This phenotype specification supports the identification of patients with lung and gastroenteropancreatic (GEP) neuroendocrine tumors (NETs) for the Neuroendocrine Tumors- Patient-Reported Outcomes Study (NET-PRO) - a multi-site, patient-centered outcomes research initiative (PCORI) funded study (RD-2020C2-20329) conducted within PCORnet. The document outlines multiple computable phenotypes tailored to different recruitment strategies, including a low-touch (high positive predictive value) phenotype for low-touch recruitment (e.g., by email/mail without chart review), and a first-pass (high sensitivity phenotype) for use when eligibility can be confirmed through clinical chart review or in-person recruitment. It also includes a tumor registry-based phenotype for validated case identification using structured oncology data. These phenotypes are designed to leverage the PCORnet Common Data Model (CDM), institutional clinical data warehouses, and tumor registries to maximize accurate and efficient patient identification across diverse healthcare systems.
Computable Phenotypes for Identifying Patients with Lung and Gastroenteropancreatic Neuroendocrine Tumors in PCORnet
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McDowell Bradley D, O'Rorke Michael M, Gryzlak Brian M, DeCook Rhonda R, Xu Tao, Dillon Joseph, Chrischilles Elizabeth A: on behalf of the NET-PRO study Investigators.. University of Iowa. Computable Phenotypes for Identifying Patients with Lung and Gastroenteropancreatic Neuroendocrine Tumors in PCORnet. PheKB; 2025 Available from: https://phekb.org/phenotype/1736