Prodromal Parkinson's disease: hype or hope for disease-modification trials?

Abstract

The ultimate goal in Parkinson's disease (PD) research remains the identification of treatments that are capable of slowing or even halting the progression of the disease. The failure of numerous past disease-modification trials in PD has been attributed to a variety of factors related not only to choosing wrong interventions, but also to using inadequate trial designs and target populations. In patients with clinically established PD, neuronal pathology may already have advanced too far to be modified by any intervention. Based on such reasoning, individuals in yet prediagnostic or prodromal disease stages, may provide a window of opportunity to test disease-modifying strategies. There is now sufficient evidence from prospective studies to define diagnostic criteria for prodromal PD and several approaches have been studied in observational cohorts. These include the use of PD-risk algorithms derived from multiple established risk factors for disease as well as follow-up of cohorts with single defined prodromal markers like hyposmia, rapid eye movement sleep behavior disorders, or PD gene carriers. In this review, we discuss recruitment strategies for disease-modification trials in various prodromal PD cohorts, as well as potential trial designs, required trial durations, and estimated sample sizes. We offer a concluding outlook on how the goal of implementing disease-modification trials in prodromal cohorts might be achieved in the future.

Keywords: Epidemiology; Neuroprotection; Neuroprotective; Preclinical; Prevention; Preventive; Probability; Randomized controlled trial.

Fig. 1

Schematic structure of MDS research criteria for prodromal PD. The approach by the MDS task force entails 1. assessment of pretest probability for prodromal PD based on age, 2. the sequential addition of LRs of various risk and prodromal markers, and 3. the calculation of post-test probabilities using the above information (see Berg  et al. 2015 [24] for further details). Modified from Mahlknecht et al. 2018 [34], with kind permission from Wiley. * Markers added with the 2019 update of the MDS research criteria for prodromal PD [29]. EDS, excessive daytime somnolence; LR, likelihood ratio; OH, orhtostatic hypotension; PD, Parkinson’s disease; SN, substantia nigra

Fig. 2

Potential screening strategies for target populations for disease-modification trials in the general community assuming three different target populations (PPV > 60%). First column: individuals with hyposmia and DAT-Deficit; real numbers from the PARS study that used olfactory testing as first remote screening step and DAT-Scan as a second screen are presented [43]. These include losses to follow up. Second column: patients with idiopathic RBD and further marker(s) that indicate increased risk for early conversion as hyposmia, abnormal color vision, or subtle motor dysfunction (approximately one third of idiopathic RBD patients) [13, 44]; the identification of idiopathic RBD patients from the general community is modeled using a questionnaire as a first remote screening step (assuming a prevalence of probable RBD of 5%) [46, 48] and polysomnography as a second screening step (assuming that approximately one sixth of probable RBD cases are confirmed as having idiopathic RBD) [45, 46]. Third column: Individuals with probable prodromal PD according to the MDS research criteria as modeled from data of the prospective population-based Bruneck Study [34]; remote screening includes a questionnaire-based assessment and brief odor-identification test. The model envisages that all participants reaching a post-test probability for prodromal PD of > 10% (one quarter of participants) are invited for the in person screening including a motor examination and transcranial sonography. Estimated numbers necessary for remote screening are derived from the prevalence of probable prodromal PD (i.e. 2.2%). Please note that only multipliers in the first column account for losses to follow-up, whereas the ones in the second and third columns do not