The effect of cardiovascular risk on disease progression in de novo Parkinson's disease patients: An observational analysis.

Background: Currently available treatment options for Parkinson's disease are symptomatic and do not alter the course of the disease. Recent studies have raised the possibility that cardiovascular risk management may slow the progression of the disease. Objectives: We estimated the effect of baseline cardiovascular risk factors on the progression of Parkinson's disease, using measures for PD-specific motor signs and cognitive functions. Methods: We used data from 424 de novo Parkinson's disease patients and 199 age-matched controls from the observational, multicenter Parkinson's Progression Markers Initiative (PPMI) study, which included follow-up of up to 9 years. The primary outcome was the severity of PD-specific motor signs, assessed with the MDS-UPDRS part III in the "OFF"-state. The secondary outcome was cognitive function, measured with the Montreal Cognitive Assessment, Symbol Digit Modalities Test, and Letter-Number Sequencing task. Exposures of interest were diabetes mellitus, hypertension, body mass index, cardiovascular event history and hypercholesterolemia, and a modified Framingham risk score, measured at baseline. The effect of each of these exposures on disease progression was modeled using linear mixed models, including adjustment for identified confounders. A secondary analysis on the Tracking Parkinson's cohort including 1,841 patients was performed to validate our findings in an independent patient cohort. Results: Mean age was 61.4 years, and the average follow-up was 5.5 years. We found no statistically significant effect of any individual cardiovascular risk factor on the MDS-UPDRS part III progression (all 95% confidence intervals (CIs) included zero), with one exception: in the PD group, the estimated effect of a one-point increase in body mass index was 0.059 points on the MDS-UPDRS part III per year (95% CI: 0.017 to 0.102). We found no evidence for an effect of any of the exposures on the rate of change in cognitive functioning in the PD group. Similar results were observed for the Tracking Parkinson's cohort (all 95% CIs overlapped with PPMI), but the 95% CI of the effect of body mass index on the MDS-UPDRS part III progression included zero. Conclusions: Based on this analysis of two large cohorts of de novo PD patients, we found no evidence to support clinically relevant effects of cardiovascular risk factors on the clinical progression of Parkinson's disease.

Professionals' Treatment Preferences in the Prodromal Phase of Parkinson's Disease: A Discrete Choice Experiment.

BACKGROUND: In Parkinson's disease (PD), several disease-modifying treatments are being tested in (pre-)clinical trials. To successfully implement such treatments, it is important to have insight into factors influencing the professionals' decision to start disease-modifying treatments in persons who are in the prodromal stage of PD. OBJECTIVE: We aim to identify factors that professionals deem important in deciding to a start disease-modifying treatment in the prodromal stage of PD. METHODS: We used a discrete choice experiment (DCE) to elicit preferences of neurologists and last-year neurology residents regarding treatment in the prodromal phase of PD. The DCE contained 16 hypothetical choice sets in which participants were asked to choose between two treatment options. The presented attributes included treatment effect, risk of severe side-effects, risk of mild side-effects, route of administration, and annual costs. RESULTS: We included 64 neurologists and 18 last year neurology residents. Participants attached most importance to treatment effect and to the risk of severe side-effects. Participants indicated that they would discuss one of the presented treatments in daily practice more often in persons with a high risk of being in the prodromal phase compared to those with a moderate risk. Other important factors for deciding to start treatment included the amount of evidence supporting the putative treatment effect, the preferences of the person in the prodromal phase, and the life expectancy. CONCLUSION: This study provides important insights in factors that influence decision making by professionals about starting treatment in the prodromal phase of PD.

Perspectives of people living with Parkinson's disease on personalized prediction models.

BACKGROUND: There is a great need for the development of personalized prediction models (PPMs) that can predict the rate of disease progression for persons with Parkinson's disease (PD), based on their individual characteristics. In this study, we aimed to clarify the perspective of persons diagnosed with PD on the value of such hypothetical PPMs. METHODS: We organized four focus group discussions, each including five persons with PD who were diagnosed within the last 5 years. The sessions focused on what they think of receiving a personalized prediction; what outcomes are important to them; if and how the possibility of influencing the prognosis would change the way they think of personalized predictions; how they deal with the uncertainty from a PPM; and what barriers and facilitators they expect for using a PPM. RESULTS: The wish of persons with PD for receiving personalized prognostic information was highly heterogenous, for various reasons. Most persons with PD would like to receive more personalized prognostic information, mainly to better prepare themselves and their loved ones for the future. The prediction provided should be as personalized as possible, and there should be adequate supervision and coaching by a professional when providing the information. They were particularly interested in receiving prognostic information when their interventions would be available that could subsequently influence the identified prognostic factor and thereby affect the disease course beneficially. CONCLUSION: Most persons with PD in this study want more insight into their own future by means of prediction models, provided that this is explained and supervized properly by professionals. PATIENT OR PUBLIC CONTRIBUTION: Two patient-researchers were involved in the study design, conduct of the study, interpretation of the data and in preparation of the manuscript.

