INS NYC 2024 Program

Custom Content	Poster Session 04 Program Schedule 02/15/2024 12:00 pm - 01:15 pm Room: Shubert Complex (Posters 1-60) Poster Session 04: Neuroimaging \| Neurostimulation/Neuromodulation \| Teleneuropsychology/Technology Final Abstract #2 Poster Symposium: Novel Technology-Based Approaches for Cognitive Assessment — Abstract 1 Evaluation of longitudinal remote smartphone cognitive assessments for early detection and longitudinal monitoring in frontotemporal lobar degeneration Mark Sanderson-Cimino, UCSF Memory and Aging Center, San Francisco, United States Annie Clark, UCSF Memory and Aging Center, San Francisco, United States Kaitlin Casaletto, UCSF Memory and Aging Center, San Francisco, United States Jack Taylor, UCSF Memory and Aging Center, San Francisco, United States Hilary Heuer, UCSF Memory and Aging Center, San Francisco, United States Amy Wise, UCSF Memory and Aging Center, San Francisco, United States Sreya Dhanam, UCSF Memory and Aging Center, San Francisco, United States Julia Fields, Mayo Clinic, Rochester, United States Jason Hassenstab, Washington University in St. Louis, St. Louis, United States Bradley Boeve, Mayo Clinic, Rochester, United States Adam Boxer, UCSF Memory and Aging Center, San Francisco, United States Adam Staffaroni, UCSF Memory and Aging Center, San Francisco, United States Category: Dementia (Non-AD) Keyword 1: computerized neuropsychological testing Keyword 2: assessment Objective: Frontotemporal lobar degeneration (FTLD) is a neuropathological entity that can cause early-onset dementia. Clinical trials of treatments targeting FTLD may be faced with difficulty recruiting enough participants due to the rarity of disease in addition to behavioral and motor features that prevent in-person participation. Decentralized clinical trial designs are therefore attractive but require validated tools for remote symptom tracking. Our previous cross-sectional analyses showed that cognitive tasks deployed via the ALLFTD Mobile App are reliable and sensitive to early stages of disease. The current study aims to understand the relationship between baseline diagnosis and performance on unsupervised smartphone cognitive testing over 18 months. Participants and Methods: The study included 259 participants (mean baseline age 52.75, SD=14.92; mean education=16.40, SD=2.30; 57.5% women) who were asymptomatic (Clinical Dementia Rating plus FTLD (CDR®+NACC-FTLD)= 0 [n=153]), prodromal (CDR®+NACC-FTLD= 0.5 [n=50]), or symptomatic (CDR®+NACC-FTLD>0.5 [n=56]) at baseline. Participants completed smartphone versions of Stroop, flanker, card sorting, and 2-back tasks, as well as a novel associative memory task, through the ALLFTD app at each assessment session. Sessions were repeated 3 times over the course of 12 days. This triplicate of sessions was repeated every 6 months for up to 18 months. Linear mixed effects models investigated the interaction of baseline disease severity (CDR®+NACC FTLD box score) and time as a predictor of the cognitive score at each assessment. All models controlled for age, education, sex, and a person-specific random intercept. Results: Greater baseline disease severity was associated with lower cognitive scores across all tasks (b range: -0.22 to -0.11; p’s < 0.001). Greater baseline disease severity predicted faster rates of decline on the memory, flanker, 2-back, and Stroop tasks (b range: -0.003 to -0.0002; p<.05). When the sample was restricted to asymptomatic and prodromal individuals (CDR®+NACC FTLD<1), greater baseline disease severity was still associated with lower scores across all tasks (b range: -0.43 to -0.18; p’s<0.002) and predicted faster rates of decline on the 2-back and flanker tasks (b range: -0.0006 to -0.0004; p’s<0.02). Conclusions: This study provides initial evidence that longitudinal cognitive measurements in a subset of tasks collected via smartphone are sensitive to differences in rate of decline across baseline disease severity.

