Screening for idiopathic pulmonary fibrosis using comorbidity signatures in electronic health records.

Autor: Onishchenko D; Department of Medicine, University of Chicago, Chicago, IL, USA., Marlowe RJ; Spencer-Fontayne Corporation, Jersey City, NJ, USA., Ngufor CG; Mayo Clinic College of Medicine and Science, Rochester, MN, USA., Faust LJ; Mayo Clinic College of Medicine and Science, Rochester, MN, USA., Limper AH; Mayo Clinic College of Medicine and Science, Rochester, MN, USA.; Director, Thoracic Research Unit, Mayo Clinic College of Medicine and Science, Rochester, MN, USA., Hunninghake GM; Director, Interstitial Lung Disease Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA., Martinez FJ; Bruce Webster Professor of Internal Medicine, Medicine, Weill Cornell Medical College, New York, NY, USA.; Chief of Division of Pulmonary and Critical Care Medicine at Weill Cornell Medicine and NewYork-Presbyterian Weill Cornell Medical Center, New York, NY, USA., Chattopadhyay I; Department of Medicine, University of Chicago, Chicago, IL, USA. ishanu@uchicago.edu.; Committee on Genetics, Genomics & Systems Biology, University of Chicago, Chicago, IL, USA. ishanu@uchicago.edu.; Committee on Quantitative Methods in Social, Behavioral, and Health Sciences, University of Chicago, Chicago, IL, USA. ishanu@uchicago.edu.
Jazyk: angličtina
Zdroj: Nature medicine [Nat Med] 2022 Oct; Vol. 28 (10), pp. 2107-2116. Date of Electronic Publication: 2022 Sep 29.
DOI: 10.1038/s41591-022-02010-y
Abstrakt: Idiopathic pulmonary fibrosis (IPF) is a lethal fibrosing interstitial lung disease with a mean survival time of less than 5 years. Nonspecific presentation, a lack of effective early screening tools, unclear pathobiology of early-stage IPF and the need for invasive and expensive procedures for diagnostic confirmation hinder early diagnosis. In this study, we introduce a new screening tool for IPF in primary care settings that requires no new laboratory tests and does not require recognition of early symptoms. Using subtle comorbidity signatures identified from the history of medical encounters of individuals, we developed an algorithm, called the zero-burden comorbidity risk score for IPF (ZCoR-IPF), to predict the future risk of an IPF diagnosis. ZCoR-IPF was trained on a national insurance claims database and validated on three independent databases, comprising a total of 2,983,215 participants, with 54,247 positive cases. The algorithm achieved positive likelihood ratios greater than 30 at a specificity of 0.99 across different cohorts, for both sexes, and for participants with different risk states and history of confounding diseases. The area under the receiver-operating characteristic curve for ZCoR-IPF in predicting IPF exceeded 0.88 and was approximately 0.84 at 1 and 4 years before a conventional diagnosis, respectively. Thus, if adopted, ZCoR-IPF can potentially enable earlier diagnosis of IPF and improve outcomes of disease-modifying therapies and other interventions.
(© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Databáze: MEDLINE
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