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.