Detecting adverse reaction signals to statins in a Chinese regional healthcare database, using a tree-based scan statistic method

Healthcare databases offer complementary data for drug safety signal detection, addressing the limitations of spontaneous reporting. We applied the tree-based scan statistic (TreeScan) to detect adverse effect signals to statin therapy, using 2010–2016 data from the Yinzhou regional healthcare database. Patients (> 18 years) with hypertension were included, and identified as statin users according to their out-/inpatient prescription records. Adverse events (AEs) were defined per ICD‐10 codes from participants’ diagnosis records. We detected the safety signals of statins using the TreeScan method and established a set of reference signals according to these ICD‐10 codes. The signal gold standard was constructed from published meta-analyses, systematic reviews, and statin package inserts. Diagnostic test measures—sensitivity, specificity, and positive predictive value, among others—were computed. In total, 224,187 patients were enrolled and classified as either statin users (85,758) or nonusers (138,429). A reference set of 126 ICD‐10-derived AEs, including 13 positive and 113 negative signals, was constructed; TreeScan generated 30 positive signals (p < 0.05), 9 of which were known AEs. Hence, TreeScan can be applied as a drug safety surveillance, signal detection method, simultaneously evaluating several potential AEs. It can further adjust for the multiple testing inherent in evaluating overlapping groups.