Estimating the US pericarditis prevalence using national health encounter surveillance databases

Abstract

Objective

To obtain a nationally representative annualized estimate of the prevalence of pericarditis (inflammation of the pericardium) in the United States (US) in order to better understand the potential burden on the health care system.

Methods

Three nationally representative datasets were used to estimate the annualized period prevalence and prevalence rate of pericarditis from 2007 to 2016: the National Ambulatory Medical Care Survey (NAMCS), the National Hospital Ambulatory Medical Care Survey (NHAMCS), and the Nationwide Inpatient Sample (NIS). Across all data sources, ICD-9/10 codes were used to identify healthcare encounters with ≥1 primary or secondary diagnosis related to pericarditis irrespective of duration or etiology. The prevalence of pericarditis in 2020 was extrapolated by multiplying the average annualized prevalence rate from 2007 to 2016 by the total US population as of March 2020.

Results

Data from NAMCS/NHAMCS (2007–2016) yielded an average annualized estimate of 125,209 patients with pericarditis, resulting in a pooled average annualized prevalence estimate of 40 patients with pericarditis per 100,000 persons. Data from NIS (2007–2016) yielded an average annualized estimate of 34,441 patients with pericarditis, resulting in a pooled average annualized prevalence estimate of 11 hospitalized patients with pericarditis per 100,000 persons. Extrapolation of these results based on the March 2020 population estimates from the US Census Bureau of 329,436,928 resulted in an estimated US prevalence of pericarditis to be approximately160,000.

Conclusion

Despite certain methodologic limitations, our analysis of data from nationally representative sources support that pericarditis is a rare disease affecting substantially fewer than 200,000 persons in the US.

Keywords:

• Pericarditis
• prevalence
• national surveillance estimates
• epidemiologic data

Transparency

Declaration of funding

This work was supported by Kiniksa Pharmaceuticals Corp.

Declaration of financial/other relationships

SAL is a consultant and advisory board member for Kiniksa Pharmaceuticals Corp. and SOBI Pharmaceuticals, and a consultant for Medtronic. ML has received consulting fees from Kiniksa Pharmaceuticals, Ltd. at the time this study was conducted. MM, XH, and MZLM were employees of Kiniksa Pharmaceuticals Corp. at the time this study was conducted. MD, MSD, RC, KKS, and AM are employees of Analysis Group, Inc., which received funding from Kiniksa Pharmaceuticals Corp. to conduct this study. ALK has received research grants and served as an advisory board member for Kiniksa Pharmaceuticals, Ltd. and Sobi. A reviewer on this manuscript has disclosed that they have received research support and consultant fees from Kiniksa; another reviewer on this manuscript has disclosed that their Institution received funding from Kiniksa Pharmaceuticals, Ltd. as an investigative site and that they received only travel and accommodation for advisory committee from SOBI and Kiniksa (not grants, fees or similar). Peer reviewers on this manuscript have no other relevant financial relationships or otherwise to disclose.

Author contributions

Study design: all authors; Formal analysis: MD, MSD, RC, KKS, and AM; Data interpretation: all authors; Manuscript writing and editing: all authors.

Acknowledgements

Medical writing assistance was provided by Gloria DeWalt and Janice Imai, employees of Analysis Group, Inc. Financial support for medical writing was provided by Kiniksa Pharmaceuticals Corp.

Ethics statement

Ethics board review was not applicable to this study.