期刊
CHEST
卷 152, 期 5, 页码 999-1007出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.chest.2017.06.009
关键词
interstitial lung disease; prognosis; risk prediction; systemic sclerosis
资金
- National Center for Advancing Translational Science, National Institutes of Health [UCSF-CTI KL2TR000143]
- Scleroderma Research Foundation
- Nina Ireland Program for Lung Health
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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