Skip to main content

Digital Health for Patients With Multiple Myeloma: An Unmet Need

Publication: JCO Clinical Cancer Informatics

Abstract

Multiple myeloma (MM) is associated with the highest symptom burden and lowest health-related quality of life (HRQoL) among patients with hematologic malignancies. HRQoL in MM is heterogeneous, varying over the course of disease, with the highest burden at diagnosis and relapse. Patients with MM are increasingly being treated with oral maintenance medications at home. As a result, longitudinal monitoring of medication adherence and patient-reported outcomes, including HRQoL, could inform on disease status, therapeutic tolerability, and satisfaction with care. Digital health technologies, including telemedicine, mobile health, and wearable devices, are poised to become an integral part of modern health care, in part due to the surge in telemedicine necessitated by the COVID-19 pandemic. Although the literature has many reports on the use of digital health technologies in other types of cancers, fewer studies report on their application to MM. In the current narrative review, we survey the applications of digital health for MM. Although there is evidence that some are associated with improved health outcomes, challenges exist that must be met to ensure more widespread adoption. These include the need for increased awareness by patients and health care providers, lack of access by the typical older patient with MM, absence of randomized clinical trials, and low integration with current workflows such as electronic health records. Following our summary of technologies that could benefit patients with MM, we end by describing our vision for how they can be integrated into each phase of the patient journey.

Introduction

This year, multiple myeloma (MM) will be diagnosed in approximately 35,000 people in the United States and an estimated 176,000 people worldwide, resulting in considerable morbidity and mortality.1,2 Between 1990 and 2016, the incidence of MM increased 126% and deaths because of MM increased 94% despite the adoption of new therapies affording longer survival.3,4 An aging global demographic appears to be the factor most responsible for increasing incidence.3 The median age of patients at diagnosis is 69 years, with the greatest incidence among adults age 65-74 years.5 The SEER Program's database shows that 63% of new cases diagnosed in 2013-2017 occurred in those age > 65 years.5

Context

Key Objective
How can digital health applications address the unmet needs in patients with multiple myeloma (MM) and what are the challenges of implementing these solutions?
Knowledge Generated
Digital health technologies have been used to improve health outcomes and patient experience in oncology. We review unmet needs and challenges for digital health applications in MM and suggest creating a multidisciplinary network and developing myeloma-specific guidelines to guide the integration of validated digital health solution–based care in each phase of the treatment journey.
Relevance
Patients with MM have the highest symptom burden and lowest health-related quality of life among patients with hematologic malignancies. Using digital health solutions will allow clinicians to more easily and longitudinally monitor these patients to inform on disease status and tolerability of emerging therapies with the ultimate goal of improving health outcomes and quality of life in patients with multiple myeloma.
Meeting the unmet need for better treatments in this population therefore requires therapies that are tolerable in elderly patients who may be at increased risk of toxicities because of advanced age and likely comorbidities.4 Polypharmacy in this population is common, with one study finding a median of approximately 10 medications in patients > 65 years with newly diagnosed MM6 and another identifying 75% of patients receiving potentially inappropriate medications without pharmacist consultation.7 The prevalence of polypharmacy makes adherence and drug-drug interactions concerning and increases risks of toxicities such as autonomic neuropathy and fall.8 Medication adherence has also taken on increasing importance as oral antimyeloma therapies have become more common.
Another important challenge to address in improving MM treatment is enhancing health-related quality of life (HRQoL). MM is associated with the highest symptom burden and lowest HRQoL among patients with hematologic malignancies.9,10 HRQoL in MM is heterogeneous, varying over the course of disease with the highest burden at diagnosis and relapse.11 Frequent, longitudinal monitoring of patient-reported outcomes (PROs) could inform on both disease status and therapeutic tolerability.
Longitudinal PRO monitoring, improved patient adherence, and many other aspects of modern MM therapy have been empowered by the evolution of digital health, defined as the “use of information and communication technologies to improve human health, healthcare services, and wellness for individuals and across populations.”12 This broad term covers categories such as mobile health (mHealth), health information technology, wearable devices, telehealth and telemedicine, and personalized medicine.13 The aims of digital health range from improving trial enrollment, patient experience and convenience, medication adherence, and HRQoL to preventing hospital admissions through vital sign monitoring.
Many factors shaping the modern health care environment can contribute to the adoption of digital health solutions, including increasing health care costs, more awareness for cost-effectiveness of drugs,14 higher patient expectations for better communication with health care providers (HCPs),15 the near ubiquity of electronic health records (EHRs), digital databases, social media (SM), and the growing popularity of wearable devices and health-related smartphone applications.16 An additional impetus for use of digital health solutions has been the COVID-19 pandemic, where remote visits via telemedicine are now recommended when possible for patients with MM and have become increasingly common for outpatient care.17-19
In this narrative review, we briefly describe specific applications of digital health, how these applications have thus far contributed to addressing unmet needs of patients with MM, their far greater potential, and the obstacles that must be overcome to reach that potential.

