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

Abstract

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