Personalizing decision-making for persons with Parkinson's disease: where do we stand and what to improve?

BACKGROUND: The large variety in symptoms and treatment effects across different persons with Parkinson's disease (PD) warrants a personalized approach, ensuring that the best decision is made for each individual. We aimed to further clarify this process of personalized decision-making, from the perspective of medical professionals. METHODS: We audio-taped 52 consultations with PD patients and their neurologist or PD nurse-specialist, in 6 outpatient clinics. We focused coding of the transcripts on which decisions were made and on if and how decisions were personalized. We subsequently interviewed professionals to elaborate on how and why decisions were personalized, and which decisions would benefit most from a more personalized approach. RESULTS: Most decisions were related to medication, referral or lifestyle. Professionals balanced clinical factors, including individual (disease-) characteristics, and non-clinical factors, including patients' preference, for each type of decision. These factors were often not explicitly discussed with the patient. Professionals experienced difficulties in personalizing decisions, mostly because evidence on the impact of characteristics of an individual patient on the outcome of the decision is unavailable. Categories of decisions for which professionals emphasized the importance of a more personalized perspective include choices not only for medication and advanced treatments, but also for referrals, lifestyle and diagnosis. CONCLUSIONS: Clinical decision-making is a complex process, influenced by many different factors that differ for each decision and for each individual. In daily practice, it proves difficult to tailor decisions to individual (disease-) characteristics, probably because sufficient evidence on the impact of these individual characteristics on outcomes is lacking.

Estimating the Effect of Early Treatment Initiation in Parkinson's Disease Using Observational Data.

BACKGROUND: Both patients and physicians may choose to delay initiation of dopamine replacement therapy in Parkinson's disease (PD) for various reasons. We used observational data to estimate the effect of earlier treatment in PD. Observational data offer a valuable source of evidence, complementary to controlled trials. METHOD: We studied the Parkinson's Progression Markers Initiative cohort of patients with de novo PD to estimate the effects of duration of PD treatment during the first 2 years of follow-up, exploiting natural interindividual variation in the time to start first treatment. We estimated the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III (primary outcome) and several functionally relevant outcomes at 2, 3, and 4 years after baseline. To adjust for time-varying confounding, we used marginal structural models with inverse probability of treatment weighting and the parametric g-formula. RESULTS: We included 302 patients from the Parkinson's Progression Markers Initiative cohort. There was a small improvement in MDS-UPDRS Part III scores after 2 years of follow-up for patients who started treatment earlier, and similar, but nonstatistically significant, differences in subsequent years. We found no statistically significant differences in most secondary outcomes, including the presence of motor fluctuations, nonmotor symptoms, MDS-UPDRS Part II scores, and the Schwab and England Activities of Daily Living Scale. CONCLUSION: Earlier treatment initiation does not lead to worse MDS-UPDRS motor scores and may offer small improvements. These findings, based on observational data, are in line with earlier findings from clinical trials. Observational data, when combined with appropriate causal methods, are a valuable source of additional evidence to support real-world clinical decisions. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Young Onset Parkinson's Disease: A Modern and Tailored Approach.

In people with young onset Parkinson's disease (YOPD), onset of symptoms is between 21 and 40 years of age. The distinction between YOPD and late-onset Parkinson's disease is supported by genetic differences (a genetic etiology is more common in people with YOPD) and clinical differences (e.g., dystonia and levodopa-induced dyskinesias are more common inYOPD). Moreover, people with YOPD tend to have different family and societal engagements compared to those with late-onset PD. These unique features have implications for clinical management, and call for a tailored multidisplinary approach involving shared-decision making.

Quadruple Decision Making for Parkinson's Disease Patients: Combining Expert Opinion, Patient Preferences, Scientific Evidence, and Big Data Approaches to Reach Precision Medicine.

Clinical decision making for Parkinson's disease patients is supported by a combination of three distinct information resources: best available scientific evidence, professional expertise, and the personal needs and preferences of patients. All three sources have clear value but also share several important limitations, mainly regarding subjectivity, generalizability and variability. For example, current scientific evidence, especially from controlled clinical trials, is often based on selected study populations, making it difficult to translate the outcome to the care for individual patients in everyday clinical practice. Big data, including data from real-life unselected Parkinson populations, can help to bridge this information gap. Fine-grained patient profiles created from big data have the potential to aid in identifying therapeutic approaches that will be most effective given each patient's individual characteristics, which is particularly important for a disorder characterized by such tremendous interindividual variability as Parkinson's disease. In this viewpoint, we argue that big data approaches should be acknowledged and harnessed, not to replace existing information resources, but rather as a fourth and complimentary source of information in clinical decision making, helping to represent the full complexity of individual patients. We introduce the 'quadruple decision making' model and illustrate its mode of action by showing how this can be used to pursue precision medicine for persons living with Parkinson's disease.

The Patient's Perspective on Shared Decision-Making in Advanced Parkinson's Disease: A Cross-Sectional Survey Study.

