Incidência e prevalência de esclerose sistêmica em Campo Grande, Estado de Mato Grosso do Sul, Brasil

Abstract

Introduction

Systemic sclerosis (SSc) is an autoimmune disease which shows extreme heterogeneity in its clinical presentation and that follows a variable and unpredictable course. Although some discrepancies in the incidence and prevalence rates between geographical regions may reflect methodological differences in the definition and verification of cases, they may also reflect true local differences.

Objectives

To determine the prevalence and incidence of SSc in the city of Campo Grande, state capital of Mato Grosso do Sul (MS), Brazil, during the period from January to December 2014.

Methods

All health care services of the city of Campo Grande ‐ MS with attending in the specialty of Rheumatology were invited to participate in the study through a standardized form of clinical and socio‐demographic assessment. Physicians of any specialty could report a suspected case of SSc, but necessarily the definitive diagnosis should be established by a rheumatologist, in order to warrant the standardization of diagnostic criteria and exclusion of other diseases resembling SSc. At the end of the study, 15 rheumatologists reported that they attended patients with SSc and sent the completed forms containing epidemiological data of patients.

Results

The incidence rate of SSc in Campo Grande for the year 2014 was 11.9 per million inhabitants and the prevalence rate was 105.6 per million inhabitants. SSc patients were mostly women, white, with a mean age of 50.58 years, showing the limited form of the disease with a mean duration of the disease of 8.19 years. Regarding laboratory tests, 94.4% were positive for ANA, 41.6% for ACA and 19.1% for anti‐Scl70; anti‐RNA Polymerase III was performed in 37 patients, with 16.2% positive.

Conclusions

The city of Campo Grande, the state capital of MS, presented a lower incidence/prevalence of SSc in comparison with those numbers found in US studies and close to European studies’ data.