Investigation of fall risk in patients with Parkinson’s disease and establishment and validation of a nomogram prediction model based on LASSO regression

Hu Haiqiong; Li Lixia; Shao Yu; Huang Yuanyuan; Xiao Fajun; Xia Ke

doi:10.13406/j.cnki.cyxb.003926

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Investigation of fall risk in patients with Parkinson’s disease and establishment and validation of a nomogram prediction model based on LASSO regression

Frontiers in brain science and neuropsychiatric disorders | 更新时间：2025-10-21

- Investigation of fall risk in patients with Parkinson’s disease and establishment and validation of a nomogram prediction model based on LASSO regression
- Journal of Chongqing Medical University Vol. 50, Issue 10, Pages: 1338-1344(2025)
- 作者机构：
  
  四川省南充精神卫生中心神经内科，南充 637000
- 作者简介：
- 基金信息：
- DOI：10.13406/j.cnki.cyxb.003926
  CLC： R741
- Received：01 April 2025，
  
  Revised：2025-05-14，
  
  Accepted：20 June 2025，
  
  Published：28 October 2025
- 稿件说明：
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胡海琼,李莉霞,邵宇,等.帕金森病患者跌倒风险调查及基于LASSO回归的列线图预测模型建立与验证[J].重庆医科大学学报,2025,50(10):1338-1344.

Hu Haiqiong,Li Lixia,Shao Yu,et al.Investigation of fall risk in patients with Parkinson’s disease and establishment and validation of a nomogram prediction model based on LASSO regression[J].Journal of Chongqing Medical University,2025,50(10):1338-1344.
胡海琼,李莉霞,邵宇,等.帕金森病患者跌倒风险调查及基于LASSO回归的列线图预测模型建立与验证[J].重庆医科大学学报,2025,50(10):1338-1344. DOI： 10.13406/j.cnki.cyxb.003926.

Hu Haiqiong,Li Lixia,Shao Yu,et al.Investigation of fall risk in patients with Parkinson’s disease and establishment and validation of a nomogram prediction model based on LASSO regression[J].Journal of Chongqing Medical University,2025,50(10):1338-1344. DOI： 10.13406/j.cnki.cyxb.003926.

摘要

目的

调查帕金森病患者跌倒风险，建立其预测模型并进行验证。

方法

选择2022年1月至2023年9月四川省南充精神卫生中心收治的372例帕金森病患者，按7：3比例分为建模组（260例）和验证组（112例）。根据过往文献报道及临床实践中发现的疑似因素收集一般资料（性别和年龄等）、疾病相关因素（帕金森病程和服药种类等）等可能影响帕金森病患者跌倒的相关因素，根据患者或其家属报告1年内有无跌倒将模型组患者分为2组，比较2组一般资料及疾病因素，以套索回归（least absolute shrinkage and selection operator，LASSO）筛选潜在变量后行多因素logistic回归，建立列线图模型并验证。

结果

模型组260例患者中，共81例（31.15%）出现跌倒。LASSO回归基础上行多因素logistic回归分析结果显示：饮酒、服药种类、帕金森病评价量表第三部分（unified Parkinson’s disease rating scale part Ⅲ，UPDRS-Ⅲ）、伯格（Berg）平衡量表、关节炎及骨质疏松为帕金森病患者跌倒的独立性影响因素。受试者工作特征曲线（receiver operator characteristic curve，ROC）分析结果显示，模型组预测帕金森病患者跌倒风险的曲线下面积（area under the curve，AUC）为0.896（95%CI=0.856~0.935），验证组预测帕金森病患者跌倒风险的AUC为0.883（95%CI=0.840~0.926）；校准曲线结果显示，模型组与验证组的预测曲线与标准曲线基本拟合。决策曲线分析结果显示：当列线图预测帕金森病患者跌倒风险概率阈值为0.10~0.90时，患者的净受益率>0。

结论

帕金森病患者跌倒主要受饮酒和服药种类等因素的影响，本研究建立的列线图模型可用于预测帕金森病患者跌倒风险。

Abstract

Objective

To investigate the risk of falls in patients with Parkinson’s disease and establish and validate a prediction model.

Methods

We selected 372 patients with Parkinson’s disease at Sichuan Nanchong Mental Health Centre from January 2022 to September 2023. The patients were divided in a 7：3 ratio into model group（260 cases） and validation group（112 cases）. According to previous literature and suspected factors found in clinical practice，we collected general information（sex，age，etc.） and disease-related factors（the duration of Parkinson’s disease，the type of medications taken，etc.） that may be associated with falls in patients with Parkinson’s disease. In the model group，between patients with and those without falls within 1 year as reported by the patients or their family members，potential predictors for falls were determined through comparison of general information and disease-related factors，least absolute shrinkage and selection operator（LASSO） regression，and multivariable logistic regression. Based on the significant factors，a nomogram model was established and validated.

Results

In the model group，81（31.15%） of the 260 patients experienced falls. According to the LASSO regression and multivariable logistic regression results，alcohol consumption，the type of medications，the score of the Unified Parkinson’s Disease Rating Scale part Ⅲ（UPDRS-Ⅲ），the Berg Balance Scale score，the presence of arthritis，and the presence of osteoporosis were independent factors influencing falls in patients with Parkinson’s disease. The area under curve （AUC） of the receiver operator characteristic curve（ROC） for predicting the risk of falls in patients with Parkinson’s disease was 0.896（95%CI=0.856-0.935） in the model group and 0.883（95%CI=0.840-0.926） in the validation group. The calibration curve analysis results showed that the prediction curves of the model and validation groups closely fitted the standard curves. The decision curve analysis results indicated that when the probability threshold for predicting the fall risk in Parkinson’s disease using the nomogram was 0.10-0.90，the net benefit rate of the patients was greater than 0.

Conclusion

The risk of falls in patients with Parkinson’s disease are mainly influenced by factors such as alcohol consumption and the type of medications. The nomogram model established in this study can be used to predict the fall risk in patients with Parkinson’s disease.

关键词

Keywords

references

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