algorithms in genetically confirmed patients.

Familial hypercholesterolaemia (FH) is a disorder of LDL cholesterol clearance, resulting in increased risk of cardiovascular disease. Recently, we developed a Dutch Lipid Clinic Network (DLCN) criteria-based algorithm to facilitate FH detection in electronic health records (EHRs). In this study, we investigated the sensitivity of this and other algorithms in a genetically confirmed FH population. All patients with a healthcare insurance-related coded diagnosis of 'primary dyslipidaemia' between 2018 and 2020 were assessed for genetically confirmed FH. Data were extracted at the time of genetic confirmation of FH (T1) and during the first visit in 2018-2020 (T2). We assessed the sensitivity of algorithms on T1 and T2 for DLCN ≥ 6 and compared with other algorithms [familial hypercholesterolaemia case ascertainment tool (FAMCAT), Make Early Diagnoses to Prevent Early Death (MEDPED), and Simon Broome (SB)] using EHR-coded data and using all available data (i.e. including non-coded free text). 208 patients with genetically confirmed FH were included. The sensitivity (95% CI) on T1 and T2 with EHR-coded data for DLCN ≥ 6 was 19% (14-25%) and 22% (17-28%), respectively. When using all available data, the sensitivity for DLCN ≥ 6 was 26% (20-32%) on T1 and 28% (22-34%) on T2. For FAMCAT, the sensitivity with EHR-coded data on T1 was 74% (67-79%) and 32% (26-39%) on T2, whilst sensitivity with all available data was 81% on T1 (75-86%) and 45% (39-52%) on T2. For Make Early Diagnoses to Prevent Early Death MEDPED and SB, using all available data, the sensitivity on T1 was 31% (25-37%) and 17% (13-23%), respectively. The FAMCAT algorithm had significantly better sensitivity than DLCN, MEDPED, and SB. FAMCAT has the best potential for FH case-finding using EHRs.

Comparative study on the performance of different classification algorithms, combined with pre- and post-processing techniques to handle imbalanced data, in the diagnosis of adult patients with familial hypercholesterolemia.

Familial Hypercholesterolemia (FH) is an inherited disorder of cholesterol metabolism. Current criteria for FH diagnosis, like Simon Broome (SB) criteria, lead to high false positive rates. The aim of this work was to explore alternative classification procedures for FH diagnosis, based on different biological and biochemical indicators. For this purpose, logistic regression (LR), naive Bayes classifier (NB), random forest (RF) and extreme gradient boosting (XGB) algorithms were combined with Synthetic Minority Oversampling Technique (SMOTE), or threshold adjustment by maximizing Youden index (YI), and compared. Data was tested through a 10 × 10 repeated k-fold cross validation design. The LR model presented an overall better performance, as assessed by the areas under the receiver operating characteristics (AUROC) and precision-recall (AUPRC) curves, and several operating characteristics (OC), regardless of the strategy to cope with class imbalance. When adopting either data processing technique, significantly higher accuracy (Acc), G-mean and F1 score values were found for all classification algorithms, compared to SB criteria (p < 0.01), revealing a more balanced predictive ability for both classes, and higher effectiveness in classifying FH patients. Adjustment of the cut-off values through pre or post-processing methods revealed a considerable gain in sensitivity (Sens) values (p < 0.01). Although the performance of pre and post-processing strategies was similar, SMOTE does not cause model’s parameters to loose interpretability. These results suggest a LR model combined with SMOTE can be an optimal approach to be used as a widespread screening tool.

Familial hypercholesterolemia in China requires greater efforts

Familial hypercholesterolemia in China requires greater efforts

Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects

Familial Hypercholesterolemia (FH) is an inherited disorder of lipid metabolism, characterized by increased low density lipoprotein cholesterol (LDLc) levels. The main purpose of the current work was to explore alternative classification methods to traditional clinical criteria for FH diagnosis, based on several biochemical and biological indicators. Logistic regression (LR), decision tree (DT), random forest (RF) and naive Bayes (NB) algorithms were developed for this purpose, and thresholds were optimized by maximization of Youden index (YI). All models presented similar accuracy (Acc), specificity (Spec) and positive predictive values (PPV). Sensitivity (Sens) and G-mean values were significantly higher in LR and RF models, compared to the DT. When compared to Simon Broome (SB) biochemical criteria for FH diagnosis, all models presented significantly higher Acc, Spec and G-mean values (p < 0.01), and lower negative predictive value (NPV, p < 0.05). Moreover, LR and RF models presented comparable Sens values. Adjustment of the cut-off point by maximizing YI significantly increased Sens values, with no significant loss in Acc. The obtained results suggest such classification algorithms can be a viable alternative to be used as a widespread screening method. An online application has been developed to assess the performance of the LR model in a wider population.

