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Updated: Feb 28, 2026

Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease
Published on: June 16, 2020
Mortality Risk Prediction in Scleroderma-Related Interstitial Lung Disease: The SADL Model
Julie Morisset1, Eric Vittinghoff2, Brett M Elicker3
1Department of Medicine, University of California, San Francisco, San Francisco, CA.
Background:
Interstitial lung disease (ILD) is an important cause of morbidity and mortality in patients with scleroderma (Scl). Risk prediction and prognostication in patients with Scl-ILD are challenging because of heterogeneity in the disease course.
Methods:
We aimed to develop a clinical mortality risk prediction model for Scl-ILD. Patients with Scl-ILD were identified from two ongoing longitudinal cohorts: 135 patients at the University of California, San Francisco (derivation cohort) and 90 patients at the Mayo Clinic (validation cohort). Using these two separate cohorts, a mortality risk prediction model was developed and validated by testing every potential candidate Cox model, each including three or four variables of a possible 19 clinical predictors, for time to death. Model discrimination was assessed using the C-index.
Results:
Three variables were included in the final risk prediction model (SADL): ever smoking history, age, and diffusing capacity of the lung for carbon monoxide (% predicted). This continuous model had similar performance in the derivation (C-index, 0.88) and validation (C-index, 0.84) cohorts. We created a point scoring system using the combined cohort (C-index, 0.82) and used it to identify a classification with low, moderate, and high mortality risk at 3 years.
Conclusions:
The SADL model uses simple, readily accessible clinical variables to predict all-cause mortality in Scl-ILD.
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