Development and internal validation of a prediction model for rheumatoid arthritis: a case-control study
Abstract This study measured sociodemographic characteristics, dietary habits, lifestyle habits, genetics, and other factors that may contribute to the development of Rheumatoid Arthritis (RA). Independent risk factors for RA were identified by logistic regression analysis, and a prediction model wa...
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Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-00816-7 |
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| author | Ling Tu Fuling Wei Yuqing Song Haitao Huang Ligang Qing Xi Luo Ying Liu Hong Chen |
| author_facet | Ling Tu Fuling Wei Yuqing Song Haitao Huang Ligang Qing Xi Luo Ying Liu Hong Chen |
| author_sort | Ling Tu |
| collection | DOAJ |
| description | Abstract This study measured sociodemographic characteristics, dietary habits, lifestyle habits, genetics, and other factors that may contribute to the development of Rheumatoid Arthritis (RA). Independent risk factors for RA were identified by logistic regression analysis, and a prediction model was constructed. The area under the receiver operating characteristic curve (AUC) was used to evaluate the prediction accuracy of the model, and the calibration of the model was evaluated by the Hosmer–Lemeshow test. A total of 432 participants, comprising 216 healthy individuals and 216 patients diagnosed with RA at two hospitals in Sichuan, China, from March 2022 to January 2023 were included in this study. Logistic regression analysis revealed that occupation type, place of residence, history of mumps, dietary combination, sweet, damp dwelling, fish, vaccine history, and rs805297 were significantly associated with the pathogenesis of RA. The model constructed in this study showed good prediction, with an AUC of 0.912. The Youden index was 0.699, the sensitivity was 0.847 and the specificity was 0.852. The Hosmer–Lemeshow test results (χ2 = 8.441, P = 0.392) indicated that the model had good diagnostic value. The internal validation AUC was 0.942. We propose a new promising model for identifying individuals at risk of developing RA. |
| format | Article |
| id | doaj-art-458b4cbcd89b4b23af3f659f0857d6ca |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-458b4cbcd89b4b23af3f659f0857d6ca2025-08-20T01:51:31ZengNature PortfolioScientific Reports2045-23222025-05-0115111210.1038/s41598-025-00816-7Development and internal validation of a prediction model for rheumatoid arthritis: a case-control studyLing Tu0Fuling Wei1Yuqing Song2Haitao Huang3Ligang Qing4Xi Luo5Ying Liu6Hong Chen7Department of Nursing, West China School of Nursing, West China Hospital, Sichuan UniversityDepartment of Nursing, West China School of Nursing, West China Hospital, Sichuan UniversitySchool of Nursing, Chengdu University of Traditional Chinese MedicineDepartment of Nursing, West China School of Nursing, West China Hospital, Sichuan UniversityShi Yang Community Health Service CenterShi Yang Community Health Service CenterDepartment of Nursing, West China School of Nursing, West China Hospital, Sichuan UniversityDepartment of Nursing, West China School of Nursing, West China Hospital, Sichuan UniversityAbstract This study measured sociodemographic characteristics, dietary habits, lifestyle habits, genetics, and other factors that may contribute to the development of Rheumatoid Arthritis (RA). Independent risk factors for RA were identified by logistic regression analysis, and a prediction model was constructed. The area under the receiver operating characteristic curve (AUC) was used to evaluate the prediction accuracy of the model, and the calibration of the model was evaluated by the Hosmer–Lemeshow test. A total of 432 participants, comprising 216 healthy individuals and 216 patients diagnosed with RA at two hospitals in Sichuan, China, from March 2022 to January 2023 were included in this study. Logistic regression analysis revealed that occupation type, place of residence, history of mumps, dietary combination, sweet, damp dwelling, fish, vaccine history, and rs805297 were significantly associated with the pathogenesis of RA. The model constructed in this study showed good prediction, with an AUC of 0.912. The Youden index was 0.699, the sensitivity was 0.847 and the specificity was 0.852. The Hosmer–Lemeshow test results (χ2 = 8.441, P = 0.392) indicated that the model had good diagnostic value. The internal validation AUC was 0.942. We propose a new promising model for identifying individuals at risk of developing RA.https://doi.org/10.1038/s41598-025-00816-7Rheumatoid arthritisRisk prediction modelRisk factorsRisk assessmentCase-control study |
| spellingShingle | Ling Tu Fuling Wei Yuqing Song Haitao Huang Ligang Qing Xi Luo Ying Liu Hong Chen Development and internal validation of a prediction model for rheumatoid arthritis: a case-control study Scientific Reports Rheumatoid arthritis Risk prediction model Risk factors Risk assessment Case-control study |
| title | Development and internal validation of a prediction model for rheumatoid arthritis: a case-control study |
| title_full | Development and internal validation of a prediction model for rheumatoid arthritis: a case-control study |
| title_fullStr | Development and internal validation of a prediction model for rheumatoid arthritis: a case-control study |
| title_full_unstemmed | Development and internal validation of a prediction model for rheumatoid arthritis: a case-control study |
| title_short | Development and internal validation of a prediction model for rheumatoid arthritis: a case-control study |
| title_sort | development and internal validation of a prediction model for rheumatoid arthritis a case control study |
| topic | Rheumatoid arthritis Risk prediction model Risk factors Risk assessment Case-control study |
| url | https://doi.org/10.1038/s41598-025-00816-7 |
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