Rationale and background
Hypertrophic cardiomyopathy (HCM) is an inherited heart disease characterised by an increased wall thickness or mass of the left ventricular wall, with a broad clinical spectrum. The diagnosis of HCM requires the presence of hypertrophy of the left ventricle (LV) in the absence of any other cardiac, metabolic, or systemic disease (e.g., systemic hypertension) that could explain the observed hypertrophy. HCM is classified into two types based on the presence or absence of left ventricular outflow tract (LVOT) obstruction, a distinction that influences patient management. The obstructive form of HCM (oHCM) is observed in approximately 66% of patients.
The prevalence of HCM in the general population was initially estimated to be approximately 1 in 500 individuals (0.2%) in a study conducted in the United States (U.S). However, discrepancies in the literature including findings from several studies in U.S. and Europe, suggest a much lower prevalence of clinically diagnosed HCM, indicating that many individuals with HCM may experience a normal lifespan without significant symptoms or the need for major interventions.
Estimating the prevalence of HCM is challenging due to several factors, including the relative rarity of the condition, the high proportion of asymptomatic patients, and diagnostic difficulties. Furthermore, fragmentation across healthcare databases can hinder accurate estimation, as patient histories may be incomplete or unavailable. As a result, large-scale epidemiological studies on the demographics and morbidity burden of HCM in Europe are scarce, with many existing studies relying solely on inpatient records that do not capture the full extent of the disease burden.
This study aims to address these gaps by estimating the prevalence of HCM and oHCM on a large scale across several European countries. In addition, it will provide valuable insights into the characteristics of patients with HCM. This approach will contribute to a more accurate understanding of the true population-level prevalence of HCM in Europe, which is essential for improving diagnosis and management across diverse populations.
Research question and objectives
The general objective of this study is to characterise hypertrophic cardiomyopathy (HCM) and obstructive HCM (oHCM) in Europe in terms of prevalence, demographics, clinical measurements, comorbidities, and treatment.
MODEL DE SOL·LICITUD
2 IMP-126-CT Versió 07
The specific objectives of this study are:
1. To estimate the annual prevalence of clinically apparent HCM and oHCM in Europe, overall and stratified by age and sex.
2. To characterise patients newly diagnosed with HCM and oHCM in terms of demographics, selected HCM-related clinical measurements, and comorbidities existing before, at the time of, and after a first HCM diagnosis.
3. To describe the frequency of selected HCM-related treatments, including medications, medical devices, and procedures before, at the time of, and after a first HCM diagnosis.
Methods
Study design
The study will consist of a retrospective cohort design including patients with a first diagnosis of HCM or oHCM. We will perform a population-level descriptive epidemiology, and a patient-level characterisation study classified as “off-the-shelf” (C1) and as described in the DARWIN EU® Complete Catalogue of Standard Data Analyses. A retrospective cohort study of all HCM or oHCM cases will be conducted.
Population
The study population will include all individuals with a first diagnosis of HCM or oHCM identified in the database during the patient selection period, which is between 01/01/2010, or from when accurate data becomes available in each database (InGef 2015, NAJS 2017), and end of available data in each database.
Variables
For objective 1, diagnosis of HCM and oHCM will be identified through the diagnosis codes defined by SNOMED.
For objective 2, selected clinical measurements and comorbidities will be identified using SNOMED and LOINC codes. These include:
– Comorbidities: cardiac arrhythmias (atrial fibrillation, ventricular fibrillation, (sustained) ventricular arrythmia, premature atrial, nodal or ventricular complexes, sick sinus syndrome, atrioventricular block), sudden cardiac arrest, ischaemic stroke, , heart failure, ischaemic heart disease, sudden cardiac death, valvular heart disease, essential hypertension, disorders of lipoprotein metabolism and other lipidaemia, type 2 diabetes mellitus, obesity chronic kidney disease, chronic obstructive pulmonary disease.
– Measurements: echocardiogram (left ventricular outflow tract and left ventricular ejection fraction measurements, maximum left ventricular thickness), cardiac magnetic resonance imaging, genetic test, Holter electrocardiogram, exercise test.
For objective 3, selected HCM treatments will be identified using RxNorm and SNOMED codes. These include:
Pharmacological treatments: beta blocking agents, non-dihydropyridine calcium channel blockers (diltiazem or verapamil), dysopiramide, myosin inhibitors (mavacamten), oral diuretics, oral anticoagulants (warfarin, phenprocoumon, dabigatran, rivaroxaban, apixaban, and edoxaban), angiotensin converting enzyme inhibitors, angiotensin II receptor blockers, mineralocorticoid receptor antagonists, antiplatelets, digoxin, amiodarone.
Procedures: implantation of cardioverter defibrillator, implantation of pacemaker, septal reduction therapy (surgical septal myectomy, alcohol septal ablation), heart transplantation.
Data sources
1. Clinical Practice Research Datalink (CPRD) GOLD, United Kingdom (UK)
2. Danish Data Health Registries (DK-DHR), Denmark
3. InGef Research Database (InGef), Germany
4. Sistema d’Informació per al Desenvolupament de la Investigació en Atenció Primària (SIDIAP), Spain
5. Croatian National Public Health Information System (NAJS), Croatia
6. Norwegian Linked Health Registry data (NLHR), Norway
Sample size
No sample size has been calculated as this is a descriptive disease epidemiology study. Based on a preliminary feasibility assessment the expected number of HCM records in the included databases for this study will be approximately 80,500. For oHCM, the expected number of records is approximately 21,400.
Statistical analysis
For objective 1, we will estimate the period prevalence on an annual basis, defined as the period from January 1st to December 31st for each year. It will be calculated as the number of individuals diagnosed with HCM and oHCM divided by the total active population, with complete persistence. All estimates will be provided overall and stratified by age and sex, along with 95% confidence intervals calculated using the Wilson method.
Patient-level characterisation will be conducted for objectives 2 and 3, both overall and by grouping patients diagnosed before 2020 and those diagnosed in 2020 or later. The index date will correspond to the date of the first HCM or oHCM diagnosis for each patient.
Age and sex at time of first HCM or oHCM diagnosis will be described. The absolute number and percentage of patients receiving pre-specified list of clinical measurements and experiencing selected comorbidities will be assessed across the following non-overlapping time intervals: >5 years, 5-3 years, 3-1 years, 364-181 days, 180-91 days, 90-1 days before the index date, and during the periods 1-90 days, 91-180 days, 181-364 days, 1-3 years, 3-5 years, >5 years after the index date, with the denominator being the patients still observed at each time point.
For objective 3, the number and percentage of patients receiving each treatment from the pre-specified list of HCM treatments will be assessed across the same non-overlapping time intervals defined for objective 2.
Additionally, the number and percentage of patients receiving each measurement, experiencing each comorbidity, and taking each treatment prior to the index date will be assessed for the entire available observation period, without considering specific time intervals, in order to describe the presence of the covariates at any time before the HCM or oHCM diagnosis.
For all continuous variables, mean with standard deviation and median with interquartile range will be reported. For all categorical analyses, number and percentages will be reported. A minimum cell count of 5 will be used when reporting results, with any smaller counts reported as “<5”. All analyses will be reported by country/database, overall and stratified by age and sex when possible.
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