Background: Choosing between deep brain stimulation (DBS), Levodopa-Carbidopa intestinal gel (LCIG), or continuous subcutaneous Apomorphine infusion (CSAI) in advanced Parkinson's disease is a complex decision. It is paramount to combine evidence with the professional's expertise and the patient's preferences. The patient's preferences can be elicited and integrated into the treatment choice through shared decision-making (SDM). Objective: In this cross-sectional survey study we explored patient's involvement in decision-making and identified facilitators and barriers for shared decision-making (SDM) in advanced Parkinson from the patient's perspective. Methods: We invited 180 Dutch persons with Parkinson who started DBS, LCIG, or CSAI in the previous 3 years to complete a questionnaire. Questions covered three topics; (1) preferred and experienced roles in the decision process for an advanced treatment, (2) information needs to make a decision and actually received information, and (3) factors that had positively or negatively influenced shared decision-making (SDM). Results: One hundred and twenty one participants completed the questionnaire. The large majority preferred to be involved in the decision-making (93%), and most respondents had experienced an active role (85%). In about half of the respondents (47%), their preferred role did not match their experienced role; 28% had a more active role than they would have preferred. Although 77% perceived to be fully informed at the time of decision, only 41% stated they knew all three therapeutic options. Participants identified the most important facilitators for shared decision-making (SDM) at the patient's level (i.e., perceiving the decision to be his own choice), at the neurologist's level (i.e., having expertise on all treatment options, and taking time for the decision), and within the professional-patient relationship (i.e., trust and having an open discussion). The main barriers for shared decision-making (SDM) existed at the patient's level (i.e., perceiving there is no choice), neurologist's level (own treatment preference), and organizational level (i.e., no research available that compares treatments, multiple professionals involved, and lack of consultation time). Conclusions: Patients want to be involved and feel involved when choosing an advanced treatment, but often do not know all treatment options. Implementation of true patient involvement needs personalized information provision on all treatment options and improvement on how this information is communicated.

Actigraphy Detects Greater Intra-Individual Variability During Gait in Non-Manifesting LRRK2 Mutation Carriers.

BACKGROUND: With recent advances in the search for disease-modifying therapies for Parkinson's disease (PD) the importance of identifying prodromal markers becomes greater. Non-manifesting LRRK2 mutation carriers (NMC) are at risk for developing PD, and provide a population in which to identify possible markers. OBJECTIVE: The aim of this study was to test the hypothesis that NMC have differences in daily activity, fragmentation of sleep, arm swing asymmetry, and movement variability during walking, detectable by actigraphy, as compared to matched control subjects. METHODS: Eleven NMC, fourteen PD patients (4 LRRK2-PD, 10 idiopathic PD (iPD)), and twenty-nine controls wore wristbands containing an accelerometer for seven days, and performed a daily walking task. Outcome measures included daily activity, fragmentation of activity, fragmentation of sleep, arm swing asymmetry during walking, and intra-individual variability. RESULTS: Compared to healthy controls, both NMC and LRRK2/iPD showed higher intra-individual variability in activity during walking compared to healthy controls. Individuals with LRRK2-PD/iPD, but not NMC, tend to have lower activity levels, more arm swing asymmetry and less increase of arm swing with transition from slow to faster walking speed compared to healthy controls. CONCLUSION: Higher intra-individual variability of gait-associated movements might be a useful biomarker of prodromal PD. These results encourage replication in a larger sample and longitudinal analysis is warranted.

Serum Inflammatory Profile for the Discrimination of Clinical Subtypes in Parkinson's Disease.

Background: Blood levels of immune markers have been proposed to discriminate patients with Parkinson's disease (PD) from controls. However, differences between clinical PD subgroups regarding these markers still need to be identified. Objective: To investigate whether clinical phenotypes can be predicted by the assessment of immune marker profiles in the serum of PD patients. Methods: Phenotypes of clinical PD from Tübingen, Germany (n = 145) and Toronto, Canada (n = 90) were defined regarding clinical subtype, disease onset, severity, and progression as well as presence of cognitive and/or autonomic dysfunction. A panel of serum immune markers was assessed using principal component analysis (PCA) and regression models to define the marker(s) that were associated with clinical phenotypes after adjusting for potential confounders. Findings of both centers were compared for validation. Further, a [18F] FEPPA-PET was performed in a group of patients with high and low values of candidate markers for the assessment of in vivo brain microglial activation. Results: Overall, serum immune markers did not cluster to define a pro/anti-inflammatory profile in PCA. Out of 25 markers only IL-12p40 showed a trend to discriminate between PD subgroups in both cohorts which could not be replicated by [18F] FEPPA-PET. Conclusions: Assessment of cytokines in serum does not reliably differentiate clinical PD subtypes. Accompanying subtype-irrelevant inflammation in PD, dual activity, and lack of specificity of the immune markers, the complex function of microglia, probable effects of treatment, disease stage, and progression on inflammation as well as current technical limitations may limit the usefulness of serum immune markers for the differentiation of subtypes.