Mortality risk prediction in scleroderma-related interstitial lung disease: the SADL model

Rationale

Interstitial lung disease (ILD) is an important cause of morbidity and mortality in scleroderma (Scl). Risk prediction and prognostication in Scl-ILD patients is 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 (UCSF, 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 3 or 4 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 DLco %-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.

Conclusion

The SADL model uses simple, readily accessible clinical variables to predict all-cause mortality in Scl-ILD.

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