Risk prediction model in rheumatoid arthritis‐associated interstitial lung disease
Ho Cheol Kim, Jeong Seok Lee, Eun Young Lee, You‐Jung Ha, Eun Jin Chae, Minkyu Han, Gary Cross, Joseph Barnett, Joseph Jacob, Jin Woo Song
Abstract
BACKGROUND AND OBJECTIVE: RA-ILD has a variable clinical course, and its prognosis is difficult to predict. Moreover, risk prediction models for prognosis remain undefined. METHODS: The prediction model was developed using retrospective data from 153 patients with RA-ILD and validated in an independent RA-ILD cohort (n = 149). Candidate variables for the prediction models were screened using a multivariate Cox proportional hazard model. C-statistics were calculated to assess and compare the predictive ability of each model. RESULTS: In the derivation cohort, the median follow-up period was 54 months, and 38.6% of the subjects exhibited a UIP pattern on HRCT imaging. In multivariate Cox analysis, old age (≥60 years, HR: 2.063), high fibrosis score (≥20% of the total lung extent, HR: 4.585), a UIP pattern (HR: 1.899) and emphysema (HR: 2.596) on HRCT were significantly poor prognostic factors and included in the final model. The prediction model demonstrated good performance in the prediction of 5-year mortality (C-index: 0.780, P < 0.001); furthermore, patients at risk were divided into three groups with 1-year mortality rates of 0%, 5.1% and 24.1%, respectively. Predicted and observed mortalities at 1, 2 and 3 years were similar in the derivation cohort, and the prediction model was also effective in predicting prognosis of the validation cohort (C-index: 0.638, P < 0.001). CONCLUSION: Our results suggest that a risk prediction model based on HRCT variables could be useful for patients with RA-ILD.