Unmet Needs for Digital Health in MM

As new therapies have improved patient outcomes, MM is now managed as a chronic disease that is treated with long-term, continuous therapy and orally administered drugs. These include immunomodulatory agents (eg, lenalidomide), proteasome inhibitors (eg, ixazomib), and older classes of oral drugs such as dexamethasone and melphalan.20 Although MM may be considered a chronic disease, patients experience a heterogenous collection of symptoms over their disease course. Therefore, a patient's treatment journey requires years, during which medication adherence must be maintained and shifting symptoms must be monitored and addressed by HCPs. Both domains could benefit from digital health technologies.
Despite data demonstrating the positive impact of digital health technology adoption in other areas of oncology, there are currently few signs so far of this occurring in MM. The studies reported to date are summarized in Table 1. Crucially, scalable platforms that leverage widely used modern digital technologies (eg, the iPhone operating system, wearables, and smartphones) are lacking. Because of the high symptom burden and heterogeneous HRQoL associated with MM, there is a need to develop and have patients and HCPs use integrated digital platforms that track PROs to potentially improve patient empowerment, resilience, HRQoL, and outcomes.
Table 1. Summary of Representative Digital Health Studies in Multiple Myeloma

Telemedicine

The primary advantage of telemedicine—eliminating travel to visit a clinic—can be a priority for patients in rural areas or those with mobility issues.26 Additionally, expanding the patient population available to a specialist for a second opinion might improve outcomes by allowing access to expertise from higher-volume facilities.27 Disadvantages arise primarily from the lack of human contact, which makes some patients feel disconnected, and inapplicability of remote monitoring for acutely ill patients. For some potential users in the HCP community, the need to negotiate regulatory issues surrounding licensing can also be seen as a disadvantage.28,29
The COVID-19 pandemic has triggered greater adoption of telemedicine to treat patients with MM and other cancer types. Recommendations and consensus statements supporting greater use of telemedicine visits to reduce the number of office visits have been published by various oncology and MM-specific societies and networks.17,18 An analysis of US insurance claims showed that during the first half of 2020, telemedicine visits increased by 20%, but in-person visits decreased by 30%. Claims data also revealed substantial state-to-state variability in the use of telemedicine visits.19

Digital Patient Education and Life Coaching

Health technologies that successfully educate patients and promote shared decision making would significantly benefit patients in maintaining HRQoL. One important aspect that influences success of internet-based education programs is digital health literacy, and a study found that it is significantly associated with shared decision making.30 Alternatively, digital life coaching is being tested to provide patient education.31 An ongoing pilot study will determine if patients with MM communicate regularly with their life coach at the time of their autologous or allogeneic stem-cell transplant (ASCT).31 Moving the coaching relationship from the office to a phone may allow patients more flexibility and greater frequency of interactions with a HCP.

Medication Adherence

The transition to oral therapy in MM is not without challenges, as a recent study reported poor adherence to lenalidomide by 38% of patients.6 Adherence was significantly associated with age, ethnic group, and polypharmacy.6 Accordingly, we suggest that the increasing use of oral oncolytics should be accompanied by development of tools that allow remote monitoring of medication adherence. Previously, adherence at home could only be measured through patient reporting or prescription refill data. Digital health has made more immediate and objective measurement possible, and its implementation has recently been accelerated by the COVID-19 pandemic.19,32
Digital devices and wearables were included in the US MM-6 study, which investigated the transition from parenteral bortezomib to oral ixazomib in community-based patients (N = 55; median age 72 years) with newly diagnosed MM. Compliance with PRO questionnaires was 96% overall and ≥ 87% in all cycles. Self-reported medication adherence was excellent or very good in ≥ 77% of patients up to cycle 5. Collection of data by activity or PRO reporting appeared feasible in this elderly, comorbid patient population.25

