期刊
ANNALS OF THE RHEUMATIC DISEASES
卷 77, 期 9, 页码 1326-1332出版社
BMJ PUBLISHING GROUP
DOI: 10.1136/annrheumdis-2018-213201
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- Boehringer Ingelheim
Objectives To identify the predictive clinical characteristics and establish a prediction model for the progression of mild interstitial lung disease (ILD) in patients with systemic sclerosis (SSc). Methods Patients with SSc from two independent prospective cohorts were included in this observational study. All patients fulfilled the 2013 American College of Rheumatology/European League Against Rheumatism criteria, had mild ILD at baseline diagnosed by High-Resolution Computed Tomography (HRCT), available baseline and al annual follow-up pulmonary function tests and no concomitant pulmonary hypertension or airflow obstruction. ILD progression was defined as a relative decrease in forced vital capacity (FVC)%>= 15%, or FVC%>= 10% combined with diffusing capacity for carbon monoxide % >= 15% at 1-year follow-up. Candidate predictors for multivariate logistic regression were selected by expert opinion based on clinical significance. A prediction model for ILD progression was established in the derivation cohort and validated in the multinational validation cohort. Results A total of 25/98 and 25/117 patients with SSc showed ILD progression in the derivation cohort and the validation cohort, respectively. Lower SpO(2) after 6 min walk test (6MWT) and arthritis ever were identified as independent predictors for ILD progression in both cohorts. The optimal cut-off value of SpO(2) after 6MWT for predicting ILD progression was determined as 94% by receiver operating characteristic curve analysis. The derived SPAR model combining both predictors (SPO2 and ARthritis) increased the prediction rate from 25.5% to 91.7% with an area under the curve (95% CI) of 0.83 (0.73 to 0.93). Conclusions The evidence-based SPAR prediction model developed in our study might be helpful for the risk stratification of patients with mild SSc-ILD in clinical practice and cohort enrichment for future clinical trial design.
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