Differential effects of an electronic symptom monitoring intervention based on the age of patients with advanced cancer

Nipp, Ryan David; Horick, Nora; Deal, Allison M.; Rogak, Lauren J.; Fuh, Charn‐Xin; Greer, Joseph A.; Dueck, Amylou C.; Basch, Ethan; Temel, Jennifer S.; El‐Jawahri, Areej

doi:10.1016/j.annonc.2019.09.003

Cited by 38 publications

(52 citation statements)

References 25 publications

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“…These interventions could potentially be adapted for caregivers of older patients with cancer. In fact, electronic symptom monitoring has been shown to improve patient outcomes [43][44][45] and could be further studied in caregivers of these patients. Our findings also have implications for the development of interventions targeting both prognostic understanding and mastery among caregivers.…”

Section: Discussionmentioning

confidence: 99%

Caregiver–Oncologist Prognostic Concordance, Caregiver Mastery, and Caregiver Psychological Health and Quality of Life

et al. 2021

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Background Caregivers of adults with cancer often report a different understanding of the patient's prognosis than the oncologist. We examine the associations of caregiver–oncologist prognostic concordance with caregiver depressive symptoms, distress, and quality of life (QoL). We also explore whether these relationships differed by caregiver environment mastery, an individual's sense of control, and effectiveness in managing life situations. Materials and Methods We used data from a national geriatric assessment cluster‐randomized trial (URCC 13070) that recruited patients aged 70 years and older with incurable cancer considering any line of cancer treatment at community oncology practices, their caregivers, and their oncologists. At enrollment, caregivers and oncologists estimated the patient's prognosis (0–6 months, 7–12 months, 1–2 years, 2–5 years, and >5 years; identical responses were concordant). Caregivers completed the Ryff's environmental mastery at enrollment. At 4–6 weeks, caregivers completed the Patient Health Questionnaire‐2 (depressive symptoms), distress thermometer, and 12‐Item Short‐Form Health Survey (quality of life [QoL]). We used generalized estimating equations in models adjusted for covariates. We then assessed the moderation effect of caregiver mastery. Results Of 411 caregiver–oncologist dyads (mean age = 66.5 years), 369 provided responses and 28% were concordant. Prognostic concordance was associated with greater caregiver depressive symptoms (β = 0.30; p = .04) but not distress or QoL. A significant moderation effect for caregiver depressive symptoms was found between concordance and mastery (p = .01). Specifically, among caregivers with low mastery (below median), concordance was associated with greater depressive symptoms (β = 0.68; p = .003). Conclusions Caregiver–oncologist prognostic concordance was associated with caregiver depressive symptoms. We found a novel moderating effect of caregiver mastery on the relationship between concordance and caregiver depressive symptoms. Implications for Practice Caregiver–oncologist prognostic concordance is associated with greater caregiver depressive symptoms, particularly in those with low caregiver mastery. When discussing prognosis with caregivers, physicians should be aware that prognostic understanding may affect caregiver psychological health and should assess their depressive symptoms. In addition, while promoting accurate prognostic understanding, physicians should also identify strengths and build resilience among caregivers.

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Section: Discussionmentioning

confidence: 99%

Caregiver–Oncologist Prognostic Concordance, Caregiver Mastery, and Caregiver Psychological Health and Quality of Life

et al. 2021

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“…However, older adults may have increased barriers to the use of new technologies and unique issues related to digital literacy, warranting further examination of the digital divide and tailoring intervention to the older adult population. A recent secondary analysis by Nipp et al found that age moderated the beneficial effects of an electronic symptom monitoring intervention on the risk of emergency room visits and survival, thus highlighting important age-related differences in electronic health interventions [44].…”

