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Addressing the need for standardization of symptomatic medication documentation in Parkinson's disease clinical research: A call to action
Journal article   Open access   Peer reviewed

Addressing the need for standardization of symptomatic medication documentation in Parkinson's disease clinical research: A call to action

Mikayla Spott, Monica Javidnia, Anne Pedata, Martijn Müller, Laura Carrillo, Tanya Simuni, Gennaro Pagano, Kevin Kwok, Klaus Romero and Diane Stephenson
Journal of Parkinson's disease, v 15(1), pp 227-235
01 Feb 2025
PMID: 39973486
url
https://doi.org/10.1177/1877718X241305711View
Published, Version of Record (VoR) Open

Abstract

Antiparkinson Agents - therapeutic use Biomedical Research - standards Clinical Trials as Topic - standards Documentation - standards Humans Parkinson Disease - drug therapy
People with Parkinson's disease (PD) are prescribed a variety of medications to mitigate symptoms and improve their quality of life. These symptomatic therapies cover a range of pharmacological classes, including classical dopaminergic treatments, other antiparkinsonian agents, and pharmacotherapies for non-PD conditions. Often, medications are prescribed for concomitant use and in increasing doses, particularly as the disease progresses. Documentation of these interventions in clinical trials is necessary to accurately capture medication usage, compare medication utilization across different studies, understand factors contributing to experimental therapeutic response, and analyze clinical trial data in a precise manner. At the present time, there is no current international standard for how these medications are documented within clinical trials. As a case example, we will highlight medication use documentation in a large international multicenter observational study commonly used as a reference for design of clinical trials. This review aims to raise awareness within the scientific community of the importance of proper medication documentation and the need for standardization to harmonize prescriptive practices, improve treatment interpretability, and perform consistently robust analyses from clinical trials data.

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Industry collaboration
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Web of Science research areas
Neurosciences
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