(23) Prevalence and Clinical Burden of Genetic Dilated Cardiomyopathy in The United States: Results from The Optum® Electronic Health Records Database

Friday, August 26, 2022

8:00 AM – 6:00 PM CEST

Location: Hall C

Publication Number: 354

Presenting Author(s)

Scott P. Kelly, PhD
– Senior Director, Global Medical Epidemiology , Pfizer Inc, New York, New York, United States

Co-Author(s)

Yaa Ababio
– Pfizer, Inc. Worldwide Medical and Safety, New York, New York, United States
Robert Moccia, MD, PhD
– Pfizer, Inc., Cambridge, MA, USA, United States
Franca S. Angeli, MD, PhD
– Pfizer, Inc., New York, NY, USA, United States
Joanne Berghout, PhD
– Pfizer, Inc., Cambridge, MA, USA, United States
Kui Huang, PhD
– Pfizer Inc, New York, New York, United States
Kathy Liu, PhD
– Pfizer, Inc., Collegeville, PA, USA, Collegeville, PA, United States
Sara Burns, MS
– Panalgo, Boston, MA, USA, Boston, MA, United States
Cynthia Senerchia, RN, MS
– Vice President, Data Management and Analytics, Optum® Digital Research Network, Boston, MA, USA, Westwood, MA, United States
Gabriel C. Brooks, MD, MAS, FACC
– Pfizer, Inc., Cambridge, MA, USA, United States

Background: Non-ischemic idiopathic dilated cardiomyopathy (DCM) is considered a significant contributor to heart failure. However, data supporting the epidemiological burden of this potentially genetic disease in the United States (US) is sparse. This study sought to estimate the period prevalence of DCM and the proportion of idiopathic DCM in the US using a large, diverse population from electronic health records (EHR).

Objectives: To estimate the period prevalence and clinical burden of DCM and idiopathic DCM in the United States (US) using a large, diverse population from electronic health records (EHR).

Methods: This retrospective, observational study included 56,812,806 deidentified patients in Optum® EHR between 2017 and 2019. Suspected DCM cases were identified using ICD-10 coding. Using deidentified notes and unstructured data, 1,000 randomly selected DCM cases underwent manual clinical review and validation to determine those that were DCM and idiopathic DCM. The period prevalence and clinical burden of DCM and idiopathic DCM were estimated.

Results: Manual clinical review yielded a positive predictive value (PPV) of DCM of 92.5% and an idiopathic DCM proportion of 46.3%. Using the PPV of DCM, the period prevalence of DCM between 2017-2019 was 118.33 per 100,000. Prevalence was increased for adults ≥ 65 years of age, males, and African Americans. Extrapolation to the US population led to an overall estimated prevalence of roughly 388,350 patients as of 2019. Applying the proportion of cases with idiopathic DCM to the previous estimates yielded an idiopathic DCM period prevalence estimate of 59.23 per 100,000 with an estimated US clinical burden of roughly 194,385 patients. Evidence of actual genetic testing in this population was scarce, with less than 0.43% of DCM cases reporting genetic testing during the study period.

Conclusions: This study establishes a period prevalence estimate for DCM and idiopathic DCM by utilizing a conservative case definition. We also observe very low uptake of molecular genetic testing in DCM clinical care. These findings suggest that the clinical burden of genetic DCM may be underestimated.