Agreement between the various familial hypercholesterolaemia diagnostic criteria in Malaysian population

Background and Aims: Aim: Diagnostic tools for familial hypercholesterolemia (FH), including the Dutch Lipid Clinic Criteria (DLCC), British Simon Broome (SB) and the US Make Early Diagnosis to Prevent Early Deaths (US MEDPED) criteria, are used to identify FH patients. However, their diagnostic outcomes may not be in agreement with each other. Furthermore, the agreement between those criteria is unclear in the Asian population. This study aimed to investigate the agreement between these criteria in an Asian population.

Systematic Identification of Familial Hypercholesterolaemia in Primary Care-A Systematic Review.

Familial hypercholesterolaemia (FH) is a common inherited cause of premature cardiovascular disease, but the majority of patients remain undiagnosed. The aim of this systematic review was to assess the effectiveness of interventions to systematically identify FH in primary care. No randomised, controlled studies were identified; however, three non-randomised intervention studies were eligible for inclusion. All three studies systematically identified FH using reminders (on-screen prompts) in electronic health records. There was insufficient evidence that providing comments on laboratory test results increased the identification of FH using the Dutch Lipid Clinic Network (DLCN) criteria. Similarly, using prompts combined with postal invitation demonstrated no significant increase in definite FH identification using Simon-Broome (SB) criteria; however, the identification of possible FH increased by 25.4% (CI 17.75 to 33.97%). Using on-screen prompts alone demonstrated a small increase of 0.05% (95% CI 0.03 to 0.07%) in identifying definite FH using SB criteria; however, when the intervention was combined with an outreach FH nurse assessment, the result was no significant increase in FH identification using a combination of SB and DLCN criteria. None of the included studies reported adverse effects associated with the interventions. Currently, there is insufficient evidence to determine which is the most effective method of systematically identifying FH in non-specialist settings.

Evaluation of cardiovascular risk factors in patients with familial hypercholesterolemia from the North-Eastern area of Romania

BackgroundFamilial hypercholesterolemia(FH) is one of the most frequent and important monogenic cholesterol pathologies. Traditional and non-traditional cardiovascular risk factors increase the prevalence of atherosclerotic cardiovascular disease(ASCVD) in this population. The aims of the study were: (a) to identify FH patients in the North-Eastern part of Romania and to analyze demographic, clinical and paraclinical data (b) to evaluate the risk of new cardiovascular events at follow-up in FH patients stratified by lipid-lowering agents.MethodsThis first prospective study in the North-Eastern part of Romania was carried out between October 2017 and October 2019; out of 980 patients with dyslipidemia evaluated with the Dutch Lipid Network(DLCN) and Simon Broome(SM) scores, 61 patients with DLCN score above 3 and possible/probable FH(SM score) were included.ResultsNine hundred-eighty patients were examined and 61 (6.2%) were received the clinical diagnosis of FH. The mean age was 48.5±12.5 years, with more female patients than male patients (63.9% versus 36%). Hypertension was the main cardiovascular risk factor for both genders, followed by physical inactivity and obesity for the female group and active smoking for the male group. The measured DLCN score recorded: “possible” FH identified in 39.4%, “probable” FH in 45.9% and “definite” FH in 14.7%. The effective lipid-lowering drugs used were statin alone and statin in association with fenofibrate, which improved both the lipid profile values and the subclinical atherosclerosis markers (ankle-brachial index, carotid intima-media thickness and high-sensitivity C-reactive protein). New ASCVDs that emerged during the study were most commonly represented by coronary heart disease and stroke. At the same time, the new cardiovascular events were delayed in patients receiving the lipid-lowering drugs, without significant differences between them.ConclusionsIn patients with suspected FH, the lipid-lowering agents during the follow-up period delayed the new cardiovascular events, yet failed to reach the goals proposed by the guidelines.

Cardiovascular disease incidence in 21 years follow-up in severe and non-severe familial hypercholesterolaemia (FH) : Data from the UK Simon Broome FH register

Background and Aims: Background: The Simon Broome (SB) FH register has previously reported a 2.2-fold higher Cardiovascular Disease (CVD) mortality in those with “severe-FH” (SFH) compared to “non-severe-FH” (NSFH). Here we examine CVD morbidity over 21 years follow-up, by linking the register participants with the UK secondary care Hospital Episode Statistics (HES) database.

Classification methods applied to familial hypercholesterolemia diagnosis at pediatric age: Comparison of Simon Broome criteria with modified decision tree models

Background and Aims: Familial hypercholesterolemia (FH) is an autosomal dominant disorder of lipid metabolism, characterized by increased low density lipoprotein cholesterol (LDLc) levels, which represents a major risk factor for cardiovascular disease (CVD). An early diagnosis of FH is therefore of paramount importance for adequate management and prognosis. Simon Broome (SB) criteria for FH diagnosis are among the most frequently used in clinical setting, and are based on family history, presence of physical signs, and LDLc and total cholesterol (TC) levels. The main purpose of this work was to build different decision tree (DT) classification models for FH diagnosis, using several biochemical markers as predictors.