Custom Content

02/15/2024
12:00 pm - 01:15 pm
Room: Shubert Complex (Posters 1-60)

Poster Session 04: Neuroimaging | Neurostimulation/Neuromodulation | Teleneuropsychology/Technology

Final Abstract #2

Poster Symposium: Novel Technology-Based Approaches for Cognitive Assessment — Abstract 1

Evaluation of longitudinal remote smartphone cognitive assessments for early detection and longitudinal monitoring in frontotemporal lobar degeneration

Mark Sanderson-Cimino, UCSF Memory and Aging Center, San Francisco, United States
Annie Clark, UCSF Memory and Aging Center, San Francisco, United States
Kaitlin Casaletto, UCSF Memory and Aging Center, San Francisco, United States
Jack Taylor, UCSF Memory and Aging Center, San Francisco, United States
Hilary Heuer, UCSF Memory and Aging Center, San Francisco, United States
Amy Wise, UCSF Memory and Aging Center, San Francisco, United States
Sreya Dhanam, UCSF Memory and Aging Center, San Francisco, United States
Julia Fields, Mayo Clinic, Rochester, United States
Jason Hassenstab, Washington University in St. Louis, St. Louis, United States
Bradley Boeve, Mayo Clinic, Rochester, United States
Adam Boxer, UCSF Memory and Aging Center, San Francisco, United States
Adam Staffaroni, UCSF Memory and Aging Center, San Francisco, United States

Category: Dementia (Non-AD)

Keyword 1: computerized neuropsychological testing
Keyword 2: assessment

Objective:

Frontotemporal lobar degeneration (FTLD) is a neuropathological entity that can cause early-onset dementia. Clinical trials of treatments targeting FTLD may be faced with difficulty recruiting enough participants due to the rarity of disease in addition to behavioral and motor features that prevent in-person participation. Decentralized clinical trial designs are therefore attractive but require validated tools for remote symptom tracking. Our previous cross-sectional analyses showed that cognitive tasks deployed via the ALLFTD Mobile App are reliable and sensitive to early stages of disease. The current study aims to understand the relationship between baseline diagnosis and performance on unsupervised smartphone cognitive testing over 18 months.

Participants and Methods:

The study included 259 participants (mean baseline age 52.75, SD=14.92; mean education=16.40, SD=2.30; 57.5% women) who were asymptomatic (Clinical Dementia Rating plus FTLD (CDR®+NACC-FTLD)= 0 [n=153]), prodromal (CDR®+NACC-FTLD= 0.5 [n=50]), or symptomatic (CDR®+NACC-FTLD>0.5 [n=56]) at baseline. Participants completed smartphone versions of Stroop, flanker, card sorting, and 2-back tasks, as well as a novel associative memory task, through the ALLFTD app at each assessment session. Sessions were repeated 3 times over the course of 12 days. This triplicate of sessions was repeated every 6 months for up to 18 months. Linear mixed effects models investigated the interaction of baseline disease severity (CDR®+NACC FTLD box score) and time as a predictor of the cognitive score at each assessment. All models controlled for age, education, sex, and a person-specific random intercept.

Results:

Greater baseline disease severity was associated with lower cognitive scores across all tasks (b range: -0.22 to -0.11; p’s < 0.001). Greater baseline disease severity predicted faster rates of decline on the memory, flanker, 2-back, and Stroop tasks (b range: -0.003 to -0.0002; p<.05). When the sample was restricted to asymptomatic and prodromal individuals (CDR®+NACC FTLD<1), greater baseline disease severity was still associated with lower scores across all tasks (b range: -0.43 to -0.18; p’s<0.002) and predicted faster rates of decline on the 2-back and flanker tasks (b range: -0.0006 to -0.0004; p’s<0.02).

Conclusions:

This study provides initial evidence that longitudinal cognitive measurements in a subset of tasks collected via smartphone are sensitive to differences in rate of decline across baseline disease severity.