To Örebro University

Objectives: Electronic health records have recently been highlighted as a low-cost resource to accelerate cancer therapeutics by drug repurposing discovery (Wu et al., JCO Clinical Cancer Informatics 2019:3, 1-9). The aim of this study was to test this approach on Swedish nationwide register data focusing on breast cancer cases with distant metastasis at initial diagnosis (de novo mBC). To demonstrate the feasibility of this methodology we i) evaluated the nine drug candidates identified by Wu et al. on our dataset, ii) generated drug repurposing hypotheses based on prescription drugs given to patients during metastatic breast cancer diagnosis/treatment.

Methods: Patients diagnosed with de novo mBC between 2010 and 2020 were identified in the Swedish Cancer Register. Data on prescription drug use was collected from the National Prescribed Drug Register and survival data was collected from the National Cause of Death Register. Based on a 6-month window from diagnosis, drug repurposing candidates were evaluated using Cox proportional hazards models.

Results: A total of 2,106 de novo mBC patients were included. The nine drug candidates found by Wu et al. (Rosuvastatin, Simvastatin, Amlodipine, Tamsulosin, Metformin, Omeprazole, Warfarin, Lisinoprol and Metroprolol) were not found significant in our data. However, a total of seven other drug repurposing hy-potheses were generated, with a plausible biological rationale for at least five of them (Calcium + Vitamin D, Morphine, Furosemide, Salbutamol and Ipratropium bromide, and Fentanyl). The other two were vaginal gel and Fluoride mouthwash.

Conclusions: This study shows that the Swedish National Health Data Registers may be leveraged as a low-cost data source to detect drug repurposing signals. While results need to be interpreted with caution to not confuse causal relationships, the hypotheses generated in our study show a model for discovering noncancer drug effects on overall survival.