Multiple myeloma (MM) is a chronic malignancy with no current cure. Previously dependent
on myeloablative chemotherapy and stem cell transplantation to induce prolonged
remission, recent advances in targeted therapies are enhancing overall survival and
extending the duration between treatments. Monoclonal antibodies, including CD38-directed
monoclonal antibodies, combination immunotherapies, and T-cell therapies are among the
many promising agents for treating relapsed or refractory (R/R) MM. This improvement in
treatment outcomes is accompanied by significant risk for toxicities such a neutropenia
and subsequent infections which themselves can be life-threatening. Several studies
indicate a high symptom burden and poor health-related quality of life for individuals
with multiple myeloma, with most of what is known from clinical trials of highly
selective populations or qualitative studies conducted outside of the US among mostly
white patients. These factors, coupled with the rapidly changing multiple myeloma
treatment landscape, limits the generalizability to wider population as well as an
understanding of MM's impact across the disease course. A more complete investigation of
the symptom burden, health self-efficacy, and financial, physiologic, and psychosocial
well-being among patients with multiple myeloma is urgently needed to provide a
comprehensive view of the ways in which multiple myeloma and its treatments affects
individuals' lives.
The purpose of this study is to explore the use of symptom monitoring and digital life
coaching (DLC) to inform a more complete understanding of the impact of multiple myeloma
on symptom burden, health self-efficacy, and financial, physiologic, and psychosocial
well-being among a diverse U.S.-based, contemporary sample. The benefits of routine
symptom monitoring have been demonstrated in recent studies, where overall survival
increased among cancer patients who routinely monitored their symptoms. As the science
related to symptom monitoring continues to evolve, exploring interventions to support
both the assessment of and interventions related to disease and treatment-related
sequelae it is important to identify how symptoms can best be monitored and managed.
Studies to date have explored how symptom monitoring can be conducted for patients in the
ambulatory setting, where patients do not receive around the clock assessment and
management as they would in the hospital setting. In this context, digital or eHealth
technologies are increasingly emerging as ways to promote health behaviors, and to
monitor individuals with chronic health states, including cancer. An integrative review
of 28 articles specifically evaluating eHealth interventions for patients with cancer
identified 16 unique eHealth interventions, largely centered around educational support
and decision aids. Telehealth counseling and navigation was found to be effective in
supporting psychosocial needs in a small study (n=20) of underserved (defined by the
authors as those who were primarily unemployed and uninsured) breast cancer patients. In
a study of 1371 cancer patients, 71% reported using a mobile phone daily and 93% reported
having internet access from home, of which 68% reported daily internet use, suggesting
that internet-based technologies may be purposeful in the sharing of information with and
coordination of care for cancer patients. Despite literature indicating its potential
efficacy, few interventional studies have been published that evaluate digital health
coaching and its relationship with self-efficacy and symptom management, specifically in
R/R MM patients. As such, there is a gap in the literature on how digital health coaching
might be used to support patients during cancer treatment and into survivorship.
Pack Health, LLC is an independent, patient engagement company that was established in
2014 with the mission of helping patients access the right care for their condition and
develop the self-management skills to achieve better health and overall well-being. Pack
Health offers a symptom management program involving both interpersonal interactions as
well as e-modules for patients diagnosed with cancer to better manage pain, fatigue,
depression, anxiety and navigate their care more effectively through digital health
coaching and tools.
A recent pilot study at UCSF conducted in collaboration with Pack Health examined the
impact of digital life coaching (DLC) on symptom outcomes for individuals with MM
undergoing upfront stem cell transplantation. Outcomes suggest the efficacy of a coaching
program for engagement up to day +100 post-transplant, with 73% (n=11) DLC engagement and
94% PRO completion. A randomized study of DLC versus usual care in individuals with MM
undergoing upfront stem cell transplantation is underway. However, patients with R/R MM
(where the disease has come back after prior lines of therapy such as transplantation)
may have unique needs. An opportunity exists to explore how a digital health coaching
platform might be used for symptom monitoring and coaching during treatment for R/R MM
for whom the chronic nature of therapy may influence both needs and outcomes in relation
to a DLC intervention.
This is a prospective study of patients with R/R MM to evaluate the feasibility and
preliminary outcomes of DLC and its potential to augment existing standards of care for
patient support. Patients enrolled in the program will be assigned to a health advisor
who will act as an educator and accountability partner, supporting patients as they
experience treatment for R/R MM. Throughout the engagement, patient reported outcomes
(PROs) will be collected at multiple time points to assess the patient status and will be
used to explore relationships between medical management, health related quality of life
(HRQoL), and engagement in the program. Patients will be enrolled and will complete all
assessments at baseline, 30, 60 and 90 days after consent. Findings from this study will
establish feasibility of a DLC intervention for individuals with R/R MM and provide
greater insight into their symptom burden, health self-efficacy, and financial,
physiologic, and psychosocial well-being through the integration of patient reported,
wearable and clinical data.