Browsing by Subject "cancer-related cognitive impairment"

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    Associating persistent self-reported cognitive decline with neurocognitive decline in older breast cancer survivors using machine learning: The Thinking and Living with Cancer study
    (Elsevier, 2022-11) Van Dyk, Kathleen; Ahn, Jaeil; Zhou, Xingtao; Zhai, Wanting; Ahles, Tim A.; Bethea, Traci N.; Carroll, Judith E.; Cohen, Harvey Jay; Dilawari, Asma A.; Graham, Deena; Jacobsen, Paul B.; Jim, Heather; McDonald, Brenna C.; Nakamura, Zev M.; Patel, Sunita K.; Rentscher, Kelly E.; Saykin, Andrew J.; Small, Brent J.; Mandelblatt, Jeanne S.; Root, James C.; Radiology and Imaging Sciences, School of Medicine
    Introduction: Many cancer survivors report cognitive problems following diagnosis and treatment. However, the clinical significance of patient-reported cognitive symptoms early in survivorship can be unclear. We used a machine learning approach to determine the association of persistent self-reported cognitive symptoms two years after diagnosis and neurocognitive test performance in a prospective cohort of older breast cancer survivors. Materials and Methods: We enrolled breast cancer survivors with non-metastatic disease (n=435) and age- and education-matched non-cancer controls (n=441) between August 2010 and December 2017 and followed until January 2020; we excluded women with neurological disease and all women passed a cognitive screen at enrollment. Women completed the FACT-Cog Perceived Cognitive Impairment (PCI) scale and neurocognitive tests of attention, processing speed, executive function, learning, memory and visuospatial ability, and timed activities of daily living assessments at enrollment (pre-systemic treatment) and annually to 24 months, for a total of 59 individual neurocognitive measures. We defined persistent self-reported cognitive decline as clinically meaningful decline (3.7+ points) on the PCI scale from enrollment to twelve months with persistence to 24 months. Analysis used four machine learning models based on data for change scores (baseline to twelve months) on the 59 neurocognitive measures and measures of depression, anxiety, and fatigue to determine a set of variables that distinguished the 24-month persistent cognitive decline group from non-cancer controls or from survivors without decline. Results: The sample of survivors and controls ranged in age from were ages 60–89. Thirty-three percent of survivors had self-reported cognitive decline at twelve months and two-thirds continued to have persistent decline to 24 months (n=60). Least Absolute Shrinkage and Selection Operator (LASSO) models distinguished survivors with persistent self-reported declines from controls (AUC=0.736) and survivors without decline (n=147; AUC=0.744). The variables that separated groups were predominantly neurocognitive test performance change scores, including declines in list learning, verbal fluency, and attention measures. Discussion: Machine learning may be useful to further our understanding of cancer-related cognitive decline. Our results suggest that persistent self-reported cognitive problems among older women with breast cancer are associated with a constellation of mild neurocognitive changes warranting clinical attention.
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    A prospective examination of change in executive function and physical activity in older breast cancer survivors
    (2020-08) Tometich, Danielle Bowman; Mosher, Catherine E.; Cyders, Melissa A.; McDonald, Brenna C.; Saykin, Andrew J.
    Only one third of older breast cancer survivors (BCS) meet national physical activity (PA) guidelines. Theories of self-regulation and research with older adults suggest that executive function (EF) plays an important role in PA, yet the impact of lower EF on older survivors’ PA is unknown. My project addressed this gap using secondary data from the Thinking and Living with Cancer (TLC) cohort study, which examined cognitive function among older BCS pre-treatment, followed every 12 months, and contemporaneously assessed matched controls. My first aim was to test two hypotheses regarding EF change and PA and determine if these relationships differ between BCS and controls. My hypotheses were: 1) EF decline from baseline to 12 months will predict lower PA at 24 months, and 2) lower PA at 12 months will predict EF decline from 12 to 24 months. My second aim was to explore whether the effects of EF change on PA in BCS differed based on risk factors for accelerated cognitive decline (i.e., older age, more advanced cancer stage, comorbidity, and APOE ε4 genotype). The TLC study measured EF with neuropsychological tests and PA with the International Physical Activity Questionnaire-Short Form. For aims 1 and 2, I used multiple regression with multiple imputation. Primary results showed no significant effect of EF change from baseline to 12 months on PA at 24 months (β=-0.01, p=0.88) and no significant group (BCS vs. controls) by EF interaction (β=-0.05, p=0.33). Separate models in BCS and controls showed similar findings. In the entire sample, PA at 12 months significantly predicted EF change from 12 to 24 months (β=0.17, p=0.01), but there was no significant group by PA interaction (β=-0.06, p=0.54). Separate analyses by group found a significant effect of PA for controls (β=0.07, p=0.02), but not for BCS (β=0.05, p=0.27). Regarding the second aim, there were no significant interactions between EF change and the proposed risk factors on PA. Findings were largely inconsistent with theory and prior research. Continued research in this area will inform future exercise interventions to improve physical and cognitive health for the growing population of older cancer survivors.