Treatment Patterns for Chronic Comorbid Conditions in Patients With Cancer Using a Large-Scale Observational Data Network.

JCO Clinical Cancer Informatics
Ruijun ChenGeorge Hripcsak

Abstract

Patients with cancer are predisposed to developing chronic, comorbid conditions that affect prognosis, quality of life, and mortality. While treatment guidelines and care variations for these comorbidities have been described for the general noncancer population, less is known about real-world treatment patterns in patients with cancer. We sought to characterize the prevalence and distribution of initial treatment patterns across a large-scale data network for depression, hypertension, and type II diabetes mellitus (T2DM) among patients with cancer. We used the Observational Health Data Sciences and Informatics network, an international collaborative implementing the Observational Medical Outcomes Partnership Common Data Model to standardize more than 2 billion patient records. For this study, we used 8 databases across 3 countries-the United States, France, and Germany-with 295,529,655 patient records. We identified patients with cancer using SNOMED (Systematized Nomenclature of Medicine) codes validated via manual review. We then characterized the treatment patterns of these patients initiating treatment of depression, hypertension, or T2DM with persistent treatment and at least 365 days of observation. Across databases, wide...Continue Reading

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Citations

May 28, 2021·JCO Clinical Cancer Informatics·Jennifer L Caswell-JinAllison W Kurian
Aug 14, 2021·BMC Medical Informatics and Decision Making·Felix Nikolaus WirthFabian Prasser

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