{"title":"中国帕金森病患者长期左旋多巴治疗后消退和运动障碍的危险因素识别和预测模型构建","authors":"Jing Zhao, Yunlei Gao, Chong Shi, Jia Chen, Yanhong Wang, Jiaqi Chen, Shaochen Ma, Peifu Wang, Jilai Li, Jichen Du, Zhirong Wan","doi":"10.1111/cns.70544","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Aims</h3>\n \n <p>This study aimed to investigate the incidence and risk factors of motor complications including wearing-off (WO) and dyskinesia during long-term levodopa (LD) therapy in Chinese patients with Parkinson's disease (PD), and develop corresponding predictive models, thereby providing a basis for personalized treatment strategies.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>This cross-sectional study included 208 consecutive PD patients who were recruited. The presence of WO and dyskinesia was assessed by a 9-item wearing-off questionnaire and the Unified Parkinson's Disease Rating Scale part IV. Univariate and multivariate logistic regression analyses were used to predict the risk factors of WO and dyskinesia. Predictive models for WO and dyskinesia were then constructed, and their diagnostic performance was evaluated using the area under the curve (AUC).</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The overall prevalence rate of motor complications was 46.2% (96/208), with a prevalence of 45.7% (95/208) for WO, 22.1% (46/208) for dyskinesia, and 21.6% (45/208) for the simultaneous occurrence of WO and dyskinesia. Younger age at onset (OR 0.92, <i>p</i> < 0.001), higher levodopa-equivalent daily dose (LEDD) (OR 1.00, <i>p</i> < 0.001), and higher Hoehn-Yahr stage (OR 3.41, <i>p</i> < 0.001) were independent risk factors for WO. A predictive model for WO constructed using these three variables demonstrated high diagnostic efficacy with an AUC of 0.887 (95% CI 0.842–0.932), a sensitivity of 84%, and a specificity of 83%. The independent risk factors for dyskinesia included younger age at onset (OR 0.94, <i>p</i> < 0.001), akinetic-rigid type (OR 2.42, <i>p</i> = 0.034), and higher LEDD (OR 1.01, <i>p</i> < 0.001). A predictive model for dyskinesia constructed using these three variables yielded an AUC value of 0.829 (95% CI 0.767–0.897), with a sensitivity of 67% and a specificity of 89%. The two models were both well calibrated and had a high net clinical benefit.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>Our findings suggest that the prevalence of motor complications during long-term LD treatment is relatively high among PD patients in China, with WO occurring more commonly than dyskinesia. Younger age at PD onset, higher LEDD, more severe disease, and akinetic-rigid subtype are key predictors of motor complications. The predictive models developed in this study could serve as a potential tool to assist clinicians in identifying patients at higher risk for WO and dyskinesia, and may support personalized treatment optimization.</p>\n </section>\n </div>","PeriodicalId":154,"journal":{"name":"CNS Neuroscience & Therapeutics","volume":"31 8","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cns.70544","citationCount":"0","resultStr":"{\"title\":\"Identifying Risk Factors and Constructing Predictive Models for Wearing-Off and Dyskinesia in Chinese Patients With Parkinson's Disease on Long-Term Levodopa Therapy\",\"authors\":\"Jing Zhao, Yunlei Gao, Chong Shi, Jia Chen, Yanhong Wang, Jiaqi Chen, Shaochen Ma, Peifu Wang, Jilai Li, Jichen Du, Zhirong Wan\",\"doi\":\"10.1111/cns.70544\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Aims</h3>\\n \\n <p>This study aimed to investigate the incidence and risk factors of motor complications including wearing-off (WO) and dyskinesia during long-term levodopa (LD) therapy in Chinese patients with Parkinson's disease (PD), and develop corresponding predictive models, thereby providing a basis for personalized treatment strategies.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>This cross-sectional study included 208 consecutive PD patients who were recruited. The presence of WO and dyskinesia was assessed by a 9-item wearing-off questionnaire and the Unified Parkinson's Disease Rating Scale part IV. Univariate and multivariate logistic regression analyses were used to predict the risk factors of WO and dyskinesia. Predictive models for WO and dyskinesia were then constructed, and their diagnostic performance was evaluated using the area under the curve (AUC).</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>The overall prevalence rate of motor complications was 46.2% (96/208), with a prevalence of 45.7% (95/208) for WO, 22.1% (46/208) for dyskinesia, and 21.6% (45/208) for the simultaneous occurrence of WO and dyskinesia. Younger age at onset (OR 0.92, <i>p</i> < 0.001), higher levodopa-equivalent daily dose (LEDD) (OR 1.00, <i>p</i> < 0.001), and higher Hoehn-Yahr stage (OR 3.41, <i>p</i> < 0.001) were independent risk factors for WO. A predictive model for WO constructed using these three variables demonstrated high diagnostic efficacy with an AUC of 0.887 (95% CI 0.842–0.932), a sensitivity of 84%, and a specificity of 83%. The independent risk factors for dyskinesia included younger age at onset (OR 0.94, <i>p</i> < 0.001), akinetic-rigid type (OR 2.42, <i>p</i> = 0.034), and higher LEDD (OR 1.01, <i>p</i> < 0.001). A predictive model for dyskinesia constructed using these three variables yielded an AUC value of 0.829 (95% CI 0.767–0.897), with a sensitivity of 67% and a specificity of 89%. The two models were both well calibrated and had a high net clinical benefit.