{
  "abstract": "Introduction Cardiovascular (CV) disease is the leading cause of morbidity and mortality globally. Low-density lipoprotein cholesterol (LDL-C) is an important modifiable risk factor of major adverse cardiovascular events. Patients without prior myocardial infarction (MI) or stroke but with established risk factors and elevated LDL-C may benefit from intensive lipid-lowering therapy (LLT); however, the size and potential healthcare burden of this population globally are not known. The benefits of evolocumab, a proprotein convertase subtilisin/kexin type 9 inhibitor, in these patients, are currently being studied in the phase 3 Effect of Evolocumab in Patients at High Cardiovascular Risk Without Prior Myocardial Infarction or Stroke (VESALIUS-CV) trial. To characterise the high-risk pre–CV-event (VESALIUS-CV–like) individuals in the real world, an observational study is being conducted across multiple countries.Methods and analysis This retrospective cohort study will use a common protocol and an analytical common data model approach to characterise VESALIUS-CV–like individuals in the real world across different geographical regions and healthcare settings. The study period will be from 2010 to 2022, subject to data availability in study sites. Patients aged 50 years and older at high risk of CV disease but without prior MI or stroke will be included in this study. VESALIUS-CV–like individuals are defined through a combination of the following: (1) one diagnosis of coronary artery disease, cerebrovascular disease, peripheral artery disease or diabetes with microvascular complications or chronic insulin use; (2) an elevated LDL-C measurement and (3) other high-risk factors. The objectives of this study are to estimate the prevalence of VESALIUS-CV–like individuals, describe their characteristics and care pathways and estimate their incidence rates of CV events and healthcare costs. The prevalence of VESALIUS-CV–like individuals will be expressed as annual prevalence; patient characteristics at index date will be presented using summary statistics; care pathways will be summarised as LLT prescription across time; and the incidence of defined CV events will be expressed as events per person-years as well as at certain time periods. Healthcare costs will be presented as CV-related costs in different time periods.Ethics and dissemination Approvals of the study protocol were obtained from relevant local ethics and regulatory frameworks for each participating database. The results of the study will be submitted to peer-reviewed scientific publications and presented at scientific conferences.",
  "authors": [
    {
      "affiliations": [
        "Center for Observational Research, Amgen Ltd, Uxbridge, UK"
      ],
      "name": "Andreas Ochs"
    },
    {
      "affiliations": [
        "Center for Observational Research, Amgen Ltd, Uxbridge, UK"
      ],
      "name": "Queenie Chan"
    },
    {
      "affiliations": [
        "Center for Observational Research, Amgen Inc, Thousand Oaks, California, USA"
      ],
      "name": "Nafeesa N Dhalwani"
    },
    {
      "affiliations": [
        "Center for Observational Research, Amgen Ltd, Uxbridge, UK"
      ],
      "name": "Michael Duxbury"
    },
    {
      "affiliations": [
        "Center for Observational Research, Amgen Inc, Thousand Oaks, California, USA"
      ],
      "name": "Erin Shannon"
    },
    {
      "affiliations": [
        "Center for Observational Research, Amgen Ltd, Uxbridge, UK"
      ],
      "name": "James O’Kelly"
    },
    {
      "affiliations": [
        "Global Development, Amgen Inc, Thousand Oaks, California, USA"
      ],
      "name": "Gabriel Paiva da Silva Lima"
    },
    {
      "affiliations": [
        "Global Development, Amgen Inc, Thousand Oaks, California, USA"
      ],
      "name": "Suna Avcil"
    },
    {
      "affiliations": [
        "Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China"
      ],
      "name": "Adrienne YL Chan"
    },
    {
      "affiliations": [
        "Laboratory of Data Discovery for Health (D24H), Hong Kong Science and Technology Park, Sha Tin, Hong Kong SAR, China",
        "School of Nursing, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China",
        "Advanced Data Analytics for Medical Science (ADAMS) Limited, Hong Kong SAR, China"
      ],
      "name": "Celine SL Chui"
    },
    {
      "affiliations": [
        "Institute of Clinical Pharmacy and Pharmaceutical Sciences, National Cheng Kung University, Taiwan, Taiwan",
        "Population Health Data Center, National Cheng Kung University, Tainan, Taiwan"
      ],
      "name": "Edward Chia-Cheng Lai"
    },
    {
      "affiliations": [
        "Sence Research, Uppsala, Sweden"
      ],
      "name": "Thomas Cars"
    },
    {
      "affiliations": [
        "School of Pharmacy, Sungkyunkwan University—Suwon Campus, Suwon, Gyeonggi-do, Republic of Korea"
      ],
      "name": "Ju-Young (Judy) Shin"
    },
    {
      "affiliations": [
        "PHARMO Institute, Utrecht, The Netherlands"
      ],
      "name": "Edith M Heintjes"
    },
    {
      "affiliations": [
        "Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China",
        "Advanced Data Analytics for Medical Science (ADAMS) Limited, Hong Kong SAR, China",
        "Aston Pharmacy School, Aston University, Birmingham, UK"
      ],
      "name": "Ian CK Wong"
    }
  ],
  "title": "Characterisation of a clinical trial–like population of high cardiovascular risk patients prior to myocardial infarction or stroke in the real world: design and protocol for a multidatabase retrospective cohort study",
  "uid": "4dc036d0-8769-5166-b75e-69e0fc0ef078"
}