Abstract
Objective: To assess the validity of a treatments- and tests-based Case-Finding Algorithm for identifying patients with non-small cell lung cancer (NSCLC) from claims databases.Data sources: Primary data from the HealthCore Integrated Research Environment (HIRE)-Oncology database and the HealthCore Integrated Research Database (HIRD) were collected between June 1, 2014, and October 31, 2015.Study design: A comparative statistical evaluation using receiver operating characteristic (ROC) curve analysis and other validity measures was used to validate the NSCLC Case-Finding Algorithm vs. a control algorithm.Data collection: Patients with lung cancer were identified based on diagnosis and pathology classifications as NSCLC or small-cell lung cancer. Records from identified patients were linked to claims data from Anthem health plans. Three-month pre-index and post-index data were included.Principal findings: The NSCLC Case-Finding Algorithm had an area under the curve (AUC) of 0.88 compared with 0.53 in the control (p < 0.0001). Promising diagnostic accuracy was observed for the NSCLC Case-Finding Algorithm based on sensitivity (94.8%), specificity (81.1%), positive predictive value (PPV) (95.3%), negative predictive value (NPV) (79.6%), accuracy (92.1%), and diagnostic odds ratio (DOR) (78.8).Conclusions: The NSCLC Case-Finding Algorithm demonstrated strong validity for distinguishing patients with NSCLC from those with SCLC in claims data records and can be used for research into NSCLC populations.
Highlights
Lung cancer is the leading cause of cancer-related deaths in both men and women, and is a heterogeneous malignancy composed of several subtypes (Siegel et al, 2017)
80– 85% of lung cancers are classified as non-small cell lung cancer (NSCLC) and the remaining 15–20% as small cell lung cancer (SCLC) (American Cancer Society, 2016)
This study used lung cancer cases identified from the HealthCore Integrated Research Environment (HIRE)-Oncology clinical database that were linked with the HealthCore Integrated Research Database (HIRD)
Summary
Lung cancer is the leading cause of cancer-related deaths in both men and women, and is a heterogeneous malignancy composed of several subtypes (Siegel et al, 2017). Case-Finding Algorithm of NSCLC Claims cancer have distinct genetic alterations and prognoses, requiring different treatment modalities to be used for NSCLC vs SCLC (NCCN NSCLC, 2017a; NCCN SCLC, 2017b) It is, important to be able to distinguish between these subtypes of lung cancer when investigating therapy options, clinical outcomes, and associated costs. Important to be able to distinguish between these subtypes of lung cancer when investigating therapy options, clinical outcomes, and associated costs Secondary data sources, such as administrative claims data, cancer registries, and electronic medical records, provide valuable information to complement results from randomized clinical trials that can be used to profile care patterns, measure patient outcomes, and estimate cancer-related costs (Schulman et al, 2013). For these databases to be considered as a reliable source of information for research studies, it is important that patients with the subtype of cancer or disease of interest can be identified correctly
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