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Deep brain stimulation (DBS) is part of state-of-the-art treatment for medically refractory Parkinson's disease, essential tremor or primary dystonia. However, there are multiple movement disorders that present after a static brain lesion and that are frequently refractory to medical treatment. Using Holmes tremor (HT) as an example, we discuss the effectiveness of currently available treatments and, performing simulations using a Markov Chain approach, propose that DBS with iterative parameter optimization is expected to be more effective than an approach based on sequential trials of pharmacological agents. Since, in DBS studies for HT, the thalamus is a frequently chosen target, using data from previous studies of lesion connectivity mapping in HT, we compared the connectivity of thalamic and non-thalamic targets with a proxy of the HT network, and found a significantly higher connectivity of thalamic DBS targets in HT. The understanding of brain networks provided by analysis of functional connectivity may thus provide an informed framework for proper surgical targeting of individual patients. Based on these findings, we argue that there is an ethical imperative to at least consider surgical options in patients with uncommon movement disorders, while simultaneously providing consistent information regarding the expected effectiveness and risks, even in a scenario of surgical-risk aversion. An approach based on n-of-1 DBS trials may ultimately significantly improve outcomes while informing on optimal therapeutic targets and parameter settings for HT and other disabling and rare movement disorders. [ABSTRACT FROM AUTHOR]

Deep brain stimulation (DBS) is part of state-of-the-art treatment for medically refractory Parkinson’s disease, essential tremor or primary dystonia. However, there are multiple movement disorders that present after a static brain lesion and that are frequently refractory to medical treatment. Using Holmes tremor (HT) as an example, we discuss the effectiveness of currently available treatments and, performing simulations using a Markov Chain approach, propose that DBS with iterative parameter optimization is expected to be more effective than an approach based on sequential trials of pharmacological agents. Since, in DBS studies for HT, the thalamus is a frequently chosen target, using data from previous studies of lesion connectivity mapping in HT, we compared the connectivity of thalamic and non-thalamic targets with a proxy of the HT network, and found a significantly higher connectivity of thalamic DBS targets in HT. The understanding of brain networks provided by analysis of functional connectivity may thus provide an informed framework for proper surgical targeting of individual patients. Based on these findings, we argue that there is an ethical imperative to at least consider surgical options in patients with uncommon movement disorders, while simultaneously providing consistent information regarding the expected effectiveness and risks, even in a scenario of surgical-risk aversion. An approach based on n-of-1 DBS trials may ultimately significantly improve outcomes while informing on optimal therapeutic targets and parameter settings for HT and other disabling and rare movement disorders.

Background and Significance: Parallel-group randomized controlled trials (PG-RCTs) are the gold standard for detecting differences in mean improvement across treatment conditions. However, PG-RCTs provide limited information about individuals, making them poorly optimized for quantifying the relationship of a biomarker measured at baseline with treatment response. In N-of-1 trials, an individual subject moves between treatment conditions to determine their specific response to each treatment. Aggregated N-of-1 trials analyze a cohort of such participants, and can be designed to optimize both statistical power and clinical or logistical constraints, such as allowing all participants to begin with an open-label stabilization phase to facilitate the enrollment of more acutely symptomatic participants. Here, we describe a set of statistical simulation studies comparing the power of four different trial designs to detect a relationship between a predictive biomarker measured at baseline and subjects' specific response to the PTSD pharmacotherapeutic agent prazosin.Methods: Data was simulated from 4 trial designs: (1) open-label; (2) open-label + blinded discontinuation; (3) traditional crossover; and (4) open label + blinded discontinuation + brief crossover (the N-of-1 design). Designs were matched in length and assessments. The primary outcome, analyzed with a linear mixed effects model, was whether a statistically significant association between biomarker value and response to prazosin was detected with 5% Type I error. Simulations were repeated 1,000 times to determine power and bias, with varied parameters.Results: Trial designs 2 & 4 had substantially higher power with fewer subjects than open label design. Trial design 4 also had higher power than trial design 2. Trial design 4 had slightly lower power than the traditional crossover design, although power declined much more rapidly as carryover was introduced.Conclusions: These results suggest that an aggregated N-of-1 trial design beginning with an open label titration phase may provide superior power over open label or open label and blinded discontinuation designs, and similar power to a traditional crossover design, in detecting an association between a predictive biomarker and the clinical response to the PTSD pharmacotherapeutic prazosin. This is achieved while allowing all participants to spend the first 8 weeks of the trial on open-label active treatment.