Section: Discussionmentioning

confidence: 99%

Capacity to Provide Geriatric Specialty Care for Older Adults in Community Oncology Practices

et al. 2020

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Background. American Society of Clinical Oncology guidelines recommend that patients ≥65 years of age starting chemotherapy undergo a geriatric assessment (GA) to inform and guide management; however, little is known about resources available in community oncology practices to implement these guidelines and to facilitate geriatric oncology research. Materials and Methods. Oncology practices within the National Cancer Institute Community Oncology Research Program (NCORP) were electronically surveyed in 2017 regarding the availability of specialty providers, supportive services, and practice characteristics, as part of a larger survey of cancer care delivery research capacity. Results. Of the 943 NCORP practices, 504 (54%) responded to the survey, representing 210 practice groups. The median new cancer cases per year ≥65 years of age was 457 (interquartile range 227-939). Of respondents, only 2.0% of practices had a fellowship-trained geriatric oncologist on staff. Geriatricians were available for consultation or comanagement at 37% of sites, and of those, only 13% had availability within the oncology clinic (5% of overall). Practice size of ≥1,000 new adult cancer cases (ages ≥18) per year was associated with higher odds (1.81, confidence interval 1.02-3.23) of geriatrician availability. Other multidisciplinary care professionals that could support GA were variably available onsite: social worker (84%), nurse navigator (81%), pharmacist (77%), dietician (71%), rehabilitative medicine (57%), psychologist (42%), and psychiatrist (37%). Conclusion. Only a third of community oncology practices have access to a geriatrician within their group and only 5% of community sites have access within the oncology clinic. Use of primarily self-administered GA tools that direct referrals to available services may be an effective implementation strategy for guideline-based care. The Oncologist 2020;25:1-7 Implications for Practice: Only a minority of community oncology practices in the U.S. have access to geriatric specialty care. Developing models of care that use patient-reported measures and/or other geriatric screening tools to assess and guide interventions in older adults, rather than geriatric consultations, are likely the most practical methods to improve the care of this vulnerable population.

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“…Nipp and colleagues found that older adults may not derive the same benefits from an electronic symptom monitoring intervention as younger adults. 32 Specifically, both the older and younger populations in the intervention arm had lower risks of hospitalization and better quality of life, but emergency room visits and survival were similar between the intervention and control arms in the older age group. This study highlights the need to tailor technologybased interventions to the unique needs of older adults.…”

Section: Emerging Data On the Use Of Digital Health Technologies For mentioning

confidence: 91%

“…The best current example of the latter is likely home-based ePRO monitoring, 31 although the robustness of this approach in older individuals with cancer is still being evaluated. 32…”

Section: Selection and Use Of Wearable Sensors In Oncology Practicementioning

confidence: 99%

Toward Modernization of Geriatric Oncology by Digital Health Technologies

Shahrokni

Loh

Wood

2020

American Society of Clinical Oncology Educational Book

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The number of older adults with cancer is increasing. Over the past 3 decades, geriatric oncology research has focused on improving the assessment of frailty and fitness of older adults with cancer as well as methods of improving their outcomes. At the same time, advances in digital health technologies have opened new frontiers for reaching this goal. Digital health technologies encompass a variety of solutions, from electronic patient-reported outcomes (ePROs) to big data and wireless sensors. These solutions have the potential to further advance our understanding of patients’ experiences during cancer treatment. Whereas the data on the feasibility and utility of such solutions in the care of older adults with cancer are limited, interest from digital health oncology researchers to further explore the benefits of these products is increasing. In this article, we describe the focus of geriatric oncology, the rationale behind the need to explore digital health technologies in this setting, and emerging data and ongoing studies, as well as provide guidelines for proper selection, implementation, and testing of digital health solutions in the context of geriatric oncology.

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Differential effects of an electronic symptom monitoring intervention based on the age of patients with advanced cancer

Cited by 38 publications

References 25 publications

Caregiver–Oncologist Prognostic Concordance, Caregiver Mastery, and Caregiver Psychological Health and Quality of Life

Caregiver–Oncologist Prognostic Concordance, Caregiver Mastery, and Caregiver Psychological Health and Quality of Life

Capacity to Provide Geriatric Specialty Care for Older Adults in Community Oncology Practices

Toward Modernization of Geriatric Oncology by Digital Health Technologies

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