Patient-Reported Symptom Monitoring

PROs have traditionally been collected at clinical visits, but today's digital health methods allow them to be more aligned with patient experience.33 A study conducted in 2004 revealed that patients with cancer preferred computerized questionnaires more than paper and pencil questionnaires, but less than face-to-face interviews.34 More recently, these findings have been confirmed in patients from the Austrian Myeloma Registry. Among 40 participants assessed for feasibility of using a tablet computer to report PROs, 87% were quite or very satisfied with electronic monitoring of PROs and had no problems using a computer tablet.35
Several groups have shown that transitioning from in-person interviews to digital and/or remote reporting can significantly improve both HRQoL and survival for patients with cancer. The largest trial of digital symptom monitoring to date (in patients with solid tumors) showed that the use of a web-based interface versus usual care for one year reduced the likelihood of emergency department visits and lengthened median overall survival.36,37 Other studies that have coupled remote or digital symptom reporting with an alert system have also reported improved survival,38 and some have reported improved physical well-being, feelings of self-efficacy,39 and greater reductions in symptom severity.40
However, few studies to date have reported remote PRO monitoring for MM. One small study of 11 patients with relapsed or refractory MM examined the value of patient-reported symptoms after one to three prior lines of therapy.41 Patients were asked to report symptom presence, severity, and interference via the National Cancer Institute's Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) weekly or, if desired, spontaneously via cell phone app or web portal. At predefined thresholds, patients received guidance and HCPs were alerted. All patients completing the study (n = 9) ranked the app favorably. Areas of improvement were apparent, however. HCPs reported difficulty in responding to alerts because of lack of integration with their current system, and none discussed symptoms reported through the app at any clinical visit. A study on the use of PRO-CTCAE concluded that the use of text fields could also improve the platform by increasing the number of reported adverse events.42 Another small study (N = 14) evaluated a web-based interface for MM symptom tracking.43 With 80% adherence, patients reported that they preferred the app to a clinic visit and HCPs noted that the use of the app identified more medical issues than did normal follow-up interviews.

Vital Sign and Activity Monitoring

Although PROs by their very nature are suitable to be monitored by a lay person, physiologic health presents feasibility issues that must be addressed before digital data can be collected reliably.44 A pilot study evaluated the usability of the VitalPatch (VitalConnect, San Jose, CA), a wearable biosensor that tracks vital signs and detects falls.45 Among patients with hematologic disorders (n = 12) who received transfusions, mean scores for pleasantness and staying in place were 6.7 and 8.1 of 10, respectively. Although the rating for pleasantness was high, three of 12 patients withdrew because of skin irritation. Despite this drawback, a growing body of evidence suggests that continuous monitoring of activity levels and key vital signs provides tangible benefits for patients with cancer. Correlations between average daily steps (assessed by Fitbit Flex [San Francisco, CA] or the Apple Watch [Cupertino, CA]) and PROs were demonstrated in two studies of patients with MM or other types of cancer.22-24 The average number of daily steps was associated with pain, fatigue, sleep disturbance, global physical quality of life (QoL), and physical and social function.

Communication and Patient Satisfaction

Digital and mobile health technologies may be able to improve patient communication skills while decreasing their symptoms and improving survival. One study indicates that this may be most successful when digital interventions are coupled with patient-provider consultation.46 Patients with cancer who met with a physician after completing a digital questionnaire discussed a larger number of symptoms than those who did not complete the questionnaire. Implementation of digital interventions to improve patient-HCP communication could address the needs of patients with MM who have a high symptom burden.

