- Morisset, Julie;
- Vittinghoff, Eric;
- Elicker, Brett M;
- Hu, Xiaowen;
- Le, Stephanie;
- Ryu, Jay H;
- Jones, Kirk D;
- Haemel, Anna;
- Golden, Jeffrey A;
- Boin, Francesco;
- Ley, Brett;
- Wolters, Paul J;
- King, Talmadge E;
- Collard, Harold R;
- Lee, Joyce S
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.