Artificial and natural interventions for chemotherapy- and / or radiotherapy-induced cognitive impairment: A systematic review of animal studies.

BACKGROUND: Cancer survivors frequently experience cognitive impairments. This systematic review assessed animal literature to identify artificial (pharmaceutical) or natural interventions (plant/endogenously-derived) to reduce treatment-related cognitive impairments. METHODS: PubMed, EMBASE, PsycINFO, Web of Science, and Scopus were searched and SYRCLE's tool was used for risk of bias assessment of the 134 included articles. RESULTS: High variability was observed and risk of bias analysis showed overall poor quality of reporting. Results generally showed positive effects in the intervention group versus cancer-therapy only group (67% of 156 cognitive measures), with only 15 (7%) measures reporting cognitive impairment despite intervention. Both artificial (61%) and natural (75%) interventions prevented cognitive impairment. Artificial interventions involving GSK3B inhibitors, PLX5622, and NMDA receptor antagonists, and natural interventions utilizing melatonin, curcumin, and N-acetylcysteine, showed most consistent outcomes. CONCLUSIONS: Both artificial and natural interventions may prevent cognitive impairment in rodents, which merit consideration in future clinical trials. Greater consistency in design is needed to enhance the generalizability across studies, including timing of cognitive tests and description of treatments and interventions.

Symptom networks in glioma patients: understanding the multidimensionality of symptoms and quality of life.

PURPOSE: To comprehend the complex relationship between symptoms and health-related quality of life (HRQoL) in patients with diffuse glioma, we applied symptom network analysis to identify patterns of associations between depression, cognition, brain tumor-related symptoms, and HRQoL. Additionally, we aimed to compare global strength between symptom networks to understand if symptoms are more tightly connected in different subgroups of patients. METHODS: We included 256 patients and stratified the sample based on disease status (preoperative vs. postoperative), tumor grade (grade II vs. III/IV), and fatigue status (non-fatigued vs. fatigued). For each subgroup of patients, we constructed a symptom network. In these six networks, each node represented a validated subscale of a questionnaire and an edge represented a partial correlation between two nodes. We statistically compared global strength between networks. RESULTS: Across the six networks, nodes were highly correlated: fatigue severity, depression, and social functioning in particular. We found no differences in GS between the networks based on disease characteristics. However, global strength was lower in the non-fatigued network compared to the fatigued network (5.51 vs. 7.49, p < 0.001). CONCLUSIONS: Symptoms and HRQoL are highly interrelated in patients with glioma. Interestingly, nodes in the network of fatigued patients were more tightly connected compared to non-fatigued patients. IMPLICATIONS FOR CANCER SURVIVORS: We introduce symptom networks as a method to understand the multidimensionality of symptoms in glioma. We find a clear association between multiple symptoms and HRQoL, which underlines the need for integrative symptom management targeting fatigue in particular.