Social Media Connections

SM has become a pervasive and almost unavoidable facet of modern life for patients with cancers including MM. Major advantages of SM use by patients with cancer include engagement and empowerment, psychosocial support, informational support, enhanced patient-physician relationships, and sources of education regarding cancer and clinical trials. However, SM has the concurrent disadvantages of misinformation, insufficient substitution for in-person support, financial exploitation, information overload, and potential breaches in privacy.47
SM has more limited potential to help oncologists, and other HCPs learn more about their patients and help them deal with cancer-associated problems. For MM, SM has already helped to identify several issues of importance to patients. One study demonstrated that data gathered on forums via crowdsourcing of BELONG.LIFE, a patient-powered research network, showed that neuropathy was the most frequently discussed treatment-related adverse event.48 Although studies such as this can perhaps increase the value of doctor-patient conversions by focusing on common complaints, relying on SM alone could introduce population bias and thus increase treatment disparities. In two other SM-based studies, patients with MM were identified after they visited websites (PatientsLikeMe and Myeloma Crowd) or the Takeda Oncology Facebook page.49,50 Patients had an average age of 61 years, were mostly White, and were treated primarily at academic medical centers. Future SM-based studies should be tailored to reach a more representative group of patients with MM.

Challenges Faced in the Use of Digital Health Methods in Myeloma

The challenges of digital health should not be underestimated, for both patients and HCPs. Notably, success in development and implementation of digital health requires a particularly collaborative effort that differs from traditional single-discipline approaches. Patient and data privacy concerns and a lack of uniform reimbursement structures must also be addressed.
Barriers to digital health use by patients include lack of access to and/or inability to use digital health technologies or lack of acceptance as a viable option to manage their care when being treated for MM. The Pew Research Institute has described an intersection of three key demographics that have a dramatic impact on the access and use of smartphones and home computers: age, income level, and proximity to a metro area. In the United States, smartphone ownership was reported by only 53% of adults over 65 years, 71% of those making < $30,000 US dollars per year, and 71% of those living in rural regions.51 When these statistics are overlaid on the epidemiology of MM, the emerging relationships are a cause for concern. First, the incidence of MM is highest among adults age 65-74 years and 63% of new cases occur in those older than 65 years.5 A recent study that stratified younger and older patients with cancer found that electronic symptom monitoring lowered emergency department visits and improved survival only for patients < 70 years.52 The mean age of patients from the Austrian Myeloma Registry who decided against electronic PRO monitoring was greater than that of patients who agreed to monitoring (74 years v 64 years, respectively).35 Second, MM mortality rate is higher among rural patients and this group is more likely to present with stage III disease. Some evidence suggests lower use of digital technologies by sicker patients.53 A national longitudinal study of Danish patients with MM assessed the completion rates of internet- or paper-based questionnaires to collect PROs.54 They found a significant association between noncompletion and both frailty and performance scores.54 These trends could hamper widespread use or success of digital health technologies among many patients with MM and could turn the digital divide into a treatment divide. Clearly, concerted efforts will be needed to ensure equal participation by patients in all of these underutilizing populations.
The challenges faced by HCPs arise from institutional and personal constraints. A practitioner's employer may have complex, incomplete, or evolving requirements for data integration that discourage the use of mHealth applications or other types of digital health technologies. Conversely, an institution's protocols for use of EHRs may prohibit that data from being shared or accessed by mHealth or wearable technologies. A recent study by population health researchers at the New York University identified 10 start-ups but only 16 health systems with partnerships to integrate data from digital technologies.55 On the personal side, some HCPs may resist using digital technologies because of issues surrounding information overload.56 Finally, in many parts of the world, health care institutions themselves are severely resource limited. Thus, widespread adoption of digital health proceeds, at least initially, at the risk of widening the digital divide.

