"Just Living With Them": Symptom Management Experiences of Rural Residents With Advanced Cancer

Describing and visualizing the patient and caregiver experience of cancer pain in the home context using ecological momentary assessments

Background

Pain continues to be a difficult and pervasive problem for patients with cancer, and those who care for them. Remote health monitoring systems (RHMS), such as the Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C), can utilize Ecological Momentary Assessments (EMAs) to provide a more holistic understanding of the patient and family experience of cancer pain within the home context.

Methods

Participants used the BESI-C system for 2-weeks which collected data via EMAs deployed on wearable devices (smartwatches) worn by both patients with cancer and their primary family caregiver. We developed three unique EMA schemas that allowed patients and caregivers to describe patient pain events and perceived impact on quality of life from their own perspective. EMA data were analyzed to provide a descriptive summary of pain events and explore different types of data visualizations.

Results

Data were collected from five (n = 5) patient-caregiver dyads (total 10 individual participants, 5 patients, 5 caregivers). A total of 283 user-initiated pain event EMAs were recorded (198 by patients; 85 by caregivers) over all 5 deployments with an average severity score of 5.4/10 for patients and 4.6/10 for caregivers' assessments of patient pain. Average self-reported overall distress and pain interference levels (1 = least distress; 4 = most distress) were higher for caregivers (x ¯ 3.02, x ¯ 2.60 , respectively ) compared to patients (x ¯ 2.82, x ¯ 2.25, respectively) while perceived burden of partner distress was higher for patients (i.e., patients perceived caregivers to be more distressed, x ¯ 3.21, than caregivers perceived patients to be distressed, x ¯ 2.55 ). Data visualizations were created using time wheels, bubble charts, box plots and line graphs to graphically represent EMA findings.

Conclusion

Collecting data via EMAs is a viable RHMS strategy to capture longitudinal cancer pain event data from patients and caregivers that can inform personalized pain management and distress-alleviating interventions.

Disparities in Psychosocial Distress Screening and Management of Lung and Ovarian Cancer Survivors

PURPOSE

Since 2016, the American College of Surgeons' Commission on Cancer (CoC) has required routine distress screening (DS) of cancer survivors treated in their accredited facilities to facilitate early identification of survivors with psychosocial concerns. Lung and ovarian cancer survivors have relatively low 5-year survival rates and may experience high levels of distress. We examined the extent to which ovarian and lung cancer survivors received CoC-mandated DS and whether DS disparities exist on the basis of diagnosis, sociodemographic factors, or facility geography (urban/rural).

METHODS

This study included a quantitative review of DS documentation and follow-up services provided using existing electronic health records (EHRs). We worked with 21 CoC-accredited facilities across the United States and examined EHRs of 2,258 survivors from these facilities (1,618 lung cancer survivors and 640 ovarian cancer survivors) diagnosed in 2016 or 2017.

RESULTS

Documentation of DS was found in half (54.8%) of the EHRs reviewed. Disparities existed across race/ethnicity, cancer type and stage, and facility characteristics. Hispanic/Latino and Asian/Pacific Islander survivors were screened at lower percentages than other survivors. Patients with ovarian cancer, those diagnosed at earlier stages, and survivors in urban facilities had relatively low percentages of DS. Non-Hispanic Black survivors were more likely than non-Hispanic White survivors to decline further psychosocial services.

CONCLUSION

Despite the mandate for routine DS in CoC-accredited oncology programs, gaps remain in how many and which survivors are screened for distress. Improvements in DS processes to enhance access to DS and appropriate psychosocial care could benefit cancer survivors. Collaboration with CoC during this study led to improvement of their processes for collecting DS data for measuring standard adherence.

Deploying the Behavioral and Environmental Sensing and Intervention for Cancer Smart Health System to Support Patients and Family Caregivers in Managing Pain: Feasibility and Acceptability Study

BACKGROUND

Distressing cancer pain remains a serious symptom management issue for patients and family caregivers, particularly within home settings. Technology can support home-based cancer symptom management but must consider the experience of patients and family caregivers, as well as the broader environmental context.

OBJECTIVE

This study aimed to test the feasibility and acceptability of a smart health sensing system-Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C)-that was designed to support the monitoring and management of cancer pain in the home setting.

METHODS

Dyads of patients with cancer and their primary family caregivers were recruited from an outpatient palliative care clinic at an academic medical center. BESI-C was deployed in each dyad home for approximately 2 weeks. Data were collected via environmental sensors to assess the home context (eg, light and temperature); Bluetooth beacons to help localize dyad positions; and smart watches worn by both patients and caregivers, equipped with heart rate monitors, accelerometers, and a custom app to deliver ecological momentary assessments (EMAs). EMAs enabled dyads to record and characterize pain events from both their own and their partners' perspectives. Sensor data streams were integrated to describe and explore the context of cancer pain events. Feasibility was assessed both technically and procedurally. Acceptability was assessed using postdeployment surveys and structured interviews with participants.

