Clinical and genetic factors predictive of mortality in early systemic sclerosis
Article first published online: 29 SEP 2009
Copyright © 2009 by the American College of Rheumatology
Arthritis Care & Research
Volume 61, Issue 10, pages 1403–1411, 15 October 2009
How to Cite
Assassi, S., del Junco, D., Sutter, K., McNearney, T. A., Reveille, J. D., Karnavas, A., Gourh, P., Estrada-Y-Martin, R. M., Fischbach, M., Arnett, F. C. and Mayes, M. D. (2009), Clinical and genetic factors predictive of mortality in early systemic sclerosis. Arthritis & Rheumatism, 61: 1403–1411. doi: 10.1002/art.24734
- Issue published online: 29 SEP 2009
- Article first published online: 29 SEP 2009
- Manuscript Accepted: 28 MAY 2009
- Manuscript Received: 15 JAN 2009
- NIH Specialized Center of Research grant in scleroderma. Grant Number: P50-AR44888
- NIH Centers for Research Translation. Grant Number: P50-AR054144
- University Clinic Research Center grants from the University of Texas Medical Branch
- University of Texas at San Antonio. Grant Numbers: M01-RR00073, M01-RR01346
- NIH Clinical and Translational Sciences award. Grant Number: 1U54-RR23417-01
- American College of Rheumatology Clinical Investigator fellowship award
To investigate the clinical and genetic variables at initial presentation that predict survival in the Genetics versus Environment in Scleroderma Outcome Study (GENISOS) cohort.
GENISOS is a prospective, observational study of a multiethnic early systemic sclerosis (SSc) cohort. To date, a total of 250 patients have been enrolled. In addition to clinical and laboratory data, electrocardiograms (EKGs), chest radiographs, and pulmonary function tests have been obtained from each patient. A modified Rodnan skin thickness score, HLA class II genotyping, and a Medsger Damage Index also have been collected. We performed multivariable analyses utilizing the Cox regression following a purposeful model building strategy.
The study analyzed 122 white, 47 African American, and 71 Hispanic SSc patients with an average disease duration of 2.6 years at enrollment. At the time of analysis, 52 (20.8%) of the 250 patients had died. In the final multivariable model excluding HLA genes, 7 variables emerged as significant predictors of mortality: age ≥65 years at enrollment, forced vital capacity <50% predicted, clinically significant arrhythmia on EKG, absence of anticentromere antibodies, hypertension, chest radiograph suggestive of pulmonary fibrosis, and low body mass index (BMI). In separate modeling that included HLA genes, HLA alleles DRB1*0802 and DQA1*0501 were significant predictors of mortality in addition to the predictors mentioned above.
A limited number of variables collected at presentation, including BMI, are able to predict mortality in patients with early SSc. In addition, some of the HLA genes associated with SSc susceptibility are useful for predicting SSc outcome.