eTable 1. Categorization of Immunosuppressive Drugs Included in Search
eTable 2. Diagnosis Categorizations by CCSR ICD-10 Groupings
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Wallace BI, Kenney B, Malani PN, Clauw DJ, Nallamothu BK, Waljee AK. Prevalence of Immunosuppressive Drug Use Among Commercially Insured US Adults, 2018-2019. JAMA Netw Open. 2021;4(5):e214920. doi:10.1001/jamanetworkopen.2021.4920
The use of immunosuppressive drugs is a potential risk factor for infectious disease, including COVID-19 illness.1 For instance, although dexamethasone improves survival among patients with severe COVID-19 infections,2 long-term glucocorticoid use may increase the risk of hospitalization among patients who contract COVID-19.3 A prior study relying on patient self-report estimated that 2.7% of US adults were immunosuppressed in 2013, but the study did not explore features associated with use of immunosuppressive medications.4 In this cross-sectional study, we used direct pharmaceutical claims to describe the contemporary prevalence of drug-induced immunosuppression in a large cohort of US adults.
Deidentified data from Clinformatics Data Mart (Optum, Inc), a national commercial claims database, were used in this cross-sectional study. Adults aged 18 through 64 years who had continuous commercial medical insurance coverage from January 1, 2017, through December 31, 2019, were included. We used 2017 data to establish baseline comorbid conditions; 2018 and 2019 data were used to determine drug-induced immunosuppression. We defined drug-induced immunosuppression as use of any of the following regimens in a 365-day period: (1) 1 dose or more of an antineoplastic immunosuppressive drug; (2) 30 days or more of oral glucocorticoids; (3) 90 days of any other oral or subcutaneous immunosuppressive drug; or (4) 2 doses of intravenous, noncorticosteroid immunosuppressive drugs. We excluded single-dose intravenous corticosteroids, which are often used as premedication for infusions. We classified immunosuppressive drugs into 6 categories as follows: oral corticosteroids, methotrexate, other disease-modifying antirheumatic drugs and transplant antirejection medications, tumor necrosis factor inhibitors, antineoplastic agents, and other biological product medications and Janus kinase inhibitors (eTable 1 in the Supplement). We used Agency for Healthcare Research and Quality Clinical Classifications Software Refined (CCSR) to group International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis codes for common medical conditions associated with drug-induced immunosuppression and common primary diagnoses (eTable 2 in the Supplement). This study was granted exempt status, including a waiver of informed patient consent for use of deidentified secondary data, by the University of Michigan Institutional Review Board. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cross-sectional studies.
Of the 3 169 441 continuously enrolled patients, 89 925 (2.8%) met the criteria for drug-induced immunosuppression during the period January 1, 2018, through December 31, 2019. Table 1 shows baseline patient characteristics. Most recipients of immunosuppressive drugs were older (median age, 53 years; interquartile range, 50-59 years), and women (55 043 [61.2%]).The most commonly prescribed immunosuppressive drugs were prednisone (47 649 patients [53.0%]), methotrexate (22 013 [24.5%]), and methylprednisolone (19 405 [21.6%]), which together were used by 62.5% of patients (Table 2). Oral corticosteroids were received by 67.7% of patients, and 40.9% received oral corticosteroids for 30 days or longer in a 365-day period. The 3 most common immunosuppression-associated diagnosis categories were malignant neoplasms (73.8%), immune-mediated conditions (68.8%), and inflammatory skin conditions (38.8%). After excluding 1 primary diagnosis category that was too general to provide useful diagnostic classification (FAC014, “medical examination/evaluation”), the 3 most common primary diagnosis categories were “neoplasm-related encounters” (51.8%), “exposure, encounters, screening, or contact with infectious disease” (50.6%), and “musculoskeletal findings, not low back pain” (48.3%).
In a national cohort of insured adults, more than 80 000 patients (2.8%) experienced drug-induced immunosuppression during the study period. Approximately two-thirds of patients (67.7%) received oral corticosteroids, and nearly half (40.9%) used oral corticosteroids for 30 days or longer. Common primary diagnoses in the study population included conditions often associated with corticosteroid use (eg, infections) and conditions for which corticosteroids are often prescribed despite limited evidence of benefit (eg, musculoskeletal pain, respiratory ailments).5 Limitations of this study include the uncertainty regarding the exact drugs prescribed for a given condition, dual indications for certain drugs (eg, methotrexate, cyclophosphamide), incomplete capture of inpatient medications, imperfect generalizability of commercial claims data, lack of corticosteroid dose information, and lack of modeling to demonstrate associations.
These findings are noteworthy given evolving evidence that long-term glucocorticoid use may increase the risk of COVID-19–related hospitalization.3 Steroid-sparing immunosuppressants may present an alternative to long-term corticosteroid use, but limited data exist regarding how these treatments affect the risk of hospitalization for COVID-19.3 While the possibility of an association is being clarified, clinicians should adhere to principles of corticosteroid stewardship by avoiding unnecessary corticosteroid prescribing when possible; carefully discussing the risks, benefits, and available treatment alternatives with patients; using the lowest drug dose and shortest duration appropriate for the condition; and advocating for public health measures.6
Accepted for Publication: February 15, 2021.
Published: May 20, 2021. doi:10.1001/jamanetworkopen.2021.4920
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Wallace BI et al. JAMA Network Open.
Corresponding Author: Beth I. Wallace, MD, MSc, Department of Internal Medicine, University of Michigan Medical School, Ste 7C27, North Ingalls Bldg, 300 N Ingalls St, SPC 5422, Ann Arbor, MI 48109-5422 (firstname.lastname@example.org).
Author Contributions: Dr Waljee had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Wallace, Nallamothu, Waljee.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Wallace, Waljee.
Critical revision of the manuscript for important intellectual content: Kenney, Malani, Clauw, Nallamothu, Waljee.
Statistical analysis: Kenney.
Administrative, technical, or material support: Malani, Clauw.
Supervision: Clauw, Waljee.
Conflict of Interest Disclosures: Dr Clauw reported receiving grants from Aptinyx Inc and Lundbeck and personal fees from Tonix Pharmaceuticals, Innovative Med Concepts, and Samumed outside the submitted work. Dr Nallamothu reported being a principal investigator or coinvestigator on research grants from the National Institutes of Health, Veterans Affairs Health Service and Research and Development, and the American Heart Association. He also reported receiving compensation, as editor-in-chief of Circulation: Cardiovascular Quality & Outcomes, a journal of the American Heart Association. He is listed as a coinventor on US utility patent No. US 9,962,124, as well as a provisional patent application (No. 54423) that used software technology with signal processing and machine learning to automate the reading of coronary angiograms, held by the University of Michigan and licensed to AngioInsight, Inc, in which Dr Nallamothu holds ownership shares and receives consultancy fees. The University of Michigan also has filed patents on his behalf related to the use of computer vision for imaging applications in gastroenterology, with technology elements licensed to Applied Morphomics, Inc, in which he has no relationship or stake. No other disclosures were reported.
Funding/Support: Dr Wallace was supported by grant 5KL2TR002241-04 from the National Center for Advancing Translational Sciences, National Institutes of Health during the preparation of this article.
Role of the Funder/Sponsor: The funding organization had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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