Background: The growing consumer digital tools market has made using individual health data to inform lifestyle changes more accessible than ever. The n-of-1 trial–a single participant, multiple crossover, comparative effectiveness trial–offers methodological tools that link interventions directly with personalized outcomes to determine the best treatment for an individual. We have developed a complete digital platform to support self-directed n-of-1 trials, comprised of virtual study on-boarding, visual informed consent, device integrations, in-app assessments, and automated data analysis.Objective: To evaluate the n-of-1 platform, a pilot study was launched to investigate the effects of commonly consumed substances on cognition. The purpose of the study is to allow an individual to measure the effect of 2 treatments (caffeine alone vs. caffeine + L-theanine) on 3 measures of cognitive performance: creative thinking, processing speed, and visual attention. Upon completion of the study, individuals receive personalized results that compare the impact of the two treatments on each of the cognitive performance measures.Methods: After the onboarding process, participants are randomized to a study length (5, 15, or 27 days), starting treatment (caffeine or caffeine + L-theanine), and app notification frequency (light, moderate). Each trial begins with a baseline period, during which participants abstain from either treatment, followed by 2 randomized counterbalanced treatment sequences (either ABBA or BAAB). Throughout the trial, daily tests assess participant cognitive performance. These tests are digital versions of the Remote Associates Test, Stroop Test, and Trail Making Test, and are implemented directly in the n-of-1 mobile application (“N1”). Assessments are completed at a fixed time, defined by the individual during study setup. Treatments are taken daily within a fixed time window prior to the user-defined assessment time. Cognitive assessment results are analyzed using a linear model with factors for treatment and block, and each treatment is compared to baseline.Results: We launched our N1 app on the Apple App Store in mid-October 2019 and recruited over 40 participants within the first month.Conclusion: This platform provides individuals the opportunity to investigate their response to treatments through n-of-1 methods, empowering them to make data-driven, personalized lifestyle choices.Trial Registration:www.ClinicalTrials.gov, identifier: NCT04056650.

There is limited information available concerning the treatment of daytime somnolence associated with Parkinson’s disease (PD); the most frequently applied therapeutic strategies include decreasing the dose of dopamine agonists or adding potential wake-promoting agents. There is recent data from a placebo-controlled trial concluding on a non-significant trend in favor of caffeine. We aimed to evaluate the efficacy of espresso-coffee in the treatment of daytime somnolence in PD. To evaluate the efficacy of espresso-coffee in the treatment of daytime somnolence in PD, we have conducted multiple single-patient (n-of-1) clinical trials comparing regular espresso coffee to decaffeinated coffee in PD patients presenting moderate to severe daytime somnolence defined as an Epworth Sleepiness Scale (ESS) score >9. Each single-patient (n-of-1) trial included a sequence of three crossovers (two treatment periods separated by two days of washout). Four patients were included in the studies and three completed the three pairs of treatment periods. In two of the four patients, espresso coffee was considered beneficial. This study concludes that multiple single patient trials are feasible in PD and suggests that espresso-coffee may have a beneficial effect on daytime somnolence in some patients. These results cannot be generalized beyond the patients included in these trials.

There is limited information available concerning the treatment of daytime somnolence associated with Parkinson's disease (PD); the most frequently applied therapeutic strategies include decreasing the dose of dopamine agonists or adding potential wake-promoting agents. There is recent data from a placebo-controlled trial concluding on a non-significant trend in favor of caffeine. We aimed to evaluate the efficacy of espresso-coffee in the treatment of daytime somnolence in PD. To evaluate the efficacy of espresso-coffee in the treatment of daytime somnolence in PD, we have conducted multiple single-patient (n-of-1) clinical trials comparing regular espresso coffee to decaffeinated coffee in PD patients presenting moderate to severe daytime somnolence defined as an Epworth Sleepiness Scale score >9. Each single-patient (n-of-1) trial included a sequence of three crossovers (two treatment periods separated by two days of washout). Four patients were included in the studies and three completed the three pairs of treatment periods. In two of the four patients, espresso coffee was considered beneficial. This study concludes that multiple single patient trials are feasible in PD and suggests that espresso-coffee may have a beneficial effect on daytime somnolence in some patients. These results cannot be generalized beyond the patients included in these trials. [ABSTRACT FROM AUTHOR]