Digital Health Technology in Clinical Research

The COVID-19 pandemic has the potential to transform the conduct of clinical trials. In March 2020, the US Food and Drug Administration issued a guidance for the conduct of clinical trials, recommending that sponsors evaluate remote methods to assess patient safety.57 Among clinical researchers who responded to a survey conducted by the American Society of Clinical Oncologists, 87% reported that they implemented telehealth visits and 90% reported implementation of remote symptom review.58 Knowledge gained from the use of telemedicine during the COVID-19 pandemic can inform ongoing and future trials in patients with MM. Some current or recent clinical trials in MM that have incorporated digital health technologies are summarized in Table 2. Among the larger trials (N ≥ 100), PAMAL (NCT03238599) focuses on activity monitoring of patients undergoing ASCT and the University of Alabama at Birmingham's study of a Myeloma Pack (NCT03777306) investigates effects of digital patient education on QoL. These studies will help define the place of mobile and electronic tools in improving care for patients with MM.
Table 2. Summary of Clinical Trials Using Digital Health Methods for Patients With Multiple Myeloma
Challenges in incorporating digital health methods into randomized controlled trials have been noted, including inadequate infrastructure and staff inexperience with supportive care studies, leading clinicians to view PRO reporting in drug trials as an optional extra.60 Some of these issues have been addressed in the recent US Food and Drug Administration guidance for monitoring of trials conducted during the pandemic.57 For these and other reasons, the Clinical Trials Transformation Initiative (CTTI) has established a digital health trials program that explores the ethical, practical, and regulatory aspects of decentralized trials. The CTTI recommendations stress that advanced consultation with regulatory agencies and thoughtful protocol design are crucial to the success of the trial.61

