Natural trajectory subclasses of cognitive impairment in breast cancer patients experiencing insomnia.

Abstract

Cancer-related cognitive impairment (CRCI) has traditionally been assessed in a dichotomous manner. Identifying subclasses of CRCI and novel biomarkers can improve the accuracy of identifying patients most at risk for CRCI. A total of 139 breast cancer patients undergoing chemotherapy completed neurocognitive batteries over 12 months. Growth mixture modeling (GMM) was used to determine latent subgroups based on different trajectories of cognitive test performance across the four time points. Additionally, the authors collected peripheral blood to measure neuron-derived exosomes (NDE). Mean cognitive performance improved significantly over time (p < .001). However, GMM identified three distinct latent subgroups: patients with stable, high performance (class 1, N = 45), patients with variable low performance (class 2, N = 15), and patients with average performance who improved over time (class 3, N = 79). Cognitive subclass 2 was characterized by significantly lower education levels than the other two classes (p = .001). Cognitive subclass 1 had fewer racial/ethnic minority patients than the other two classes (p = .015). Cognitive subclasses did not differ significantly in any other demographic or clinical characteristic. There were no significant differences observed by NDE. There are multiple distinct longitudinal trajectories of CRCI and these may be influenced by social determinants of health such as education and race/ethnicity. Future research can focus on ways to administer interventions earlier to those at most risk for CRCI and continue to explore novel biomarkers of CRCI.