Mathematical modeling of glucose regulation and sleep resting heart rate to predict risk of metabolic dysregulation in cancer survivors

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Authors: Yue Liao, Christine Spadola, Souvik Roy
Cited by: 1
References: 39

Abstract

Sleep-related alterations in glucose metabolism and autonomic regulation play a critical role in the early development of type 2 diabetes mellitus (T2DM), especially among cancer survivors. Motivated by this interplay, we develop a physiologically informed mathematical model linking nocturnal glucose levels with resting heart rate dynamics. The model comprises of a coupled system of ordinary differential equations, and is fitted to wearable sensor data using particle swarm optimization. Sensitivity analysis is carried out to obtain the key parameters driving metabolic dysregulation, enabling the formulation of a personalized risk score. Successful validation using synthetic patient data and cancer survivor patient data suggests that this framework provides a non-invasive, interpretable tool for early T2DM risk stratification based on nocturnal physiological patterns.

Fields of Study & Subjects

Heart Rate Variability and Autonomic Control Diabetes Management and Research Cancer survivorship and care

Publication details

Journal / source
PLoS ONE
Publisher
Public Library of Science (PLoS)
Volume
21
Issue
1
Pages
e0339461–e0339461
Publication date
2 January 2026
Language
EN