Systematic Identification and Description of Contemporary Real World DATA Sources Focusing on Lipoprotein(A)
Author(s)
Natani H1, Agrawal R1, Fonseca AF2, Studer R2
1Novartis Healthcare Pvt. Ltd., Hyderabad, India, 2Novartis Pharma AG, Basel, Switzerland
OBJECTIVES : To identify and summarize real-world data (RWD) sources containing data on lipoprotein(a) [Lp(a)] to create a comprehensive understanding of the breadth and depth of existing data around the cardiovascular risk factor Lp(a). METHODS : A literature review was conducted to identify publications with RWD pertaining to Lp(a) in MEDLINE and EMBASE and grey literature published from inception till November 2017. A list of unique data sources was generated and metadata was extracted to describe time and type of data collection, study design, population size, clinical characteristics, treatment, follow-up duration and outcomes, represented by 67 variables. RESULTS : Of the 2,430 retrieved publications, 202 unique data sources were identified. Half of them were from Europe (50%) followed by Asia (23%), Americas (20%), Oceania (2%), and Africa (1%); 3% were multi-regional. Most widely recorded parameters were age (97%) and sex (95%), lipid profile parameters such as HDL (91%), LDL (90%) and total cholesterol (89%). Some of the least reported parameters included drug codes (0.5%), comorbid conditions such as peripheral artery disease (0%), transient ischemic attack (0%), and coronary artery disease (0.5%). Ninety-six percent of the data sources reported less than half of the variables assessed. Ethnicity was reported in 35% of the data sources. Possibility to access these data sources was actively reported in 22% of the data sources and linking of the data sources was stated as possible with 17% of the data sources. Among the datasets that reported the creation/finalization date, 93% included data captured prior to 2010. CONCLUSIONS : This review highlights the existence of data sources containing information on Lp(a) in certain geographies, while demonstrating geographical and data gaps for many variables, providing both a base for assessment of possibilities of partnerships with existing data sources as well as the need to continue efforts to further generate data to increase the understanding around Lp(a).
Conference/Value in Health Info
2020-11, ISPOR Europe 2020, Milan, Italy
Value in Health, Volume 23, Issue S2 (December 2020)
Code
PCV102
Topic
Clinical Outcomes, Epidemiology & Public Health, Real World Data & Information Systems
Topic Subcategory
Clinical Outcomes Assessment, Distributed Data & Research Networks, Reproducibility & Replicability
Disease
Cardiovascular Disorders