Dalla Lana School of Public Health

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• All welcome. Registration: 

The CANSSI Ontario STatistics Seminars (CAST) Series is proud to host a talk by:

Dr. Terry Therneau
Professor of Biostatistics
Consultant Division of Clinical Trials and Biostatistics
Department of Quantitative Health Sciences
Mayo Clinic

Talk Title:
Challenges in Modeling Cognitive Aging

Date: Friday, June 19, 2026

Time: 11:00 AM-12 PM ET

Format: Hybrid (In-person and Zoom)

In-person Location:
Rooms 10031 & 10032
The University of Toronto
700 University Avenue
Toronto, ON

All welcome. Registration: https://canssiontario.utoronto.ca/event/cast-terry-therneau/

Abstract:
In this talk I will discuss key issues in modeling cognitive aging for both direct measures of cognition (e.g. memory tests and activities of daily living) and assessment of underlying processes via biomarkers (e.g. amyloid PET or serum assays). The fundamental challenge is that the timeline of the underlying processes will often span 20 or more years in a given person, while the median observation time for any given participant is normally no more than 4-6 years even for long term studies. Challenges include the presence of substantial between subject variation in the age of onset of the process. For amyloid, for instance, APOE e4+ shifts onset by about 6 years, remaining per subject variation is about 9. There is also variation in the availability of measurements since different cognitive tests and blood samples are collected at different times in different studies. Modeling and inference is further challenged by a low signal-to-noise ratio for many markers. Further challenges arise from informative censoring. The goal is to understand how multiple markers relate to any given underlying pathology, and to study how multiple underlying pathologies may interact. One subject may exhibit pathology A earlier than others while others may exhibit pathology B earlier.

Several different modeling approaches have been proposed in the literature, but often focus on only one or two of the above. A successful modeling approach in this millieu needs to effectively integrate as much information as possible, across patients, ages, and markers. Examples we have found useful are multi-marker nonlinear mixed effects models and hidden Markov models; each has both strengths and weakness, and both are computationally challenging.

Speaker Profile:
Terry M. Therneau, Ph.D., is a Mayo Clinic statistician engaged in clinical research programs, with interests in both medical and statistical areas. Their clinical and research focus spans aging and dementia, Alzheimer’s disease, liver disease, and survival analysis. Dr. Therneau’s research aims to advance patient care through the development of multistate time-to-event models, the application of such models to disease progression, and the creation of reliable and effective software for these analyses.