Predictors of survival in systemic lupus erythematosus.
We conducted the current study to determine the impact of demographic factors, household income, clinical manifestations, disease activity, serologic tests, and calendar year on survival among patients with systemic lupus erythematosus (SLE). In a large prospective cohort of patients with SLE, we used the Kaplan-Meier method to estimate survival probabilities of SLE patients over time since diagnosis. We analyzed the predictors of survival in SLE using Cox proportional hazards models.The study included 1378 patients with SLE, with a median follow-up in the cohort of 6.1 years. One hundred eighteen patients died (8.6%). The overall cumulative probability of survival after disease diagnosis at 5, 10, 15, and 20 years was 95%, 91%, 85%, and 78%, respectively. Based on a multivariable model, age at SLE diagnosis >or=50 years old (hazard ratio [HR]=5.9; p<.001) and male gender (HR=2.4; p=.004) were associated with poorer survival. Patients with annual family income<25,000 dollars had poorer survival (HR=1.7; p=.040). The presence of hemolytic anemia in the first year after disease diagnosis (p=.016) or during the follow-up period (p=.031) increased the risk of death. A low complement level during the first year after diagnosis was the only serologic marker of poorer survival (p=.013 for low C3 level and p=.053 for low C4 level).
Kasitanon
Nuntana
N
From Division of Rheumatology (NK, MP), Department of Medicine, Johns Hopkins University School of Medicine, Baltimore; and Department of Epidemiology and Preventive Medicine (LSM), University of Maryland School of Medicine, Baltimore, Maryland.
Magder
Laurence S
LS
Petri
Michelle
M
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D002648:Child; D002675:Child, Preschool; D003710:Demography; D005260:Female; D006801:Humans; D008180:Lupus Erythematosus, Systemic / Q000401:mortality* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D016016:Proportional Hazards Models; D011446:Prospective Studies; D018570:Risk Assessment; D012737:Sex Factors; D012959:Socioeconomic Factors; D016019:Survival Analysis; D013997:Time Factors; D014481:United States / Q000453:epidemiology