Future Directions of Digital Health in MM

Digital health will inexorably continue to be integrated into multiple aspects of MM health care by patients, physicians, caregivers, industry, and regulatory agencies. To obtain maximum benefit from all new technologies, three key issues must be addressed. First, product development must be directed and informed by patients and HCPs. Priority must be given to technologies most likely to benefit patients with MM, instead of technologies that are merely available and may work. Second, all stakeholders must acknowledge that successful use of digital health technologies will require change, may disrupt current practices, and could involve reassignment of roles and responsibilities. Finally, digital health care will not succeed with a one-size-fits-all approach. Personalized treatment plans will be needed to prevent harm brought on by a patient's inability to use a digital or mobile tool prescribed by an HCP. Mobile and digital technologies lie on a continuum that ranges from passive monitoring to active use by a patient, and passive monitoring will most likely be more successful for older patients and those with more advanced disease.
In our view, successfully addressing all these issues will require industry, professional organizations, and patient advocacy groups to form alliances and organize all ongoing activities. Similar to how the National Comprehensive Cancer Network evolved to become a leading authority for cancer care,62 a similar network should guide the transition from traditional to digitally enhanced care for patients with MM. The digitalization of MM care is an enormous task that will require new networks and partnerships, but some infrastructure is already in place. The HealthTree Foundation's Myeloma Coach program and the Multiple Myeloma Research Foundation's Myeloma Mentor program provide portals by which patients can be introduced to and kept informed of digital technologies.63,64 The International Myeloma Working Group, which first published guidelines in 2003,65 can facilitate development of new guidelines for use of digital health technologies, as described below. Patient registries such as Austria's and the Netherlands' national myeloma registries, the Connect MM Registry, and the Insight MM can also play a role in determining the use and efficacy of new technologies among patients in a real-world setting.35,66-68
We envision that different types of applications and technologies will be needed as patients with MM progress from diagnosis through relapse to maintenance with oral therapies (Fig 1). First, newly diagnosed patients should be encouraged to seek advice from coaches or mentors and engage in the community via SM or patient engagement platforms such as Myeloma Pack. In acute care settings, such as during a clinical trial or after a transplant or immunotherapy, technologies that monitor vital signs and activity can prevent rehospitalizations. Among patients with MM who received an ASCT, readmission rates can occur in as many as 86% of patients, with fever being one of the predictive factors for readmission.69,70 Accordingly, a passive sensor like the VitalPatch or a similar wearable device that monitors temperature will play an important role in the post-transplant setting. Medication adherence is an important priority for patients being treated with oral therapies, and this issue will perhaps require the most personalization of digital and mobile tools. For patients who are reluctant to use digital aids or who do not have a smartphone, the most successful approach may be to combine passive wearable devices such as the Apple Watch or Fitbit with regular telemedicine appointments. If caregivers are available, a treatment plan could also promote the use of a smartphone app like Medisafe, which is used by patients with MM but has not been studied yet in randomized controlled trials.71 Among patients who are amenable to using more active monitoring tools, smartphone apps should be the standard for tracking medication adherence. When a relapse occurs, patients need to learn about their treatment options and communicate effectively with their HCPs. Digital technologies most suitable for this phase of the patient journey should include electronic questionnaires and digital life coaching, coupled with continuous participation in patient engagement platforms.
Fig 1. Integrating digital health technology into the patient journey of MM. Upper left box: Digital health technologies support stages of the MM treatment journey. SM-based and other platform-based tools (purple) enable patient advocacy and disease management; smartphone apps (blue) allow transfer of data related to PROs; wearable devices and smart-home programming (green) facilitate remote monitoring of patient's vital signs and other physiologic events33; smartphone apps and telemedicine appointments (orange) encourage patients to track their medication adherence and communicate adherence to their HCP25,71; smartphone apps (red) enhance in-person visits via patients' self-reporting of AEs and changes in symptoms of MM.33 Right-sided boxes: Use of specific digital health technologies will change as the patient enters each phase of the MM journey. At the time of diagnosis, patients require advocacy and advice for disease management. During treatment, medication adherence, symptom reporting, PRO data submission, and physiologic data collection are key to enhancing the benefits of treatment. When a patient is in remission, symptom and activity reporting is needed to monitor the emergence of symptoms of MM. Ongoing disease monitoring requires patients to submit PRO data, report symptoms of MM, and submit physiologic data to their HCP. If a relapse occurs, patients once again require advocacy and advice for treatment options. They must also submit PRO and physiologic data to their HCP. AE, adverse event; HCP, health care provider; MM, multiple myeloma; PRO, patient-reported outcome; SM, social media.
Except for telemedicine, no major clinical guidelines for any indication recommend digital health tools.72 By using CTTI recommendations as a starting point, stakeholders can develop MM-specific guidelines for the use of digital health technologies to monitor patients throughout their journey. Although these guidelines will optimally need to align with treatment guidelines, they should include patient assessment as an earlier pretreatment phase. Not all patients will be good candidates for all available technologies; therefore, evaluation of a patient's medical and socioeconomic factors will hopefully yield the best mix of traditional and digital care. This is a crucial aspect of linking digital tools to treatment because clinical and demographic factors are known to affect a patient's ability or willingness to use electronic and mobile tools.35,52-54 During periods of acute care, evidence-based guidelines should be developed to stipulate a timeframe for monitoring patient symptoms. Further along the patient journey, digital health guidelines should outline a set of best practices to help patients manage long-term medication adherence and HRQoL by using one or more of the tools that we have described in this review. These best practices should be patient-centric and include recommendations for engaging patients whose initial assessment uncovered risk factors such as advanced age or disease, lack of caregivers, a rural location, and minority status. In addition, guidelines will need to discuss integration of longitudinal data into both patients' EHRs and their visits to an HCP. Recommendations regarding SM should focus on identifying new topics for research, rather than on enrolling patients or gathering data.
In conclusion, although digital health solutions are emerging in oncology, there is a still greater unmet need for solutions in MM. The growing demand for more personalized, patient-centric, and cost-effective care for patients with MM continues to drive the development of digital health solutions. These hold promise in improving patient education, patient and caregiver engagement, communication with HCPs, proactive symptom management, medication adherence, and HRQoL. Challenges to overcome are increased awareness by patients and HCPs, lack of access by the typical older patient with MM, the need for larger, more collaborative teams, and seamless integration with existing databases and EHRs, which, in turn, calls for better interfaces and HCP engagement.73
Very few studies of digital health applications in patients with MM have appeared to date, and no integrated digital platform to facilitate such studies appears to exist. Given the promise of these new technologies for improving outcomes in this important patient population, further studies are essential and the data that they provide will be much anticipated. We suggest that MM-specific guidelines should be developed to promote the integration of validated technologies into each phase of the patient journey. In the future, when digital technologies are widely deployed and all HCPs have access to evidence-based guidelines, patients with MM can hopefully experience better health and QoL.

Acknowledgment

The authors received writing and editorial assistance from Bio Connections LLC (Chicago, IL).

Support

Supported by Bristol Myers Squibb.

Authors' Disclosures of Potential Conflicts of Interest

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/cci/author-center.
Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).

