To the Editor,
We read with interest Dahodwala et al's recent article in Movement Disorders Clinical Practice, “Longitudinal Study of Treatment Variability for Parkinson's Disease across Specialized Centers.” 1 Using the Parkinson Outcomes Project (POP) dataset from international Centers of Excellence (COEs), it offers a critical perspective on the heterogeneity of Parkinson's disease (PD) management; their rigorous analysis of treatment patterns and their association with clinical outcomes, beyond randomized controlled trials’ limitations, enriches our understanding. The study's finding of marked treatment variability among specialized COEs (eg, levodopa use 59.3–94.6%, physical therapy referrals 13–71%, deep brain stimulation rates 2–41%) raises important questions about such disparities’ drivers and implications, and we highlight key points for further exploration.
First, the representativeness of the study population and the design of the POP dataset invite thoughtful consideration. While the dataset's size is impressive, its reliance on a convenience sample from COEs may reflect a subset of patients with better healthcare access or more typical PD presentations. This could influence the generalizability of findings to the broader PD population, particularly those in underserved regions or with atypical phenotypes, potentially underestimating the full spectrum of treatment variability. Additionally, the granularity of outcome measures, such as binary categorization of falls or broad Hoehn & Yahr staging, might limit the ability to capture subtle triggers for interventions like physical therapy or levodopa‐equivalent daily dose (LEDD) adjustments. 2
Second, there are opportunities to further refine the analysis by considering additional factors that may shape treatment decisions. While the study adjusts for key variables, aspects such as physician philosophy, center‐specific protocols, local reimbursement policies, patient preferences, and undiagnosed comorbidities could also contribute to variability. The observation that LEDD often remains unadjusted following worsening mobility or disease stage is particularly thought‐provoking and may point to unexplored influences like side effects, therapeutic thresholds, or individualized targets for motor complications. 3 Moreover, with 23.8% of treatment variable data missing, future analyses could explore advanced imputation techniques or inverse probability weighting to ensure a more comprehensive understanding of these patterns.
Third, the potential for deeper subgroup analyses remains an exciting avenue for future research. Beyond disease duration, examining variability across age of onset, motor phenotypes, genetic factors, or cognitive status could reveal distinct care patterns and unmet needs. The authors’ mention of racial and ethnic disparities further underscores the importance of targeted analyses to address inequities in PD management.
From a clinical perspective, these findings highlight the pressing need for evidence‐based guidelines on the timing of non‐pharmacological interventions and dopaminergic titration. The reactive nature of physical therapy referrals and the lack of LEDD adjustments suggest opportunities for proactive strategies and individualized care. Looking forward, methodological innovations such as causal inference models, machine learning, and qualitative studies could shed light on the complex drivers of variability. From a policy standpoint, adaptable guidelines for both specialized and general care settings, alongside quality metrics encompassing functional outcomes and patient satisfaction, are essential to ensure equitable, high‐quality PD care.
In conclusion, Dahodwala et al have made a seminal contribution to real‐world evidence on PD management. Their work inspiringly calls for exploring the roots of treatment variability, enhancing analytical approaches, and implementing best practices for consistent and equitable care. We applaud their impactful study and encourage continued investigation into these critical issues.
Author Roles
(1) Research Project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript Preparation: A. Writing of the First Draft, B. Review and Critique.
J.C.: 1A, 1B, 1C, 3A.
J.L.: 1A, 1B, 3B.
Disclosures
Ethical Compliance Statement: Ethical review and informed patient consent were not necessary for this work. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this work is consistent with those guidelines.
Funding Sources and Conflict of Interest: The authors declare that there are no funding sources or conflicts of interest relevant to this work.
Financial Disclosures for the Previous 12 Months: The authors declare that there are no additional disclosures to report.
Data Availability Statement
Data sharing is not applicable to this article because no datasets were generated or analyzed during the current study.
References
- 1. Dahodwala N, Kapogiannis T, Cruz A, Beck JC, Davis TL, Liu H, et al. Longitudinal study of treatment variability for Parkinson's disease across specialized centers. Mov Disord Clin Pract 2025;12(12):2207–2216. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Phillips O, Salles P, Liao J, Yu J, Fernandez H. Utilizing technology‐based outcome measures in the natural setting to answer intriguing clinical questions in Parkinson disease. Parkinsonism Relat Disord 2023;113:105614. 10.1016/j.parkreldis.2023.105614. [DOI] [Google Scholar]
- 3. Barbagallo G, Quattrone A. Does levodopa have a disease‐modifying effect in Parkinson's disease? Evidence from a delayed‐start trial. Mov Disord 2019;34(6):820. 10.1002/mds.27686. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data sharing is not applicable to this article because no datasets were generated or analyzed during the current study.