Network modulation following sham surgery in Parkinson’s disease
Autor: | Yilong Ma, David Eidelberg, Ji Hyun Ko, Paul J. Mattis, Chris C. Tang, Vijay Dhawan, Andrew Feigin, Matthew J. During, Michael G. Kaplitt |
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Rok vydání: | 2014 |
Předmět: |
Male
Levodopa Pathology medicine.medical_specialty Randomization Parkinson's disease Deep brain stimulation medicine.medical_treatment Models Neurological Placebo law.invention Antiparkinson Agents Placebos Double-Blind Method Randomized controlled trial law Cerebellum Limbic System medicine Humans Computer Simulation Glutamate Decarboxylase business.industry Functional Neuroimaging Sham surgery Brain Parkinson Disease Genetic Therapy General Medicine Middle Aged Placebo Effect medicine.disease Clinical trial Positron-Emission Tomography Anesthesia Commentary Female business Monte Carlo Method Metabolic Networks and Pathways medicine.drug |
Zdroj: | Journal of Clinical Investigation. 124:3656-3666 |
ISSN: | 0021-9738 |
Popis: | Patient responses to placebo and sham effects are a major obstacle to the development of therapies for brain disorders, including Parkinson's disease (PD). Here, we used functional brain imaging and network analysis to study the circuitry underlying placebo effects in PD subjects randomized to sham surgery as part of a double-blind gene therapy trial. Metabolic imaging was performed prior to randomization, then again at 6 and 12 months after sham surgery. In this cohort, the sham response was associated with the expression of a distinct cerebello-limbic circuit. The expression of this network increased consistently in patients blinded to treatment and correlated with independent clinical ratings. Once patients were unblinded, network expression declined toward baseline levels. Analogous network alterations were not seen with open-label levodopa treatment or during disease progression. Furthermore, sham outcomes in blinded patients correlated with baseline network expression, suggesting the potential use of this quantitative measure to identify "sham-susceptible" subjects before randomization. Indeed, Monte Carlo simulations revealed that a priori exclusion of such individuals substantially lowers the number of randomized participants needed to demonstrate treatment efficacy. Individualized subject selection based on a predetermined network criterion may therefore limit the need for sham interventions in future clinical trials. |
Databáze: | OpenAIRE |
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