Mortality Risk Prediction in Scleroderma-Related Interstitial Lung Disease: The SADL Model

Abstract

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.

Keywords: interstitial lung disease; prognosis; risk prediction; systemic sclerosis.

Figure 1

Cohort formation. Patients were excluded if they did not have interstitial lung disease on high-resolution CT and/or surgical lung biopsy.

Figure 2

Cumulative mortality in the combined cohort by risk category. Red line, high-risk patients; blue line, moderate-risk patients; dashed gray line, low-risk patients.