Are risk predicting models useful for estimating survival of patients with rheumatoid arthritis-associated interstitial lung disease?
Nurmi, Hanna M.; Purokivi, Minna K.; Kärkkäinen, Miia S.; Kettunen, Hannu-Pekka; Selander, Tuomas A.; Kaarteenaho, Riitta L. (2017-01-13)
Nurmi, Hanna M., Minna K. Purokivi, Miia S. Kärkkäinen, Hannu-Pekka Kettunen, Tuomas A. Selander, and Riitta L. Kaarteenaho. 2017. "Are Risk Predicting Models Useful for Estimating Survival of Patients with Rheumatoid Arthritis-Associated Interstitial Lung Disease?" BMC Pulmonary Medicine 17 (1). doi:10.1186/s12890-016-0358-2.
© The Author(s). 2017. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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https://urn.fi/URN:NBN:fi-fe201702201786
Tiivistelmä
Abstract
Background: Risk predicting models have been applied in idiopathic pulmonary fibrosis (IPF), but still not validated in patients with rheumatoid arthritis-associated interstitial lung disease (RA-ILD). The purpose of this study was to test the suitability of three prediction models as well as individual lung function and demographic factors for evaluating the prognosis of RA-ILD patients.
Methods: Clinical and radiological data of 59 RA-ILD patients was re-assessed. GAP (gender, age, physiologic variables) and the modified interstitial lung disease (ILD)-GAP as well as the composite physiologic indexes (CPI) were tested for predicting mortality using the goodness-of-fit test and Cox model. Potential predictors of mortality were also sought from single lung function parameters and clinical characteristics.
Results: The median survival was 152 and 61 months in GAP / ILD-GAP stages I and II (p = 0.017). Both GAP and ILD-GAP models accurately estimated 1-year, 2-year and 3-year mortality. CPI (p = 0.025), GAP (p = 0.008) and ILD-GAP (p = 0.028) scores, age (p = 0.002), baseline diffusion capacity to carbon monoxide (DLCO) (p = 0.014) and hospitalization due to respiratory reasons (p = 0.039), were significant predictors of mortality in the univariate analysis, whereas forced vital capacity (FVC) was not predictive. CPI score (HR 1.03, p = 0.018) and baseline DLCO (HR 0.97, p = 0.011) remained significant predictors of mortality after adjusting for age.
Conclusions: GAP and ILD-GAP are applicable for evaluating the risk of death of patients with RA-ILD in a similar manner as in those with IPF. Baseline DLCO and CPI score also predicted survival.
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