What Huntington’s Disease Patients Say About Their Illness: An Online Direct-to-Participant Pilot Study

Article type: Research Article

Authors: Anderson, Karen E.^{a; *} | Arbatti, Lakshmi^b | Hosamath, Abhishek^b | Feigin, Andrew^{c; d} | Goldstein, Jody^d | Kayson, Elise^d | Kinsler, Brett L.^d | Falanga, Lauren^d | Denise, Lynn^d | Carlozzi, Noelle E.^e | Frank, Samuel^f | Jackson, Katie^g | Kostyk, Sandra^h | Purks, Jennifer L.ⁱ | Serbin, Kenneth P.^j | Kinel, Shari^d | Beck, Christopher A.ⁱ | Shoulson, Ira^{b; i}

Affiliations: [a] Georgetown University, Washington, DC, USA | [b] Grey Matter Technologies/Modality.AI, San Francisco, CA, USA | [c] NYU Langone Health, New York, NY, USA | [d] Huntington Study Group, Rochester, NY, USA | [e] University of Michigan, Ann Arbor, Michigan, USA | [f] Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, USA | [g] Help4HD, Elk Grove, CA, USA | [h] The Ohio State University, Columbus, OH, USA | [i] University of Rochester, Rochester, NY, USA | [j] University of San Diego, San Diego, CA, USA

Correspondence: [*] Correspondence to: Karen E. Anderson, MD, Department of Psychiatry, Research Division, 2115 Wisconsin Ave NW, Washington, DC 20007, USA. Tel.: +1 202 687 4870; E-mail kea45@georgetown.edu.

Abstract: Background:Direct-to-participant online reporting facilitates the conduct of clinical research by increasing access and clinically meaningful patient engagement. Objective:We assessed feasibility of online data collection from adults with diagnosed Huntington’s disease (HD) who directly reported their problems and impact in their own words. Methods:Data were collected online from consenting United States residents who self-identified as 1) having been diagnosed with Huntington’s disease, 2) able to ambulate independently, and 3) self-sufficient for most daily needs. Data for this pilot study were collected using the Huntington Study Group myHDstory online research platform. The Huntington Disease Patient Report of Problems (HD-PROP), an open-ended questionnaire, was used to capture verbatim bothersome problems and functional impact. Natural language processing, human-in-the-loop curation of verbatim reports involving clinical and experience experts, and machine learning classified verbatim-reports into clinically meaningful symptoms. Results:All 8 questionnaires in the online pilot study were completed by 345 participants who were 60.9% men, 34.5±9.9 (mean±SD) years old, and 9.5±8.4 years since HD diagnosis. Racial self-identification was 46.4% Caucasian, 28.7% African American, 15.4% American Indian/Alaska Native, and 9.5% other. Accuracy of verbatim classification was 99%. Non-motor problems were the most frequently reported symptoms; depression and cognitive impairment were the most common. Conclusions:Online research participation was feasible for a diverse cohort of adults who self-reported an HD diagnosis and predominantly non-motor symptoms related to mood and cognition. Online research tools can help inform what bothers HD patients, identify clinically meaningful outcomes, and facilitate participation by diverse and under-represented populations.

Keywords: Patient-reported outcomes, Huntington’s disease, machine learning, self-report

DOI: 10.3233/JHD-231520

Journal: Journal of Huntington's Disease, vol. 13, no. 2, pp. 237-248, 2024