Abstract 14681: Comparative Study Between International Guidelines in Detecting Pediatric Familial Hypercholesterolemia Through a Unique Community Health System in Kagawa, Japan

Introduction: Familial hypercholesterolemia (FH) is an autosomal hereditary disease found in patients who have elevated low-density lipoprotein cholesterol (LDL-C) from birth. Early detection and treatment of FH during childhood potentially reduces the risk of premature cardiovascular events. In Kagawa prefecture, a unique community health system, involving three steps, has been conducted to prevent lifestyle-related diseases for 10-year-old children. This system includes universal lipid screening, selection by pediatricians, and next-generation sequencing (NGS) of FH-related genes in hospitals. The aim of this study is to compare 3 international guidelines to detect pediatric FH with this unique community health system in Kagawa. Methods: In Kagawa prefecture, the universal lipid screening of approximately 8,000 children at 10 years of age is performed annually, covering over 90% of the target group. After excluding secondary hypercholesterolemia, pediatric clinics introduced children with LDL-C &gt;140mg/dL to 4 designated hospitals to perform NGS. We applied the guidelines of the Dutch Lipid Clinic Network (DLCN), Simon Broome (SB), and the Japanese Atherosclerosis Society (JAS) to children who received NGS in the unique community health system in Kagawa. Results: We performed NGS for 46 children from January 2018 to February 2020 (LDL-C 186.0±50.3 mg/dL; Male/F 27/19) and 26 (57%) had FH genetic mutations (23 LDL-R and 3 PCSK9 mutations). Seventeen children met FH criteria for DLCN (35%), 10 for Simon Broome (22%), and 11 for JAS (24%), respectively. The combination of NGS and either of the 3 guidelines increased the number of children diagnosed as FH up to 31 (67%). Conclusion: International guidelines detected only half of pediatric FH who were diagnosed by the unique community health system in Kagawa. Further investigation will be required to build an effective universal screening system for pediatric FH.

Comparison between different diagnostic scores for the diagnosis of familial hypercholesterolemia: assessment of their diagnostic accuracy in comparison with genetic testing

Abstract Background The Dutch Lipid Clinic Network Score (DLCN) is a useful score to guide the physician to the diagnosis of familial hypercholesterolemia (FH). However, some concerns have been pointed out about its diagnostic accuracy in pediatric population; so, other scores such as Simon Broome (SB) and US MedPed Program have been tested and currently used. Aim To test the different diagnostic and predictive accuracy between those three scores (DLCN, SM and MedPed) in relation to positivity of genetic test. Methods We enrolled 25 pediatric patients aged &amp;lt;18 yo referred to our Chieti and Rome lipid clinics for the clinical suspicion of FH. We performed the genetic analysis for searching pathogenetic mutations for FH (NGS by Lipid in Code, LIPIGEN study). Differently from the others, DLCN provides a numerical data as a diagnostic score; thus, to uniform the three scores, we chose to define subjects with a DLCN score ≥6 as likely FH, while subjects with a lower value were defined as unlikely FH. Furthermore, we calculated the SB and the MedPed score, as previously demonstrated, defining the subjects as likely or unlikely FH. Therefore, we analyzed the diagnostic accuracy of those scores in relation to FH mutation data (positive or negative). Results We recruited 25 patients, 13 males (52%), mean age of 11.8 years. Sixteen patients (64%) resulted positive for the genetic mutation The DLCN showed a sensitivity of 43%, specificity of 66%, a positive predictive value (PPV) of 0.7 and a negative predictive value (NPV) of 0.4. SB showed a sensitivity of 68%, specificity of 55%, a PPV of 0.73 and NPV of 0.5. The MedPed score showed a sensitivity of 68%, specificity of 44%, a PPV of 0.68 and NPV of 0.44. Furthermore, we elaborated a ROC curve of low-density lipoprotein cholesterol (LDL-C) values with respect to the positivity of the FH genetic test: the value that showed the best diagnostic accuracy was 190 mg / dL (sensitivity 68.8% and specificity 75%), while the value of 116.5 mg/dL demonstrated a sensitivity of 100% but with a specificity of 11%. Conclusions Our work demonstrates that none of the three scores tested has an optimal diagnostic accuracy with respect to the diagnosis of FH in the pediatric population. By comparison, SB demonstrates the best sensitivity and the best specificity. In addition, the LDL-C value of 190 mg / dL provides the best diagnostic accuracy against the diagnosis of FH in the pediatric population. Further data and studies will be needed to improve the diagnostic performance of these scores, in order to refer pediatric patients to the genetic test, for an early confirmation in order to refer pediatric patients to the genetic test, for an early FH diagnosis confirmation. Funding Acknowledgement Type of funding source: None

