Symptoms and survivorship needs differences between "good sleepers" and "bad sleepers" in survivors of breast and gynecologic cancers.

INTRODUCTION: Although 80% of cancer survivors report symptoms of insomnia, only 28-43% meet DSM-5 criteria for this diagnosis. We sought to characterize the association between patient-reported insomnia symptoms, patient outcomes, and supportive care variables, as well as explore clinically meaningful insomnia thresholds in a sample of women diagnosed with breast and gynecologic cancers. METHODS: From July 2018-March 2019, all breast and gynecologic cancer survivors seen at the Stanford Women's Cancer Center were approached and invited to participate in the study (15% declined). Of those who consented, 273 survivors completed an online survey related to their sleep (ISI), quality of life (FACT-G), distress (PHQ-4), supportive care needs (SCNS-SF34), and symptom severity (MDASI). Survivors who scored <8 on ISI were categorized as "good sleepers," survivors with ISI ≥8 were categorized as "bad sleepers." RESULTS: 126 (46.2%) of survivors were "good sleepers," 147 (53.8%) were "bad sleepers." Good sleepers were older than bad sleepers (p < .05) but did not differ in any other demographic or any medical variables. Using hierarchical linear regression models, we found that good sleep (ISI <8) was associated with higher quality of life, lower psychological distress, increased social support, lower symptom severity, and lower supportive care needs, after accounting for demographic, medical, and treatment variables. The findings were largely replicated with an ISI cut off of 15. CONCLUSIONS: Among women treated for breast and gynecologic cancers, survivors who were good sleepers had better psychosocial outcomes, fewer supportive care needs, and lower symptom severity compared to those who reported insomnia symptoms. Results also indicate that degree of sleep impairment, whether mild or severe, has similarly poor associations with most aspects of patient functioning and symptomatic burden. Further research is needed to determine causality of these findings.

Patient Perspectives of Inpatient Telemedicine During the COVID-19 Pandemic: Qualitative Assessment.

BACKGROUND: Telemedicine has been adopted in the inpatient setting to facilitate clinical interactions between on-site clinicians and isolated hospitalized patients. Such remote interactions have the potential to reduce pathogen exposure and use of personal protective equipment but may also pose new safety concerns given prior evidence that isolated patients can receive suboptimal care. Formal evaluations of the use and practical acceptance of inpatient telemedicine among hospitalized patients are lacking. OBJECTIVE: We aimed to evaluate the experience of patients hospitalized for COVID-19 with inpatient telemedicine introduced as an infection control measure during the pandemic. METHODS: We conducted a qualitative evaluation in a COVID-19 designated non-intensive care hospital unit at a large academic health center (Stanford Health Care) from October 2020 through January 2021. Semistructured qualitative interviews focused on patient experience, impact on quality of care, communication, and mental health. Purposive sampling was used to recruit participants representing diversity across varying demographics until thematic saturation was reached. Interview transcripts were qualitatively analyzed using an inductive-deductive approach. RESULTS: Interviews with 20 hospitalized patients suggested that nonemergency clinical care and bridging to in-person care comprised the majority of inpatient telemedicine use. Nurses were reported to enter the room and call on the tablet far more frequently than physicians, who typically entered the room at least daily. Patients reported broad acceptance of the technology, citing improved convenience and reduced anxiety, but preferred in-person care where possible. Quality of care was believed to be similar to in-person care with the exception of a few patients who wanted more frequent in-person examinations. Ongoing challenges included low audio volume, shifting tablet location, and inconsistent verbal introductions from the clinical team. CONCLUSIONS: Patient experiences with inpatient telemedicine were largely favorable. Although most patients expressed a preference for in-person care, telemedicine was acceptable given the circumstances associated with the COVID-19 pandemic. Improvements in technical and care team use may enhance acceptability. Further evaluation is needed to understand the impact of inpatient telemedicine and the optimal balance between in-person and virtual care in the hospital setting.

Greater financial toxicity relates to greater distress and worse quality of life among breast and gynecologic cancer survivors.

BACKGROUND: Financial toxicity includes distress and burden from cancer-related costs. Women are more likely to experience worse cancer-related financial outcomes than men. This study evaluated breast and gynecologic cancer patients' subjective experiences of financial toxicity and associations with distress and quality of life (QOL). METHODS: A cross-sectional survey study included measures of financial toxicity (Comprehensive Score for Financial Toxicity [COST] Version 2), distress (Patient Health Questionnaire), and QOL (Functional Assessment of Cancer Therapy). Chi-square, t-tests, and ANOVAs examined bivariate relationships. Two regression models tested associations between financial toxicity and distress and QOL, controlling for covariates. Financial toxicity subgroups were compared based on a validated grading system. RESULTS: Participants (N = 273; 74% breast cancer) averaged 54.65 years (SD = 12.08), were 3.42 years (SD = 4.20) post-diagnosis, and 33% reported cancer-related change in employment status. Financial toxicity was "mild" overall (COST M = 26.11, SD = 11.14); 32% worried about cancer-related financial problems (quite a bit/very much; item-level analysis). Worse financial toxicity related to younger age (p < 0.001), identifying as a non-Asian minority (p = 0.03) or Hispanic (p = 0.01), being single (p < 0.001), lower education (p = 0.004), lower income (p < 0.001), late-stage disease (p = 0.001), recurrent disease (p = 0.004), and active treatment (p < 0.001). In separate multivariable models, greater financial toxicity related to greater distress (ß = -0.45 p < 0.001) and worse QOL (ß = 0.58, p < 0.001). Financial toxicity subgroups reported clinically significant differences in distress and QOL (p's < 0.05). CONCLUSIONS: Cancer-related financial burden is associated with pervasive negative effects and may impact subgroups differently. Future research should explore financial experiences across subgroups, aiming to better identify those at risk and build targeted interventions.