Electrophysiological Biomarkers of Chemotherapy-related Cognitive Impairment and Recovery

Completed

Conditions: Myelodysplastic Syndrome
Multiple Myeloma
Chronic Myeloid Leukemia
Non-hodgkin Lymphoma
Acute Lymphoid Leukemia
Acute Myeloid Leukemia
Effects of Chemotherapy
Mild Cognitive Impairment
Chronic Lymphocytic Leukemia

Registration Number: NCT02767388

Lead Sponsor: University of Nebraska

Brief Summary: Broadly speaking, the goal of this study is to better understand the influence of chemotherapy treatment on the cognitive and neural mechanisms underlying human behavior. Extant literature lacks diversity in studied cancer populations and treatment protocols, and provides limited understanding of the cognitive abilities that are impaired by chemotherapy. To overcome these limitations, this study will employ a sophisticated battery of tests on an understudied cancer population. Eligible participants will either be patients diagnosed with hematological malignancy (HM) or demographically matched healthy control patients.

After HM diagnosis and treatment protocols have been established, patients will be inducted into the longitudinal study comprised of three visits: 1) after diagnosis but prior to chemotherapy treatment (baseline), 2) after one treatment cycle (one month post-baseline), and 3) after three treatment cycles (three months post-baseline). Patients will undergo a test battery designed to measure specific behavioral and neural mechanisms of attention; tests will either be computer-based cognitive tasks or simulated driving tests that immerse patients into virtual driving scenarios. During each test, EEG will be concurrently measured through non-invasive scalp electrophysiology recordings; EEG recordings will reveal underlying neural mechanisms affected by chemotherapy. Additionally, neuropsychological tests of vision, attention, and memory will be administered, as well as questionnaires to evaluate health, mobility, and life space. Finally, blood samples will be collected to examine levels of circulating inflammation-specific proteins typically present in cancer patients. This study will allow us to better understand the mechanisms through which chemotherapy influences cognitive performance. Results from this study will influence the administration of chemotherapy treatments so that patients can continue to receive the highest medical care while maintaining optimal cognitive abilities and quality of life.

Detailed Description: The broad goal of this research project is to develop a core set of biomarkers for chemotherapy-related cognitive impairment (or chemobrain). Clinical studies have documented mild cognitive impairment in chemotherapy patients most frequently within the domains of attention and memory, though impairments have been observed across a broad range of cognitive abilities. In addition, neuroimaging studies have demonstrated chemotherapy-related structural and functional changes in distributed cortical areas, including regions of the fronto-parietal attention network. While these studies suggest chemotherapy treatment negatively impacts patient health and cognitive function, it remains unclear how chemotherapy affects neural mechanisms of cognitive abilities. Current literature is limited in four major ways: (1) most research has focused on breast cancer populations, providing little insight into impact of tumor type, (2) few studies have examined the parametric effects of chemotherapy toxicity, (3) neuropsychological exams provide weak resolution of specific cognitive functions, and (4) neural factors associated with cognitive impairment are difficult to dissociate from non-neural (e.g. psychosocial) factors. To overcome these central limitations, the investigators propose a one-year longitudinal study that aims to systematically examine the influence of cancer stage and treatment toxicity on mild cognitive impairment observed in hematological malignancy (HM) patients by implementing a core battery of behavioral and neural measures of attention.

Our specific aims (SA) are to:

SA1: Quantify chemotherapy-related impairments of attention-specific processes in HM patients.

H1a: No difference in behavioral measures of attention will be observed across HM groups prior to treatment, and HM groups will perform worse than healthy controls.

H1b: Exposure to chemotherapy will predict behavioral impairments of attention, and the magnitude of impairment will be linked with treatment toxicity.

SA2: Quantify electrophysiological measures of attention-specific processes and determine the link between chemotherapy-related impairments in neural activity and cognitive ability.

H2a: No difference in electrophysiological measures of attention will be observed across HM and healthy control groups prior to treatment.

H2b: Exposure to chemotherapy will predict functional impairments in electrophysiological measures of attention, and the magnitude of impairment will be linked with treatment toxicity.

H2c: Chemotherapy-related impairment in neural measures of attention will be predicted by concurrent impairments in behavioral measures of attention (as in H1b).

SA3: Implement controlled simulations of on-road driving scenarios that probe specific attention processes to determine the impact of chemotherapy on complex real-world behavior.

H3a: No difference in driving performance will be observed across HM groups prior to treatment, and driving performance will be better in healthy controls compared to HM patients.

H3b: Exposure to chemotherapy will predict greater impairment in simulated driving performance, and the magnitude of impairment will be linked with treatment toxicity.

H3c: Impairments in behavioral (as in H1a) and neural measures (as in H2a) of attention will predict greater impairment in simulated on-road driving performance.

Our empirical approach will allow us to more rigorously study the neural mechanisms of chemotherapy-related cognitive impairment. The current proposal aims to extend previous research by longitudinally investigating an understudied cancer population whose constituents are assigned to a treatment group at diagnosis, thus providing sufficient experimental control for examining parametric effects of cancer burden and treatment toxicity on specific mechanisms of attention. Results obtained from this study will be critical to understanding risk factors associated with chemotherapy, which will allow clinicians to make informed treatment recommendations in order to reduce the likelihood of cognitive impairment and maintain the highest quality of life possible for the ever-increasing cancer survivor population.

Recruitment & Eligibility

Status: COMPLETED

Sex: All

Target Recruitment: 45

Inclusion Criteria

Not provided

Exclusion Criteria

Not provided

Study & Design

Study Type: OBSERVATIONAL

Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Change From Baseline Capture Task Performance at 1- and 3- Months	Collected at Study Induction, 1 month after Study Induction, 3 months after Study Induction	Response time - measured as the time required to respond to a target hidden among distractor items - is the primary outcome measure of the capture task. Proportional response time was calculated by subtracting mean response time in the neutral condition from response time in the capture condition, and dividing that number by the standard deviation of response time across conditions. Changes in proportional response time across study visits is reported. Positive values correspond to an increase in response time and negative values correspond to a decrease in response time.
Change From Baseline CDA Amplitude at 1- and 3- Months	Collected at Study Induction, 1 month after Study Induction, 3 months after Study Induction	Electrophysiological component that measures online storage load
Change From Baseline N2pc Amplitude at 1- and 3- Months	Collected at Study Induction, 1 month after Study Induction, 3 months after Study Induction	Electrophysiological component that measures allocation of attentional resources
Change From Baseline Filter Task Performance at 1- and 3- Months	Collected at Study Induction, 1 month after Study Induction, 3 months after Study Induction	Response accuracy - measured as the proportion of correct trials - is the primary outcome measure of the filter task. Changes in response accuracy were calculated by subtracting response accuracy at 1-month and 3-months from baseline response accuracy. Positive values correspond to an increase in accuracy and negative values correspond to a decline in accuracy.