Predicting Mortality in Systemic Sclerosis-Associated Interstitial Lung Disease Using Risk Prediction Models Derived From Idiopathic Pulmonary Fibrosis.

BACKGROUND

Mortality risk prediction tools have been developed in idiopathic pulmonary fibrosis, however, it is unknown whether these models accurately estimate mortality in systemic sclerosis-associated interstitial lung disease (SSc-ILD).

METHODS

Four baseline risk prediction models--the Composite Physiologic Index, the Interstitial Lung Disease-Gender, Age, Physiology Index, the du Bois index, and the modified du Bois index--were calculated for patients recruited from a specialized SSc-ILD clinic. Each baseline model was assessed using logistic regression analysis with 1-year mortality as the outcome variable. Discrimination was quantified using the area under the receiver operating characteristic curve. Calibration was assessed using the goodness-of-fit test. The incremental prognostic ability of additional predictor variables was determined by adding prespecified variables to each baseline model.

RESULTS

The 156 patients with SSc-ILD completed 1,294 pulmonary function tests, 725 6-min walk tests, and 637 echocardiograms. Median survival was 15.0 years from the time of SSc-ILD diagnosis. All baseline models were significant predictors of 1-year mortality in SSc-ILD. The modified du Bois index had an area under the receiver operating characteristic curve of 0.84, compared with 0.77 to 0.81 in the other models. Calibration was acceptable for the modified du Bois index, but was poor for the other models. All baseline models include FVC and 6-min walk distance was identified as an additional independent predictor of 1-year mortality.

CONCLUSIONS

The modified du Bois index has good discrimination and calibration for the prediction of 1-year mortality in SSc-ILD. FVC and 6-min walk distance are important independent predictors of 1-year mortality in SSc-ILD.