Sex differences in cardiovascular morbidity associated with familial hypercholesterolaemia: A retrospective cohort study of the UK Simon Broome register linked to national hospital records

Background and aimsThe UK Simon Broome (SB) familial hypercholesterolaemia (FH) register previously reported 3-fold higher standardised mortality ratio for cardiovascular disease (CVD) in women compared to men from 2009 to 2015. Here we examined sex differences in CVD morbidity in FH by national linkage of the SB register with Hospital Episode Statistics (HES). MethodsOf 3553 FH individuals in the SB register (aged 20–79 years at registration), 2988 (52.5% women) had linked HES records. Standardised Morbidity Ratios (SMbR) compared to an age and sex-matched UK general practice population were calculated [95% confidence intervals] for first CVD hospitalisation in HES (a composite of coronary heart disease (CHD), myocardial infarction (MI), stable or unstable angina, stroke, TIA, peripheral vascular disease (PVD), heart failure, coronary revascularisation interventions). ResultsAt registration, men had significantly (p < 0.001) higher prevalence of previous CHD (24.8% vs 17.6%), previous MI (13.2% vs 6.3%), and were commenced on lipid-lowering treatment at a younger age than women (37.5 years vs 42.3 years). The SMbR for composite CVD was 6.83 (6.33–7.37) in men and 7.55 (6.99–8.15) in women. In individuals aged 30–50 years, SMbR in women was 50% higher than in men (15.04 [12.98–17.42] vs 10.03 [9.01–11.17]). In individuals >50 years, SMbR was 33% higher in women than men (6.11 [5.57–6.70] vs 4.59 [4.08–5.15]). ConclusionsExcess CVD morbidity due to FH remains markedly elevated in women at all ages, but especially those aged 30–50 years. This highlights the need for earlier diagnosis and optimisation of lipid-lowering risk factor management for all FH patients, with particular attention to young women with FH.

IN SILICO VERSUS CLINICAL CRITERIA FOR THE DIAGNOSIS OF FAMILIAL HYPERCHOLESTEROLEMIA: A COMPARATIVE EVALUATION

Familial hypercholesterolemia (FH) carries up to a 22-fold higher risk of cardiovascular disease. The Dutch Lipid Clinical Criteria (DLCC), Simon Broome (SB) Criteria, and the US Make Early Diagnosis to Prevent Early Deaths (MEDPED) Criteria are used to diagnose FH. The Healthy Nevada Project (HNP)

Effect of Lipoprotein(a) on the Diagnosis of Familial Hypercholesterolemia: Does It Make a Difference in the Clinic?

Diagnostic tools for familial hypercholesterolemia (FH) rely on estimation of LDL cholesterol concentration. However, routine measurement or calculation of LDL cholesterol concentration using the Friedewald equation contains a cholesterol contribution from lipoprotein(a) [Lp(a)]. We investigated whether Lp(a) influences the phenotypic diagnosis of FH by commonly used clinical criteria. A cohort of 907 adult index patients attending a clinic were studied. The Dutch Lipid Clinic Network (DLCN) and Simon Broome (SB) diagnostic criteria were estimated before and after adjusting LDL cholesterol concentration for the cholesterol content (30%) of Lp(a). Diagnostic reclassification rates and area under the ROC (AUROC) curves in predicting an FH mutation were also compared. Seventy-four patients defined by DLCN criteria (8.2%) and 207 patients defined by SB criteria (22.8%) were reclassified to "unlikely" FH after adjusting LDL cholesterol for Lp(a) cholesterol. The proportion of FH patients defined by DLCN (probable/definite) and SB (possible/definite) criteria decreased significantly in patients with increased Lp(a) (>0.5 g/L; n = 330) after Lp(a) cholesterol adjustment (P < 0.01). The overall reclassification rate was significantly higher in patients with Lp(a) concentration >1.0 g/L (P < 0.001). The AUROC curve for LDL cholesterol concentration ≥191 mg/dL (≥5.0 mmol/L), DLCN criteria, and SB criteria in predicting an FH mutation increased significantly after adjustment (P < 0.001). There was no significant difference in AUROC curve before and after Lp(a) cholesterol adjustment at an LDL cholesterol concentration ≥251 mg/dL (≥6.5 mmol/L). Adjusting LDL cholesterol concentration for Lp(a) cholesterol improves the diagnostic accuracy of DLCN and SB criteria, especially with Lp(a) >1.0 g/L and LDL cholesterol <251 mg/dL (<6.5 mmol/L). Lp(a) should be measured in all patients suspected of having FH.

Coronary heart disease mortality in severe and non-severe familial hyper-cholesterolaemia : data from the uk simon broome fh register.

Background and Aims: