We previously reported a basic algorithm to identify the risk of Parkinson’s disease (PD) using published data on risk factors and prodromal features. Using this algorithm, the PREDICT-PD study identified individuals at increased risk of PD and used tapping speed, hyposmia and REM sleep behaviour disorder (RBD) as “intermediate” markers of prodromal PD in the absence of sufficient incident cases. We have now developed and tested an enhanced algorithm which incorporates the intermediate markers into the risk model. Risk estimates were compared using the enhanced and the basic algorithm in members of the PREDICT-PD pilot cohort. The enhanced PREDICT-PD algorithm yielded a much greater range of risk estimates than the basic algorithm (93–609-fold difference between the 10th and 90th centiles vs 10–13-fold respectively). There was a greater increase in the risk of PD with increasing risk scores for the enhanced algorithm than for the basic algorithm (hazard ratios per one standard deviation increase in log risk of 2.75 [95% CI 1.68–4.50; p < 0.001] versus 1.47 [95% CI 0.86–2.51; p = 0.16] respectively). Estimates from the enhanced algorithm also correlated more closely with subclinical striatal DaT-SPECT dopamine depletion (R² = 0.164, p = 0.005 vs R² = 0.043, p = 0.17). Incorporating the previous intermediate markers of prodromal PD and using likelihood ratios improved the accuracy of the PREDICT-PD prediction algorithm.

我们先前报道了一种基本算法，可使用已发布的有关危险因素和前驱特征的数据来识别帕金森氏病（PD）的风险。使用此算法，PREDICT-PD研究确定了PD风险增加的个体，并在没有足够事件发生的情况下，将敲击速度，低渗和REM睡眠行为障碍（RBD）用作前驱PD的“中间”标记。现在，我们已经开发并测试了一种增强的算法，该算法将中间标记纳入了风险模型。在PREDICT-PD试点队列的成员中，使用增强算法和基本算法比较了风险估计。增强的PREDICT-PD算法产生的风险估计范围比基本算法大得多（第10和90个百分位数之间的差异为93-609倍，而第10至13倍之间的差异为10-13倍）。p  <0.001]与1.47 [95％CI 0.86-2.51；p  = 0.16]。增强算法的估计值也与亚临床纹状体DaT-SPECT多巴胺耗竭密切相关（R ²  = 0.164，P  = 0.005，R ²  = 0.043，P  = 0.17）。合并前驱PD的先前中间标记并使用似然比可提高PREDICT-PD预测算法的准确性。