People with high levels of cholesterol, and particularly low-density cholesterol (LDL-C), are known to be at an increased risk of having cardiovascular events such as heart attacks and strokes. Guidelines recommend that people with high LDL-C, especially those with other risk factors for cardiovascular events, are targeted for LDL-C reduction partly through treatment with drugs such as statins. Even with existing therapy, some patients fail to reduce LDL-C either because they cannot tolerate the drugs or else the drugs are ineffective. .A new therapy known as inclisiran may be effective at treating these people who do not respond well to existing therapy. In this study we wish to use the Clinical Practice Research Datalink to select three groups of patients at risk of cardiovascular event who also have evidence of high LDL-C levels. These groups are i) those who have already had a cardiovascular event ii) those who have other risk factors associated with cardiovascular events and iii) those with familial hypercholesterolemia; a condition where the patient has very high LDL-C levels which are difficult to reduce with current treatments. We then wish to determine how many new cases of these conditions occur each year (incidence), how many patients are in these groups (prevalence), what current treatments these people take and their LDL-C levels and other biochemistry, the rates of cardiovascular events that these people have and the cost of treating these people. This will help in providing information about the population that could benefit from new treatments including inclisiran.
Elevated levels of low density lipoprotein cholesterol (LDL-C) are associated with cardiovascular risk. Reducing LDL-C with lipid-lowering therapies may halt the progression of atherosclerotic plaque and reduce the incidence of cardiovascular events. However, a significant proportion of patients with elevated LDL-C are intolerant, contraindicated or refractory to existing treatments. In clinical trials, inclisiran has shown efficacy in reducing LDL-C. This retrospective, descriptive study aims to use the Clinical Practice Research Datalink to select three cohorts that may benefit from inclisiran: i) atherosclerotic cardiovascular disease (ASCVD), ii) ASCVD-risk equivalent (based on presence of Type 2 diabetes, familial hypercholesterolemia or a baseline Framingham risk score indicative of ≥20% risk of 10-year cardiovascular event), iii) familial hypercholesterolemia. From these pools, those with evidence of hypercholesterolemia based on diagnosis, LDL-C test or prescription of lipid-lowering therapy will form the study cohorts. Index date will be date of first occurrence of a contributory diagnosis or biochemical marker in the study identification period (01/01/2016-31/12/19 for the primary incidence analysis). Cohorts will also be stratified by demographic characteristics, baseline therapy, LDL-C control and statin intolerance. The primary objective is to describe the incidence of these conditions. Secondary objectives are to describe i) prevalence ii) demographics, clinical characteristics and baseline biochemistry lipid lowering regimens iii) incidence of subsequent hospitalisations, mortality, myocardial infarction and stroke and iv) resource use and associated costs. A model will be constructed to predict high-cost patients defined by the upper decile. Linked data from the Hospital Episode Statistics admitted patient care, outpatient and accident and emergency datasets will be used to ascertain exposures and descriptive disease and surgical outcomes and resource use and costs. Office of National Statistics mortality data will provide cardiovascular and mortality outcomes. Index of multiple deprivation data will provide baseline characteristics and as a predictor in the model.
Incidence, prevalence, baseline characteristics; incidence of cardiovascular events; cardiovascular mortality;all-cause mortality healthcare utilisation, costs,
Christopher Morgan - Chief Investigator - Pharmatelligence Limited t/a Human Data Sciences
Christopher Morgan - Corresponding Applicant - Pharmatelligence Limited t/a Human Data Sciences
- Collaborator -
Raquel Lahoz - Collaborator - NOVARTIS
Thomas Berni - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation