Improving estimation of Parkinson\u2019s disease risk\u2014the enhanced PREDICT-PD algorithm

Jonathan P Bestwick,Gavin Giovannoni,Andrew J Lees,Jack Cuzick,Daniel Rack,Alastair J Noyce,Anette E Schrag,Cristina Simonet,Richard N Rees,Mark Jitlal,Stephen D Auger

doi:10.1038/s41531-021-00176-9

Jonathan P Bestwick, Gavin Giovannoni + Show 9 more

Open Access

https://doi.org/10.1038/s41531-021-00176-9

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Abstract

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.

Highlights

Neurodegeneration preceding a formal diagnosis of Parkinson’s disease (PD) is associated with identifiable motor and non-motor features
All the factors which were available for inclusion into risk estimates in either the basic or enhanced PREDICT-PD risk estimates are outlined in Table 2, alongside the most recent MDS prodromal criteria likelihood ratios[3]
Shown in the figures are the distributions revised risk according to age for the enhanced PREDICT-PD using the basic PREDICT-PD algorithm, the enhanced PREDICT-PD

Summary

INTRODUCTION

Neurodegeneration preceding a formal diagnosis of Parkinson’s disease (PD) is associated with identifiable motor and non-motor features. We sought to refine the PREDICT-PD algorithm, first by changing the method of risk estimation from odds ratios to likelihood ratios and by incorporating objective assessment of tapping speed and smell, and probable RBD into risk estimates. To assess whether these steps improved risk estimation, we compared the distributions of risk derived from the enhanced algorithm to those using the basic PREDICT-PD algorithm[1,4], and to the MDS prodromal criteria algorithm[2,3]. We assessed the relationship between risk estimates and subclinical striatal dopamine depletion measured by dopamine transporter imaging (DaT-SPECT) in a subgroup of the participants who have previously been reported using the basic algorithm[6]

RESULTS

Objective motor impairmentb

DISCUSSION