Validation of a Case-Finding Algorithm for Identifying Patients with Non-small Cell Lung Cancer (NSCLC) in Administrative Claims Databases

Objective. To assess the validity of the non-small cell lung cancer (NSCLC)a treatments- and tests-based Case-Finding Algorithm to identify for identifying patients with non-small cell lung cancer (NSCLC) from claims databases. Data sources. Primary data from the HealthCore Integrated Research Environment-Oncology database and the HealthCore Integrated Research dDatabase were collected between June 1, 2014, and October 31, 2015. Study design. A comparative statistical evaluation using receiver operating characteristic curve analysis and other validity measures was used to validate the NSCLC Case-Finding Algorithm versus a control algorithm. Data collection. Patients with Llung cancer patients were identified based on diagnosis and pathology classifications as NSCLC or small -cell lung cancer. Records from iIdentified 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 of 0.880 compared with 0.530 in the control (p<.0001). Promising diagnostic accuracy was observed for the NSCLC Case-Finding Algorithm based on sensitivity (94.8%), specificity (81.1%), positive predictive value (95.3%), negative predictive value (79.6%), accuracy (92.1%), (0.75), and diagnostic odds ratio (78.8). Conclusions. The NSCLC Case-Finding Algorithm demonstrated good statistical propertiesstrong validity for for identifying distinguishing patients with NSCLC patients from those with SCLC in claims data records and can be used for research into NSCLC when clinical/pathological data are not availablepopulations.