Modeling using clinical examination indicators predicts interstitial lung disease among patients with rheumatoid arthritis
Interstitial lung disease (ILD) is a severe extra-articular manifestation of rheumatoid arthritis (RA) that is well-defined as a chronic systemic autoimmune disease. A proportion of patients with RA-associated ILD (RA-ILD) develop pulmonary fibrosis (PF), resulting in poor prognosis and increased li...
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PeerJ Inc.
2017-02-01
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| Online Access: | https://peerj.com/articles/3021.pdf |
| _version_ | 1797418375815626752 |
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| author | Yao Wang Wuqi Song Jing Wu Zhangming Li Fengyun Mu Yang Li He Huang Wenliang Zhu Fengmin Zhang |
| author_facet | Yao Wang Wuqi Song Jing Wu Zhangming Li Fengyun Mu Yang Li He Huang Wenliang Zhu Fengmin Zhang |
| author_sort | Yao Wang |
| collection | DOAJ |
| description | Interstitial lung disease (ILD) is a severe extra-articular manifestation of rheumatoid arthritis (RA) that is well-defined as a chronic systemic autoimmune disease. A proportion of patients with RA-associated ILD (RA-ILD) develop pulmonary fibrosis (PF), resulting in poor prognosis and increased lifetime risk. We investigated whether routine clinical examination indicators (CEIs) could be used to identify RA patients with high PF risk. A total of 533 patients with established RA were recruited in this study for model building and 32 CEIs were measured for each of them. To identify PF risk, a new artificial neural network (ANN) was built, in which inputs were generated by calculating Euclidean distance of CEIs between patients. Receiver operating characteristic curve analysis indicated that the ANN performed well in predicting the PF risk (Youden index = 0.436) by only incorporating four CEIs including age, eosinophil count, platelet count, and white blood cell count. A set of 218 RA patients with healthy lungs or suffering from ILD and a set of 87 RA patients suffering from PF were used for independent validation. Results showed that the model successfully identified ILD and PF with a true positive rate of 84.9% and 82.8%, respectively. The present study suggests that model integration of multiple routine CEIs contributes to identification of potential PF risk among patients with RA. |
| first_indexed | 2024-03-09T06:32:51Z |
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| institution | Directory Open Access Journal |
| issn | 2167-8359 |
| language | English |
| last_indexed | 2024-03-09T06:32:51Z |
| publishDate | 2017-02-01 |
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| spelling | doaj.art-4564f96aca3947f58bc1dd10ba0531e42023-12-03T11:03:04ZengPeerJ Inc.PeerJ2167-83592017-02-015e302110.7717/peerj.3021Modeling using clinical examination indicators predicts interstitial lung disease among patients with rheumatoid arthritisYao Wang0Wuqi Song1Jing Wu2Zhangming Li3Fengyun Mu4Yang Li5He Huang6Wenliang Zhu7Fengmin Zhang8Department of Microbiology, Wu Lien-Teh Institute, Harbin Medical University, Harbin, Heilongjiang Province, ChinaDepartment of Microbiology, Wu Lien-Teh Institute, Harbin Medical University, Harbin, Heilongjiang Province, ChinaDepartment of Microbiology, Wu Lien-Teh Institute, Harbin Medical University, Harbin, Heilongjiang Province, ChinaDepartment of Pharmacy Administration, Harbin Medical University, Harbin, Heilongjiang Province, ChinaDepartment of Laboratory Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, ChinaDepartment of Rheumatology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, ChinaDepartment of Rheumatology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, ChinaInstitute of Clinical Pharmacology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, ChinaDepartment of Microbiology, Wu Lien-Teh Institute, Harbin Medical University, Harbin, Heilongjiang Province, ChinaInterstitial lung disease (ILD) is a severe extra-articular manifestation of rheumatoid arthritis (RA) that is well-defined as a chronic systemic autoimmune disease. A proportion of patients with RA-associated ILD (RA-ILD) develop pulmonary fibrosis (PF), resulting in poor prognosis and increased lifetime risk. We investigated whether routine clinical examination indicators (CEIs) could be used to identify RA patients with high PF risk. A total of 533 patients with established RA were recruited in this study for model building and 32 CEIs were measured for each of them. To identify PF risk, a new artificial neural network (ANN) was built, in which inputs were generated by calculating Euclidean distance of CEIs between patients. Receiver operating characteristic curve analysis indicated that the ANN performed well in predicting the PF risk (Youden index = 0.436) by only incorporating four CEIs including age, eosinophil count, platelet count, and white blood cell count. A set of 218 RA patients with healthy lungs or suffering from ILD and a set of 87 RA patients suffering from PF were used for independent validation. Results showed that the model successfully identified ILD and PF with a true positive rate of 84.9% and 82.8%, respectively. The present study suggests that model integration of multiple routine CEIs contributes to identification of potential PF risk among patients with RA.https://peerj.com/articles/3021.pdfClinical examination indicatorArtificial neural networkInterstitial lung diseasePulmonary fibrosisRheumatoid arthritisEuclidean distance |
| spellingShingle | Yao Wang Wuqi Song Jing Wu Zhangming Li Fengyun Mu Yang Li He Huang Wenliang Zhu Fengmin Zhang Modeling using clinical examination indicators predicts interstitial lung disease among patients with rheumatoid arthritis PeerJ Clinical examination indicator Artificial neural network Interstitial lung disease Pulmonary fibrosis Rheumatoid arthritis Euclidean distance |
| title | Modeling using clinical examination indicators predicts interstitial lung disease among patients with rheumatoid arthritis |
| title_full | Modeling using clinical examination indicators predicts interstitial lung disease among patients with rheumatoid arthritis |
| title_fullStr | Modeling using clinical examination indicators predicts interstitial lung disease among patients with rheumatoid arthritis |
| title_full_unstemmed | Modeling using clinical examination indicators predicts interstitial lung disease among patients with rheumatoid arthritis |
| title_short | Modeling using clinical examination indicators predicts interstitial lung disease among patients with rheumatoid arthritis |
| title_sort | modeling using clinical examination indicators predicts interstitial lung disease among patients with rheumatoid arthritis |
| topic | Clinical examination indicator Artificial neural network Interstitial lung disease Pulmonary fibrosis Rheumatoid arthritis Euclidean distance |
| url | https://peerj.com/articles/3021.pdf |
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