Severe restrictive lung disease in systemic sclerosis

Abstract

Objective: We sought to identify risk factors for developing severe restrictive lung disease and to determine the time of onset and rate of progression in patients with systemic sclerosis (SSc).

Methods: Using the University of Pittsburgh Scleroderma Databank, we grouped patients according to their lowest forced vital capacity (FVC) value: > 75% predicted, 50-75% predicted, and < 50% predicted. In patients with severe restrictive disease, we examined serial pulmonary function test (PFT) results to determine the rate of loss of lung volume over time.

Results: Of 890 SSc patients, 60% (n = 531) never had an FVC < or = 75% predicted; 27% (n = 243) had moderate restrictive disease, with an FVC value of 50-75% predicted; and only 13% (n = 116) of the patients had severe restrictive disease, with FVC < or = 50% predicted. Black race, male sex, early disease, and primary cardiac involvement due to SSc were the features most frequently associated with severe restrictive lung disease (by multiple logistic regression). Fifty-five patients with severe restrictive lung disease had their first of at least 2 PFTs during the first 5 years after onset of any SSc (not pulmonary) symptoms. In 30 patients, the FVC declined by 32% per year in the first 2 years of illness, in 16 patients the annual loss was 12% in years 2-4 after disease onset, and in 9 patients annual loss was 3% during years 4-6 of disease (P < 0.005 by 1-way analysis of variance).

Conclusion: In SSc patients, black men with early disease who have cardiac involvement are the most likely to have factors associated with the development of severe restrictive lung disease (which is increasingly becoming a major cause of death). Disease subtype (diffuse versus limited cutaneous) and serum anti-topoisomerase I antibody do not differentiate between moderate and severe restrictive disease. Careful monitoring of pulmonary function early in the disease, when the greatest loss of lung function occurs, may help identify patients likely to respond to new therapy.