University of Oulu

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.

Are risk predicting models useful for estimating survival of patients with rheumatoid arthritis-associated interstitial lung disease?

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Author: Nurmi, Hanna M.1,2; Purokivi, Minna K.1; Kärkkäinen, Miia S.2;
Organizations: 1Center of Medicine and Clinical Research, Division of Respiratory Medicine, Kuopio University Hospital
2Division of Respiratory Medicine, Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland
3Diagnostic Imaging Center, Division of Radiology, Kuopio University Hospital
4Science Services Center, Kuopio University Hospital
5Respiratory Medicine, Internal Medicine Research Unit, Medical Research Center Oulu, Oulu University Hospital and University of Oulu
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe201702201786
Language: English
Published: BioMed Central, 2017
Publish Date: 2017-02-20
Description:

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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Series: Bmc pulmonary medicine
ISSN: 1471-2466
ISSN-E: 1471-2466
ISSN-L: 1471-2466
Issue: 17
Article number: 16
DOI: 10.1186/s12890-016-0358-2
OADOI: https://oadoi.org/10.1186/s12890-016-0358-2
Type of Publication: A1 Journal article – refereed
Field of Science: 3121 Internal medicine
Subjects:
GAP
Funding: The study was supported by the Foundation of the Finnish Anti-Tuberculosis Association, the Jalmari and Rauha Ahokas Foundation, the Väinö and Laina Kivi Foundation, The Research Foundation of the Pulmonary Diseases, The Kuopio region Respiratory Foundation and a state subsidy of the Kuopio University Hospital.
Dataset Reference: We cannot share our original data. It has been gathered in a detailed manner and minding that our population is relatively small in this Eastern-Finland hospital, we could not guarantee anonymity of the individual patients.
Copyright information: © 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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