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>Our findings suggest that the prevalence of motor complications during long-term LD treatment is relatively high among PD patients in China, with WO occurring more commonly than dyskinesia. Younger age at PD onset, higher LEDD, more severe disease, and akinetic-rigid subtype are key predictors of motor complications. The predictive models developed in this study could serve as a potential tool to assist clinicians in identifying patients at higher risk for WO and dyskinesia, and may support personalized treatment optimization.</p>\\n </section>\\n </div>\",\"PeriodicalId\":154,\"journal\":{\"name\":\"CNS Neuroscience & Therapeutics\",\"volume\":\"31 8\",\"pages\":\"\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2025-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cns.70544\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CNS Neuroscience & Therapeutics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/cns.70544\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CNS Neuroscience & Therapeutics","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/cns.70544","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
目的探讨我国帕金森病(PD)患者长期左旋多巴(LD)治疗过程中磨耗(WO)、运动障碍等运动并发症的发生率及危险因素,建立相应的预测模型,为制定个性化治疗策略提供依据。方法本横断面研究纳入了208例连续入选的PD患者。通过9项逐渐消失问卷和统一帕金森病评定量表第四部分来评估WO和运动障碍的存在。单变量和多变量logistic回归分析用于预测WO和运动障碍的危险因素。然后构建WO和运动障碍的预测模型,并使用曲线下面积(AUC)评估其诊断性能。结果运动并发症总体发生率为46.2%(96/208),其中运动障碍发生率为45.7%(95/208),运动障碍发生率为22.1%(46/208),运动障碍合并运动障碍发生率为21.6%(45/208)。发病年龄较小(OR 0.92, p < 0.001)、左旋多巴当量日剂量(LEDD)较高(OR 1.00, p < 0.001)和Hoehn-Yahr分期较高(OR 3.41, p < 0.001)是WO的独立危险因素。使用这三个变量构建的WO预测模型显示出较高的诊断效果,AUC为0.887 (95% CI 0.842-0.932),敏感性为84%,特异性为83%。运动障碍的独立危险因素包括发病年龄较轻(OR 0.94, p < 0.001)、动力刚性型(OR 2.42, p = 0.034)和较高的LEDD (OR 1.01, p < 0.001)。使用这三个变量构建的运动障碍预测模型的AUC值为0.829 (95% CI 0.767-0.897),敏感性为67%,特异性为89%。这两种模型都经过了很好的校准,并且具有很高的净临床效益。结论我们的研究结果表明,在中国PD患者中,长期LD治疗期间运动并发症的发生率相对较高,其中WO比运动障碍更常见。PD发病年龄越小、LEDD越高、病情越严重、运动刚性亚型是运动并发症的关键预测因素。本研究中建立的预测模型可以作为一种潜在的工具,帮助临床医生识别WO和运动障碍的高风险患者,并可能支持个性化的治疗优化。
Identifying Risk Factors and Constructing Predictive Models for Wearing-Off and Dyskinesia in Chinese Patients With Parkinson's Disease on Long-Term Levodopa Therapy
Aims
This study aimed to investigate the incidence and risk factors of motor complications including wearing-off (WO) and dyskinesia during long-term levodopa (LD) therapy in Chinese patients with Parkinson's disease (PD), and develop corresponding predictive models, thereby providing a basis for personalized treatment strategies.
Methods
This cross-sectional study included 208 consecutive PD patients who were recruited. The presence of WO and dyskinesia was assessed by a 9-item wearing-off questionnaire and the Unified Parkinson's Disease Rating Scale part IV. Univariate and multivariate logistic regression analyses were used to predict the risk factors of WO and dyskinesia. Predictive models for WO and dyskinesia were then constructed, and their diagnostic performance was evaluated using the area under the curve (AUC).
Results
The overall prevalence rate of motor complications was 46.2% (96/208), with a prevalence of 45.7% (95/208) for WO, 22.1% (46/208) for dyskinesia, and 21.6% (45/208) for the simultaneous occurrence of WO and dyskinesia. Younger age at onset (OR 0.92, p < 0.001), higher levodopa-equivalent daily dose (LEDD) (OR 1.00, p < 0.001), and higher Hoehn-Yahr stage (OR 3.41, p < 0.001) were independent risk factors for WO. A predictive model for WO constructed using these three variables demonstrated high diagnostic efficacy with an AUC of 0.887 (95% CI 0.842–0.932), a sensitivity of 84%, and a specificity of 83%. The independent risk factors for dyskinesia included younger age at onset (OR 0.94, p < 0.001), akinetic-rigid type (OR 2.42, p = 0.034), and higher LEDD (OR 1.01, p < 0.001). A predictive model for dyskinesia constructed using these three variables yielded an AUC value of 0.829 (95% CI 0.767–0.897), with a sensitivity of 67% and a specificity of 89%. The two models were both well calibrated and had a high net clinical benefit.
Conclusion
Our findings suggest that the prevalence of motor complications during long-term LD treatment is relatively high among PD patients in China, with WO occurring more commonly than dyskinesia. Younger age at PD onset, higher LEDD, more severe disease, and akinetic-rigid subtype are key predictors of motor complications. The predictive models developed in this study could serve as a potential tool to assist clinicians in identifying patients at higher risk for WO and dyskinesia, and may support personalized treatment optimization.
期刊介绍:
CNS Neuroscience & Therapeutics provides a medium for rapid publication of original clinical, experimental, and translational research papers, timely reviews and reports of novel findings of therapeutic relevance to the central nervous system, as well as papers related to clinical pharmacology, drug development and novel methodologies for drug evaluation. The journal focuses on neurological and psychiatric diseases such as stroke, Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, epilepsy, and drug abuse.