Fatigue and resting-state functional brain networks in breast cancer patients treated with chemotherapy.

PURPOSE: This longitudinal study aimed to disentangle the impact of chemotherapy on fatigue and hypothetically associated functional brain network alterations. METHODS: In total, 34 breast cancer patients treated with chemotherapy (BCC +), 32 patients not treated with chemotherapy (BCC -), and 35 non-cancer controls (NC) were included. Fatigue was assessed using the EORTC QLQ-C30 fatigue subscale at two time points: baseline (T1) and six months after completion of chemotherapy or matched intervals (T2). Participants also underwent resting-state functional magnetic resonance imaging (rsfMRI). An atlas spanning 90 cortical and subcortical brain regions was used to extract time series, after which Pearson correlation coefficients were calculated to construct a brain network per participant per timepoint. Network measures of local segregation and global integration were compared between groups and timepoints and correlated with fatigue. RESULTS: As expected, fatigue increased over time in the BCC + group (p = 0.025) leading to higher fatigue compared to NC at T2 (p = 0.023). Meanwhile, fatigue decreased from T1 to T2 in the BCC - group (p = 0.013). The BCC + group had significantly lower local efficiency than NC at T2 (p = 0.033), while a negative correlation was seen between fatigue and local efficiency across timepoints and all participants (T1 rho = - 0.274, p = 0.006; T2 rho = - 0.207, p = 0.039). CONCLUSION: Although greater fatigue and lower local functional network segregation co-occur in breast cancer patients after chemotherapy, the relationship between the two generalized across participant subgroups, suggesting that local efficiency is a general neural correlate of fatigue.

Binary classification threatens the validity of cognitive impairment detection.

OBJECTIVE: Neuropsychological literature reports varying prevalence of cognitive impairment within patient populations, despite assessment with standardized neuropsychological tests. Within the domain of oncology, the International Cognition and Cancer Task Force (ICCTF) proposed standard cutoff points to harmonize the operationalization of cognitive impairment. We evaluated how this binary classification affects agreement between two highly comparable test batteries. METHOD: Two hundred non-central nervous system (non-CNS) cancer patients who finished treatment (56% females; median age 53 yrs) completed traditional tests and their online equivalents in a counterbalanced design. Following ICCTF standards, impairment was defined as a score of ≥ 1.5 standard deviations (SDs) below normative means on two tests and/or ≥ 2 SDs below normative means on one test. Agreement of classification between traditional and online assessment was evaluated using Cohen's κ. Additional Monte Carlo simulations were conducted to demonstrate how different cutoff points and test characteristics affect agreement. RESULTS: The correlation between total scores of traditional and online assessment was .78. Proportions of impaired patients did not differ between assessment methods: 40% using traditional tests and 38% using online equivalents, χ²(1) = .17, p < .68. Nevertheless, within-person agreement in impairment classification between traditional and online assessment was merely fair (K = .35). Monte Carlo simulations showed similarly low agreement scores (K = .41 for 1.5 SD; K = .33 for 2 SD criterion). CONCLUSIONS: Our results show that binary classification can lead to a situation where two highly similar batteries fail to identify the same individuals as impaired. Additional simulations suggest that within-person agreement between assessment methods using binary classification is inherently low. Modern statistical tools may help to improve validity of impairment detection. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Temporal Dynamics of Resting-state Functional Networks and Cognitive Functioning following Systemic Treatment for Breast Cancer.

Many women with breast cancer suffer from a decline in memory and executive function, particularly after treatment with chemotherapy. Recent neuroimaging studies suggest that changes in network dynamics are fundamental in decline in these cognitive functions. This has, however, not yet been investigated in breast cancer patients. Using resting state functional magnetic resonance imaging, we prospectively investigated whether changes in dynamic functional connectivity were associated with changes in memory and executive function. We examined 34 breast cancer patients that received chemotherapy, 32 patients that did not receive chemotherapy, and 35 no-cancer controls. All participants were assessed prior to treatment and six months after completion of chemotherapy, or at similar intervals for the other groups. To assess memory and executive function, we used the Hopkins Verbal Learning Test - Immediate Recall and the Trail Making Test B, respectively. Using a sliding window approach, we then evaluated dynamic functional connectivity of resting state networks supporting memory and executive function, i.e. the default mode network and frontoparietal network, respectively. Next, we directly investigated the association between cognitive performance and dynamic functional connectivity. We found no group differences in cognitive performance or connectivity measures. The association between dynamic functional connectivity of the default mode network and memory differed significantly across groups. This was not the case for the frontoparietal network and executive function. This suggests that cancer and chemotherapy alter the role of dynamic functional connectivity in memory function. Further implications of these findings are discussed.