Purpose The purpose of this study is to (a) visualize the symptom–cytokine networks (perceived stress, fatigue, loneliness, perceived cognitive impairment, daytime sleepiness, sleep quality, and 13 cytokines) and (b) explore centrality metrics of symptom–cytokine networks in breast cancer survivors who completed chemotherapy treatment. Methods Cross-sectional analysis of data collected from 66 breast cancer survivors who were on average three years post chemotherapy completion. Perceived stress, fatigue, loneliness, perceived cognitive impairment, daytime sleepiness, and sleep quality were measured with self-report instruments, and a panel of 13 cytokines was measured from serum using multiplex assays. Symptoms and cytokines were simultaneously evaluated with correlations, network analysis, and community analysis. Results Network analysis revealed the nodes with the greatest degree and closeness were interleukin-2, granulocyte-macrophage colony-stimulating factor, interleukin-13, and perceived cognitive impairment. Node betweenness was highest for perceived cognitive impairment and interleukin-2. Community analysis revealed two separate communities of nodes within the network (symptoms and the cytokines). Several edges connected the two communities including perceived cognitive impairment, stress, fatigue, depression, interleukin-2, granulocyte-macrophage colony-stimulating factor, interleukin-8, interleukin-13, and interleukin-10. Partial correlation analyses revealed significant negative relationships between interleukin-2 and fatigue, loneliness, stress, and perceived cognitive impairment ( rs = −.27 to −.37, ps < .05) and a significant negative relationship between perceived cognitive impairment and granulocyte-macrophage colony-stimulating factor ( r =  −.34, p <  .01). Conclusions Our analyses support that perceived cognitive impairment, stress, loneliness, depressive symptoms, and fatigue co-occur and extend the literature by suggesting that interleukin-2 may contribute to the underlying mechanistic pathway of these co-occurring symptoms. Our findings add to a growing body of literature that is shifting to study symptoms as they co-occur, or cluster, rather than individual symptoms.

Early studies of oncology visits performed via telehealth demonstrate patient and provider satisfaction; however, understanding of the impact of telehealth on clinic workflows is limited. The incorporation of telehealth visits into an interprofessional model of oncology care was evaluated to assess for changes in care delivery and patient engagement. New patients with a gastrointestinal cancer diagnosis who were actively undergoing treatment and followed for at least three months were divided into two cohorts based on telehealth utilization. Individual patient charts were reviewed by touchpoint, consisting of in-person visits, telehealth visits, phone calls, and patient portal messages. A total of 28 patient charts were analyzed, 11 pre-telehealth conventional care patients, and 17 telehealth patients. Telehealth cohort patients demonstrated an increased average number of total touchpoints when compared to the pre-telehealth cohort ( p-value = 0.008) and had an increased number of patient portal and phone call touchpoints ( p-value = 0.00 and  0.002). Telehealth provided more interactions between patients and providers demonstrating increased connectivity between a patient and their care team throughout their complex cancer journey. Clinic workflows may need to adjust to account for the increased demand of unscheduled patient interactions.

The COVID-19 pandemic has had considerable impact on volume of outpatient procedures, including radiation therapy, a critical treatment option for cancer patients. In order to measure the impact, we performed a retrospective review of patients treated at our multicenter institution with curative or palliative radiation over the past three years. Materials/Methods: Patients treated with radiation (n = 7,935) at our institution between 1/1/2018 and 12/31/2020 were retroactively enrolled in this IRB exempt study. Data elements such as primary cancer site, age, sex, and treatment intent were captured through our oncology analytics platform. Pearson's Chi square test for significance was used to assess a null hypothesis that there was no significant difference in treatment volume or treatment intent by disease system

systolic blood pressure [SBP], diastolic blood pressure [DBP], and pulse pressure [PP]) were evaluated for all available time points. Course start date of radiation represented day 0 in the irradiated aorta and other radiation cohorts, while the average number of days from the first occurrence of initial diagnosis to course start date for respective cancers was considered day 0 in the unirradiated aorta cohort. Interrupted time series analyses were conducted using custom R scripts, with pairwise statistical comparisons by t-test. Results: Within the cohort we observed no significant differences in pre vs. post-treatment changes in SBP, DBP, or PP for patients that did not receive radiation to the aorta across all disease sites. Similarly, there was no change in these metrics among patients with prostate cancer, whether or not they received brachytherapy. Interestingly, we observed no difference in pre-vs. post-treatment changes in SBP, DBP, or PP in patients with esophageal, pancreas, or gastric malignancies receiving radiation to the aorta -with the understanding that this is an unselected cohort regarding actual site of radiation, as we did not exclude patients receiving radiation to distant metastatic sites Conclusion: Our preliminary analysis demonstrates no evidence to suggest that presumptive radiation dose to the aorta results in significant changes to SBP, DBP, or PP in a mixed cohort of cancer patients.