Modeling the Number of Attacks in Multiple Sclerosis Patients Using Zero-Inflated Negative Binomial Model

Background and aims: Multiple sclerosis (MS) is an inflammatory disease of the central nervous system. The impact of the number of attacks on the disease is undeniable. The aim of this study was to analyze the number of attacks in these patients. Methods: In this descriptive-analytical study, the registered data of 1840 MS patients referred to the MS clinic of Ayatollah Kashani hospital in Isfahan were used. The number of attacks during the treatment period was defined as the response variable, age at diagnosis, sex, employment, level of education, marital status, family history, course of disease, and expanded disability as the explanatory variables. The analysis was performed using zero-inflated negative binomial model via Bayesian framework in OpenBUGS software. Results: Age at diagnosis (CI: -0.04, -0.20), marital status (CI: -0.56, 0.002), level of education (CI: -0.81, -0.26), Job (CIHousewives vs Employee=[0.04, 0.64], CIUnemployee vs Employee=[-1.10,0.008])), and course of disease (CI: -0.51, -0.08) had a significant effect on the number of attacks. In relapsing-remitting patients, the number of attacks was partial significantly affected by expanded disability status scale (EDSS) (CI: -0.019, 0.16). Conclusion: Aging, being single (never married), high education, and not having a job decrease the number of attacks; therefore, lower age, being married, primary education, and being a housewife increase the number of attacks. An interventional or educational program is suggested in order to prevent the occurrence of further attacks in high-risk groups of patients and to increase their chances of recovery.