Sundar Jagannath

Consulting or Advisory Role: BioMED Corp, Bristol Myers Squibb, Janssen, Karyopharm Therapeutics, Legend Biotech, Merck & Co, Surface Oncology, Takeda, Sanofi

Joseph Mikhael

Honoraria: Amgen, Karyopharm Therapeutics, Sanofi, Janssen, Celgene, GlaxoSmithKline, Takeda

Omar Nadeem

Consulting or Advisory Role: Celgene, Janssen, Amgen, Sanofi, Takeda, Adaptive Biotechnologies

Noopur Raje

Consulting or Advisory Role: Bristol Myers Squibb
No other potential conflicts of interest were reported.

References

1.
Sung H, Ferlay J, Siegel RL, et al: Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 71:209-249, 2021
2.
Siegel RL, Miller KD, Fuchs HE, et al: Cancer statistics, 2021. CA Cancer J Clin 71:7-33, 2021
3.
Cowan AJ, Allen C, Barac A, et al: Global burden of multiple myeloma: A systematic analysis for the Global Burden of Disease study 2016. JAMA Oncol 4:1221-1227, 2018
4.
Kumar SK, Dispenzieri A, Lacy MQ, et al: Continued improvement in survival in multiple myeloma: Changes in early mortality and outcomes in older patients. Leukemia 28:1122-1128, 2014
5.
SEER Cancer Stat Facts: Myeloma. Bethesda, MD, National Cancer Institute. https://seer.cancer.gov/statfacts/html/mulmy.html
6.
Mian H, Fiala M, Wildes TM: Adherence to lenalidomide in older adults with newly diagnosed multiple myeloma. Clin Lymphoma Myeloma Leuk 20:98-104.e1, 2020
7.
Sweiss K, Calip GS, Wirth S, et al: Polypharmacy and potentially inappropriate medication use is highly prevalent in multiple myeloma patients and is improved by a collaborative physician-pharmacist clinic. J Oncol Pharm Pract 26:536-542, 2020
8.
Umit EG, Baysal M, Bas V, et al: Polypharmacy and potentially inappropriate medication use in older patients with multiple myeloma, related to fall risk and autonomous neuropathy. J Oncol Pharm Pract 26:43-50, 2020
9.
Richardson PG, Larocca A, Leleu X, et al: The burden of relapsed/refractory multiple myeloma: An indirect comparison of health-related quality of life burden across different types of advanced cancers at baseline and after treatment based on HORIZON (OP-106) study of melflufen plus dexamethasone. Blood 134:3487, 2019
10.
Johnsen AT, Tholstrup D, Petersen MA, et al: Health related quality of life in a nationally representative sample of haematological patients. Eur J Haematol 83:139-148, 2009
11.
King TA, King MT, White KJ: Patient reported outcomes in optimizing myeloma patients' health-related quality of life. Semin Oncol Nurs 33:299-315, 2017
12.
Kostkova P: Grand challenges in digital health. Front Public Health 3:134, 2015
14.
Carlson JJ, Guzauskas GF, Chapman RH, et al: Cost-effectiveness of drugs to treat relapsed/refractory multiple myeloma in the United States. J Manag Care Spec Pharm 24:29-38, 2018
15.
Mougalian SS, Gross CP, Hall EK: Text messaging in oncology: A review of the landscape. JCO Clin Cancer Inform 2:1-9, 2018
16.
Cox SM, Lane A, Volchenboum SL: Use of wearable, mobile, and sensor technology in cancer clinical trials. JCO Clin Cancer Inform 2:1-11, 2018
17.
Malard F, Mohty M: Management of patients with multiple myeloma during the COVID-19 pandemic. Lancet Haematol 7:e435-e437, 2020
18.
Terpos E, Engelhardt M, Cook G, et al: Management of patients with multiple myeloma in the era of COVID-19 pandemic: A consensus paper from the European Myeloma Network (EMN). Leukemia 34:2000-2011, 2020
19.
Patel SY, Mehrotra A, Huskamp HA, et al: Trends in outpatient care delivery and telemedicine during the COVID-19 pandemic in the US. JAMA Intern Med 181:388-391, 2021
20.
Kumar SK, Vij R, Noga SJ, et al: Treating multiple myeloma patients with oral therapies. Clin Lymphoma Myeloma Leuk 17:243-251, 2017
21.
Biran N, Yucel E, Anthony Kouyaté R, et al: Value of digital patient reported outcomes (PROs) – long-term management of treatment fatigue in relapsed or refractory multiple myeloma. Blood 134:3439, 2019