RESULTS

Overall, 5 deployments (n=10 participants; 5 patient and family caregiver dyads) were completed, and 283 unique pain events were recorded. Using our "BESI-C Performance Scoring Instrument," the overall technical feasibility score for deployments was 86.4 out of 100. Procedural feasibility challenges included the rurality of dyads, smart watch battery life and EMA reliability, and the length of time required for deployment installation. Postdeployment acceptability Likert surveys (1=strongly disagree; 5=strongly agree) found that dyads disagreed that BESI-C was a burden (1.7 out of 5) or compromised their privacy (1.9 out of 5) and agreed that the system collected helpful information to better manage cancer pain (4.6 out of 5). Participants also expressed an interest in seeing their own individual data (4.4 out of 5) and strongly agreed that it is important that data collected by BESI-C are shared with their respective partners (4.8 out of 5) and health care providers (4.8 out of 5). Qualitative feedback from participants suggested that BESI-C positively improved patient-caregiver communication regarding pain management. Importantly, we demonstrated proof of concept that seriously ill patients with cancer and their caregivers will mark pain events in real time using a smart watch.

CONCLUSIONS

It is feasible to deploy BESI-C, and dyads find the system acceptable. By leveraging human-centered design and the integration of heterogenous environmental, physiological, and behavioral data, the BESI-C system offers an innovative approach to monitor cancer pain, mitigate the escalation of pain and distress, and improve symptom management self-efficacy.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/16178.

The Impact of Commission on Cancer Accreditation Status, Hospital Rurality and Hospital Size on Quality Measure Performance Rates

BACKGROUND

Rural cancer patients receive lower-quality care and experience worse outcomes than urban patients. Commission on Cancer (CoC) accreditation requires hospitals to monitor performance on evidence-based quality measuresPlease confirm the list of authors is correc, but the impact of accreditation is not clear due to lack of data from non-accredited facilities and confounding between patient rurality and hospital accreditation, rurality, and size.

METHODS

This retrospective, observational study assessed associations between rurality, accreditation, size, and performance rates for four CoC quality measures (breast radiation, breast chemotherapy, colon chemotherapy, colon nodal yield). Iowa Cancer Registry data were queried to identify all eligible patients diagnosed between 2011 and 2017. Cases were assigned to the surgery hospital to calculate performance rates. Univariate and multivariate regression models were fitted to identify patient- and hospital-level predictors and assess trends.

RESULTS

The study cohort included 10,381 patients; 46% were rural. Compared with urban patients, rural patients more often received treatment at small, rural, and non-accredited facilities (p < 0.001 for all). Rural hospitals had fewer beds and were far less likely to be CoC-accredited than urban hospitals (p < 0.001 for all). On multivariate analysis, CoC accreditation was the strongest, independent predictor of higher hospital performance for all quality measures evaluated (p < 0.05 in each model). Performance rates significantly improved over time only for the colon nodal yield quality measure, and only in urban hospitals.

CONCLUSIONS

CoC accreditation requires monitoring and evaluating performance on quality measures, which likely contributes to better performance on these measures. Efforts to support rural hospital accreditation may improve existing disparities in rural cancer treatment and outcomes.

Prognostic biomarker TUBA1C is correlated to immune cell infiltration in the tumor microenvironment of lung adenocarcinoma

BACKGROUND

TUBA1C is a microtubule component that is involved in a variety of cancers. Our main objective was to investigate TUBA1C expression, its prognostic value, its potential biological functions, and its impact on the immune system of patients with lung adenocarcinoma (LUAD).

METHODS

The Cancer Genome Atlas (TCGA), Gene Expression Profiling Interactive Analysis (GEPIA) and Immunohistochemistry Analysis were used to analyze TUBA1C expression, its clinicopathology, overall survival (OS), and disease-free survival (DFS) in LUAD patients. We also determined the correlation between TUBA1C and tumor-infiltrating immune cells (TIICs) by using CIBERSORT and GEPIA databases. To determine the expression of TUBA1C in LUAD, we analyzed a collection of immune infiltration levels and cumulative survival of LUAD tissues in TIMER database. By using UALCAN, STRING, and GeneMANIA databases, we investigated the protein-coding genes related to TUBA1C and its co-expression genes in LUAD tissues. Gene set enrichment analysis (GSEA) was performed by using the TCGA dataset.

RESULTS

The mRNA and the protein expression of TUBA1C were found to be up-regulated in LUAD tissues. The univariate analysis indicated that an increased expression of TUBA1C was significantly correlated to the following parameters: age, stage, and lymph node metastasis. An over-expression of TUBA1C was associated with a poor prognosis of LUAD. In TIMER and CIBERSORT databases, we found that TUBA1C is correlated with 13 types of TIICs: activated B cell, activated CD4 T cell, central memory CD4 T cell, effector memory CD8 T cell, eosinophils, immature B cell, gamma-delta T cell, immature dendritic cell, mast cell, memory B cell, natural killer T cell, regulatory T cell, and type 2T helper cell. By performing GSEA, we found that TUBA1C is closely correlated to cell cycle, p53 signaling pathway, glycolysis, and gluconeogenesis.

CONCLUSIONS

Our findings indicate that TUBA1C is associated with TIICs in tumor microenvironment. Therefore, it serves as a novel prognostic biomarker and a target for future treatment methods of LUAD.