| Summary: | Kimberly Page,1,2 Fares Qeadan,1,2 Clifford Qualls,2 Karla Thornton,1 Sanjeev Arora1 1Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA; 2Clinical and Translational Science Center, University of New Mexico Health Sciences Center, Albuquerque, NM, USACorrespondence: Kimberly PageDepartment of Internal Medicine, University of New Mexico Health Sciences Center, MSC10 5550, 1 University of New Mexico, Albuquerque, NM 98131, USATel +1505-272-2520Email Pagek@salud.unm.eduAbstract: Propensity score analysis is a statistical approach to reduce bias often present in non-randomized observational studies. In this paper we use this method to re-analyze data from a study that assessed whether patients receiving HCV treatment from providers in Project ECHO had different clinical outcomes than patients treated by specialists from an academic medical center (UNM HCV clinic) but in which treatment assignment was not randomized. We modeled the best estimated probability of treatment assignment, and then assess differences overall SVR and SVR in patients with genotype 1 infection by treatment arm using Stabilized Inverse Probability of Treatment Weights (SIPTW). Results show that after adjustment for SIPTW, HCV treatment outcomes were significantly better for the ECHO patients compared to the UNM HCV clinic patients. Higher proportions of patients treated by primary care providers achieved SVR and SVR with genotype 1 compared to those treated at UNM HCV clinic with 15.1% and 16.3% absolute differences, respectively. These results indicate that previously published results (showing no differences) were biased, and resulted in an underestimation of the treatment effect of ECHO on HCV treatment.Keywords: propensity scoring, ECHO, hepatitis C virus, treatment
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