Andrew Nashed1, Shijun Zhang2, Chien-Wei Chiang2, M Zitu2, Gregory A Otterson3, Carolyn J Presley3, Kari Kendra3, Sandip H Patel3, Andrew Johns4, Mingjia Li4, Madison Grogan3, Gabrielle Lopez3, Dwight H Owen3, Lang Li2. 1. Department of Internal Medicine, The Ohio State University, A450B Starling Loving Hall Columbus, Columbus, OH, 43210, USA. Andrew.Nashed@osumc.edu. 2. Department of Biomedical Informatics and Center for Biostatistics, The Ohio State University, A450B Starling Loving Hall Columbus, Columbus, OH, 43210, USA. 3. Division of Medical Oncology, The Ohio State University, A450B Starling Loving Hall ColumbusA450B Starling Loving Hall Columbus, Columbus, OH, 43210, USA. 4. Department of Internal Medicine, The Ohio State University, A450B Starling Loving Hall Columbus, Columbus, OH, 43210, USA.
Abstract
BACKGROUND: The aim of this retrospective study was to demonstrate that irAEs, specifically gastrointestinal and pulmonary, examined through International Classification of Disease (ICD) data leads to underrepresentation of true irAEs and overrepresentation of false irAEs, thereby concluding that ICD claims data are a poor approach to electronic health record (EHR) data mining for irAEs in immunotherapy clinical research. METHODS: This retrospective analysis was conducted in 1,063 cancer patients who received ICIs between 2011 and 2017. We identified irAEs by manual review of medical records to determine the incidence of each of our endpoints, namely colitis, hepatitis, pneumonitis, other irAE, or no irAE. We then performed a secondary analysis utilizing ICD claims data alone using a broad range of symptom and disease-specific ICD codes representative of irAEs. RESULTS: 16% (n = 174/1,063) of the total study population was initially found to have either pneumonitis 3% (n = 37), colitis 7% (n = 81) or hepatitis 5% (n = 56) on manual review. Of these patients, 46% (n = 80/174) did not have ICD code evidence in the EHR reflecting their irAE. Of the total patients not found to have any irAEs during manual review, 61% (n = 459/748) of patients had ICD codes suggestive of possible irAE, yet were not identified as having an irAE during manual review. DISCUSSION: Examining gastrointestinal and pulmonary irAEs through the International Classification of Disease (ICD) data leads to underrepresentation of true irAEs and overrepresentation of false irAEs.
BACKGROUND: The aim of this retrospective study was to demonstrate that irAEs, specifically gastrointestinal and pulmonary, examined through International Classification of Disease (ICD) data leads to underrepresentation of true irAEs and overrepresentation of false irAEs, thereby concluding that ICD claims data are a poor approach to electronic health record (EHR) data mining for irAEs in immunotherapy clinical research. METHODS: This retrospective analysis was conducted in 1,063 cancerpatients who received ICIs between 2011 and 2017. We identified irAEs by manual review of medical records to determine the incidence of each of our endpoints, namely colitis, hepatitis, pneumonitis, other irAE, or no irAE. We then performed a secondary analysis utilizing ICD claims data alone using a broad range of symptom and disease-specific ICD codes representative of irAEs. RESULTS: 16% (n = 174/1,063) of the total study population was initially found to have either pneumonitis 3% (n = 37), colitis 7% (n = 81) or hepatitis 5% (n = 56) on manual review. Of these patients, 46% (n = 80/174) did not have ICD code evidence in the EHR reflecting their irAE. Of the total patients not found to have any irAEs during manual review, 61% (n = 459/748) of patients had ICD codes suggestive of possible irAE, yet were not identified as having an irAE during manual review. DISCUSSION: Examining gastrointestinal and pulmonary irAEs through the International Classification of Disease (ICD) data leads to underrepresentation of true irAEs and overrepresentation of false irAEs.
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