{"title":"基于提名图的模型可准确预测轴性脊柱关节炎的疾病复发。","authors":"Lianjie Wang Apipu Thitidechnisa, Yifang Wei, Jing Chen, Hongbing Rui, Yu Huang, Qing Zheng","doi":"10.1177/10538127241303356","DOIUrl":null,"url":null,"abstract":"<p><p>BackgroundThe accuracy of predicting axial spondyloarthritis (axSpA) flares based on clinical experience is limited.ObjectiveThe aim of this study was to evaluate the efficacy of the previously designed nomogram prediction model in forecasting disease flares among rheumatologists and medical students.MethodsPatients who met the classification criteria for axSpA were enrolled in the study. Once a low ankylosing spondylitis disease activity score (ASDAS ≤ 2.1) was achieved, patients were monitored for 12 months to observe any disease flare-ups. Investigators assessed the likelihood of axSpA recurrence using the nomogram prediction model and their clinical experience, respectively. This allowed for a comparison of the predictive efficacy of both methods among the specialists and students.ResultsThe accuracy, sensitivity, specificity, and Youden index in which disease flare-ups were predicted by the rheumatologist using clinical experience were slightly lower than those obtained using the nomogram prediction model, but the difference was not statistically significant (<i>P </i>> 0.05). In contrast, the indicators above by medical students using clinical experience were significantly lower compared to those predicted by the nomogram prediction model (<i>P </i>< 0.05).ConclusionThe nomogram prediction model is effective in predicting the probability of disease remission and flare-ups in axSpA patients with low disease activity, demonstrating good clinical practicality and usability. Medical students can also use this model to significantly enhance the accuracy of predicting axSpA flares.</p>","PeriodicalId":15129,"journal":{"name":"Journal of Back and Musculoskeletal Rehabilitation","volume":"38 2","pages":"287-293"},"PeriodicalIF":1.4000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nomogram-Based model accurately predicts disease flare-ups in axial spondyloarthritis.\",\"authors\":\"Lianjie Wang Apipu Thitidechnisa, Yifang Wei, Jing Chen, Hongbing Rui, Yu Huang, Qing Zheng\",\"doi\":\"10.1177/10538127241303356\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>BackgroundThe accuracy of predicting axial spondyloarthritis (axSpA) flares based on clinical experience is limited.ObjectiveThe aim of this study was to evaluate the efficacy of the previously designed nomogram prediction model in forecasting disease flares among rheumatologists and medical students.MethodsPatients who met the classification criteria for axSpA were enrolled in the study. Once a low ankylosing spondylitis disease activity score (ASDAS ≤ 2.1) was achieved, patients were monitored for 12 months to observe any disease flare-ups. Investigators assessed the likelihood of axSpA recurrence using the nomogram prediction model and their clinical experience, respectively. This allowed for a comparison of the predictive efficacy of both methods among the specialists and students.ResultsThe accuracy, sensitivity, specificity, and Youden index in which disease flare-ups were predicted by the rheumatologist using clinical experience were slightly lower than those obtained using the nomogram prediction model, but the difference was not statistically significant (<i>P </i>> 0.05). In contrast, the indicators above by medical students using clinical experience were significantly lower compared to those predicted by the nomogram prediction model (<i>P </i>< 0.05).ConclusionThe nomogram prediction model is effective in predicting the probability of disease remission and flare-ups in axSpA patients with low disease activity, demonstrating good clinical practicality and usability. Medical students can also use this model to significantly enhance the accuracy of predicting axSpA flares.</p>\",\"PeriodicalId\":15129,\"journal\":{\"name\":\"Journal of Back and Musculoskeletal Rehabilitation\",\"volume\":\"38 2\",\"pages\":\"287-293\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Back and Musculoskeletal Rehabilitation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/10538127241303356\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/12/20 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"ORTHOPEDICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Back and Musculoskeletal Rehabilitation","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/10538127241303356","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/20 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ORTHOPEDICS","Score":null,"Total":0}
Nomogram-Based model accurately predicts disease flare-ups in axial spondyloarthritis.
BackgroundThe accuracy of predicting axial spondyloarthritis (axSpA) flares based on clinical experience is limited.ObjectiveThe aim of this study was to evaluate the efficacy of the previously designed nomogram prediction model in forecasting disease flares among rheumatologists and medical students.MethodsPatients who met the classification criteria for axSpA were enrolled in the study. Once a low ankylosing spondylitis disease activity score (ASDAS ≤ 2.1) was achieved, patients were monitored for 12 months to observe any disease flare-ups. Investigators assessed the likelihood of axSpA recurrence using the nomogram prediction model and their clinical experience, respectively. This allowed for a comparison of the predictive efficacy of both methods among the specialists and students.ResultsThe accuracy, sensitivity, specificity, and Youden index in which disease flare-ups were predicted by the rheumatologist using clinical experience were slightly lower than those obtained using the nomogram prediction model, but the difference was not statistically significant (P > 0.05). In contrast, the indicators above by medical students using clinical experience were significantly lower compared to those predicted by the nomogram prediction model (P < 0.05).ConclusionThe nomogram prediction model is effective in predicting the probability of disease remission and flare-ups in axSpA patients with low disease activity, demonstrating good clinical practicality and usability. Medical students can also use this model to significantly enhance the accuracy of predicting axSpA flares.
期刊介绍:
The Journal of Back and Musculoskeletal Rehabilitation is a journal whose main focus is to present relevant information about the interdisciplinary approach to musculoskeletal rehabilitation for clinicians who treat patients with back and musculoskeletal pain complaints. It will provide readers with both 1) a general fund of knowledge on the assessment and management of specific problems and 2) new information considered to be state-of-the-art in the field. The intended audience is multidisciplinary as well as multi-specialty.
In each issue clinicians can find information which they can use in their patient setting the very next day.