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 less than 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 (greater than 64 years), reduced renal function (blood urea nitrogen greater than 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 less than 80% with hemoglobin greater than 14 gm/dl or forced vital capacity less than 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 greater than 64 years old with a blood urea nitrogen level greater than 16 mg/dl. These results may be useful in predicting individual patients at risk for shortened survival.