Disease progression strikingly differs in research and real-world Parkinson's populations

Brett K Beaulieu-Jones; Francesca Frau; Sylvie Bozzi; Karen J Chandross; M Judith Peterschmitt; Caroline Cohen; Catherine Coulovrat; Dinesh Kumar; Mark J Kruger; Scott L Lipnick; Lane Fitzsimmons; Isaac S Kohane; Clemens R Scherzer

doi:10.1038/s41531-024-00667-5

Disease progression strikingly differs in research and real-world Parkinson's populations

NPJ Parkinsons Dis. 2024 Mar 13;10(1):58. doi: 10.1038/s41531-024-00667-5.

Authors

Brett K Beaulieu-Jones^{1

2

3

4

5}, Francesca Frau⁶, Sylvie Bozzi⁷, Karen J Chandross⁸, M Judith Peterschmitt⁹, Caroline Cohen¹⁰, Catherine Coulovrat¹¹, Dinesh Kumar¹¹, Mark J Kruger⁹, Scott L Lipnick¹², Lane Fitzsimmons¹², Isaac S Kohane¹², Clemens R Scherzer^{13

14

15}

Affiliations

¹ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA. beaulieujones@uchicago.edu.
² APDA Center for Advanced Parkinson Research of Harvard Medical School and Brigham and Women's Hospital, Boston, MA, 02115, USA. beaulieujones@uchicago.edu.
³ Precision Neurology Program of Brigham & Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA. beaulieujones@uchicago.edu.
⁴ Department of Medicine, University of Chicago, Chicago, IL, 60615, USA. beaulieujones@uchicago.edu.
⁵ Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA. beaulieujones@uchicago.edu.
⁶ Sanofi R&D, Data and Data Science, Frankfurt, Germany.
⁷ Sanofi Health Economics and Value Assessment, Sanofi, Paris, France.
⁸ Sanofi R&D, Bridgewater, NJ, USA.
⁹ Sanofi Genzyme, Clinical Development Neurology, Cambridge, MA, USA.
¹⁰ Sanofi R&D, Paris, France.
¹¹ Sanofi Translational Sciences, Framingham, MA, 01701, USA.
¹² Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA.
¹³ APDA Center for Advanced Parkinson Research of Harvard Medical School and Brigham and Women's Hospital, Boston, MA, 02115, USA. clemens.scherzer@yale.edu.
¹⁴ Precision Neurology Program of Brigham & Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA. clemens.scherzer@yale.edu.
¹⁵ Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA. clemens.scherzer@yale.edu.

Abstract

Characterization of Parkinson's disease (PD) progression using real-world evidence could guide clinical trial design and identify subpopulations. Efforts to curate research populations, the increasing availability of real-world data, and advances in natural language processing, particularly large language models, allow for a more granular comparison of populations than previously possible. This study includes two research populations and two real-world data-derived (RWD) populations. The research populations are the Harvard Biomarkers Study (HBS, N = 935), a longitudinal biomarkers cohort study with in-person structured study visits; and Fox Insights (N = 36,660), an online self-survey-based research study of the Michael J. Fox Foundation. Real-world cohorts are the Optum Integrated Claims-electronic health records (N = 157,475), representing wide-scale linked medical and claims data and de-identified data from Mass General Brigham (MGB, N = 22,949), an academic hospital system. Structured, de-identified electronic health records data at MGB are supplemented using a manually validated natural language processing with a large language model to extract measurements of PD progression. Motor and cognitive progression scores change more rapidly in MGB than HBS (median survival until H&Y 3: 5.6 years vs. >10, p < 0.001; mini-mental state exam median decline 0.28 vs. 0.11, p < 0.001; and clinically recognized cognitive decline, p = 0.001). In real-world populations, patients are diagnosed more than eleven years later (RWD mean of 72.2 vs. research mean of 60.4, p < 0.001). After diagnosis, in real-world cohorts, treatment with PD medications has initiated an average of 2.3 years later (95% CI: [2.1-2.4]; p < 0.001). This study provides a detailed characterization of Parkinson's progression in diverse populations. It delineates systemic divergences in the patient populations enrolled in research settings vs. patients in the real-world. These divergences are likely due to a combination of selection bias and real population differences, but exact attribution of the causes is challenging. This study emphasizes a need to utilize multiple data sources and to diligently consider potential biases when planning, choosing data sources, and performing downstream tasks and analyses.

Abstract

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