Department of Rehabilitation Medicine, First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi, China.
Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi, China.
Aging (Albany NY). 2021 Feb 1;13(4):5238-5249. doi: 10.18632/aging.202443.
To establish and validate a nomogram and corresponding web-based calculator to predict the survival of patients with Parkinson's disease (PD).
In this cohort study, we retrospectively evaluated patients (n=497) with PD using a two-stage design, from March 2004 to November 2007 and from July 2005 to July 2015. Predictive variables included in the model were identified by univariate and multiple Cox proportional hazard analyses in the training set.
Independent prognostic factors including age, PD duration, and Hoehn and Yahr stage were determined and included in the model. The model showed good discrimination power with the area under the curve (AUC) values generated to predict 4-, 6-, and 8-year survival in the training set being 0.716, 0.783, and 0.814, respectively. In the validation set, the AUCs of 4- and 6-year survival predictions were 0.85 and 0.924, respectively. Calibration plots and decision curve analysis showed good model performance both in the training and validation sets. For convenient application, we established a web-based calculator (https://tangyl.shinyapps.io/PDprognosis/).
We developed a satisfactory, simple-to-use nomogram and corresponding web-based calculator based on three relevant factors to predict prognosis and survival of patients with PD. This model can aid personalized treatment and clinical decision-making.
建立并验证一个列线图和相应的网络计算器，以预测帕金森病（PD）患者的生存情况。
在这项队列研究中，我们采用两阶段设计，回顾性评估了 2004 年 3 月至 2007 年 11 月和 2005 年 7 月至 2015 年 7 月期间的 497 例 PD 患者。模型中的预测变量通过单变量和多 Cox 比例风险分析在训练集中确定。
确定了独立的预后因素，包括年龄、PD 持续时间和 Hoehn 和 Yahr 分期，并将其纳入模型。该模型具有良好的区分能力，在训练集中生成的预测 4、6 和 8 年生存率的曲线下面积（AUC）值分别为 0.716、0.783 和 0.814。在验证集中，4 年和 6 年生存率预测的 AUC 值分别为 0.85 和 0.924。校准图和决策曲线分析表明，该模型在训练集和验证集中均具有良好的性能。为了方便应用，我们建立了一个基于三个相关因素的网络计算器（https://tangyl.shinyapps.io/PDprognosis/）。
我们开发了一个基于三个相关因素的满意的、易于使用的列线图和相应的网络计算器，以预测 PD 患者的预后和生存情况。该模型可以辅助个性化治疗和临床决策。
