PREDICTORS OF SURVIVAL IN SYSTEMIC-SCLEROSIS (SCLERODERMA)

We conducted followup of 264 patients with definite systemic sclerosis (SSc) who were entered into the multicenter Scleroderma Criteria Cooperative Study (SCCS) during 1973-1977. At the end of the study (average 5.2 years of followup), 38% were known to be alive, 50% were dead (68% of these deaths definitely related to SSc), and 12% were lost to followup. Survival analyses of 484 demographic, clinical, and laboratory items recorded at entry into the SCCS (within 2 years of physician diagnosis of SSc) were performed. Survival declined linearly, and the cumulative survival rate was < 80% at 2 years, 50% at 8.5 years, and 30% at 12 years after entry. Analysis using combinations of entry variables identifying organ system involvement confirmed that renal, cardiac, pulmonary, and gastrointestinal involvement in SSc predicted reduced survival; however, data on organ system involvement at study entry could not be used to consistently predict which organ system would ultimately be involved as the primary cause of death. By survival tree analysis, the individual entry variables best predicting reduced survival included older age (> 64 years), reduced renal function (blood urea nitrogen > 16 mg/dl), anemia (hemoglobin less-than-or-equal-to 11 gm/dl), reduced pulmonary diffusing capacity for carbon monoxide (less-than-or-equal-to 50% of predicted), reduced total serum protein level (less-than-or-equal-to 6 gm/dl), and reduced pulmonary reserve (forced vital capacity < 80% with hemoglobin > 14 gm/dl or forced vital capacity < 65% with hemoglobin less-than-or-equal-to 14 gm/dl). Cox proportional hazards model analysis confirmed these results. Different combinations of variables led to markedly different survival rates. The poorest prospects for survival were in patients with SSc who were less-than-or-equal-to 64 years old with a hemoglobin level less-than-or-equal-to 11 gm/dl, and in those > 64 years old with a blood urea nitrogen level > 16 mg/dl. These results may be useful in predicting individual patients at risk for shortened survival.