A new analytic tool for assessing the impact of the US Food and Drug Administration regulatory actions

• DOI: 10.1002/pds.5552
• Publication Date: 2022-11-04T15:13:08Z
• Authors: Christine Y. Lu; Laura Hou; Joy Kolonoski; Andrew B. Petrone; Fang Zhang; Catherine Corey; Ting‐Ying Huang; Marie C. Bradley
• Keywords: Concomitant; Pharmacoepidemiology; Interrupted time series

Abstract Purpose Develop and test a flexible, scalable tool using interrupted time series (ITS) analysis to assess the impact of Food Drug Administration (FDA) regulatory actions on drug use. Methods We applied in Sentinel Distributed Database FDA's 2010 safety communications (DSC) concerning long‐acting beta2‐agonists (LABA) adult asthma patients. evaluated changes LABA use by measuring initiation alone concomitant controller medications (ACM) after DSCs. The generated ITS graphs used segmented regression estimate baseline slope, level change, slope absolute relative at up two user‐specified point (s) intervention. tested compared our results against prior analyses that similar measures. Results Initiation declined among patients aged 18–45 years before FDA DSCs (−0.10% per quarter; 95%CI: −0.11% −0.09%) downward trend continued after. Concomitant ACM was stable After DSCs, there small decrease 0.006% quarter (95% CI, −0.008% −0.003%). found those 46–64 with poorly‐controlled asthma. Our were consistent previous studies, confirming performance new tool. Conclusions developed reusable real‐world databases formatted Common Data Model can