22.
Thompson CA, Novotny P, Sloan JA, et al: Association between patient-reported outcomes and physical activity measured on the Apple Watch in patients with hematological malignancies. Blood 130:2179, 2017
23.
Thompson CA, Yost KJ, Bartz A, et al: Patient-reported outcomes, emoji, and activity measured on the Apple Watch in cancer patients. J Clin Oncol 36, 2018 (suppl; abstr 6501)
24.
Bennett AV, Reeve BB, Basch EM, et al: Evaluation of pedometry as a patient-centered outcome in patients undergoing hematopoietic cell transplant (HCT): A comparison of pedometry and patient reports of symptoms, health, and quality of life. Qual Life Res 25:535-546, 2016
25.
Noga SJ, Rifkin RM, Manda S, et al: Real-world (RW) treatment patterns and patient-related factors including quality of life (QoL), medication adherence, and actigraphy in community patients (pts) with newly diagnosed multiple myeloma (NDMM) transitioning from bortezomib (btz) to ixazomib: The US MM-6 community-based study. Blood 134:3168, 2019
26.
Freeman CL, Mikhael J: COVID-19 and myeloma: What are the implications for now and in the future? Br J Haematol 190:173-178, 2020
27.
Go RS, Bartley AC, Crowson CS, et al: Association between treatment facility volume and mortality of patients with multiple myeloma. J Clin Oncol 35:598-604, 2017
28.
Mullangi S, Agrawal M, Schulman K: The COVID-19 pandemic—An opportune time to update medical licensing. JAMA Intern Med 181:307-308, 2021
29.
Mehrotra A, Nimgaonkar A, Richman B: Telemedicine and medical licensure—Potential paths for reform. N Engl J Med 384:687-690, 2021
30.
Nejati B, Lin CC, Aaronson NK, et al: Determinants of satisfactory patient communication and shared decision making in patients with multiple myeloma. Psychooncology 28:1490-1497, 2019
31.
Banerjee R, Lazar A, Dunn L, et al: Digital life coaching for myeloma patients undergoing transplantation. Blood 136:2-3, 2020
32.
Keesara S, Jonas A, Schulman K: COVID-19 and health care's digital revolution. N Engl J Med 382:e82, 2020
33.
Fallahzadeh R, Rokni SA, Ghasemzadeh H, et al: Digital health for geriatric oncology. JCO Clin Cancer Inform 2:1-12, 2018
34.
Mullen KH, Berry DL, Zierler BK: Computerized symptom and quality-of-life assessment for patients with cancer part II: Acceptability and usability. Oncol Nurs Forum 31:E84-E89, 2004
35.
Sztankay M, Neppl L, Wintner LM, et al: Complementing clinical cancer registry data with patient reported outcomes: A feasibility study on routine electronic patient-reported outcome assessment for the Austrian Myelome Registry. Eur J Cancer Care (Engl) 28:e13154, 2019
36.
Basch E, Deal AM, Dueck AC, et al: Overall survival results of a trial assessing patient-reported outcomes for symptom monitoring during routine cancer treatment. JAMA 318:197-198, 2017
37.
Basch E, Deal AM, Kris MG, et al: Symptom monitoring with patient-reported outcomes during routine cancer treatment: A randomized controlled trial. J Clin Oncol 34:557-565, 2016
38.
Denis F, Lethrosne C, Pourel N, et al: Randomized trial comparing a web-mediated follow-up with routine surveillance in lung cancer patients. J Natl Cancer Inst 109, 2017
39.
Absolom K, Warrington L, Hudson E, et al: Phase III randomized controlled trial of eRAPID: digital health intervention during chemotherapy. J Clin Oncol 39:734-747, 2021
40.
Cleeland CS, Wang XS, Shi Q, et al: Automated symptom alerts reduce postoperative symptom severity after cancer surgery: A randomized controlled clinical trial. J Clin Oncol 29:994-1000, 2011
41.
Biran N, Anthony Kouyate R, Yucel E, et al: Adaptation and evaluation of a symptom-monitoring digital health intervention for patients with relapsed and refractory multiple myeloma: Pilot mixed-methods implementation study. JMIR Form Res 4:e18982, 2020
42.
Chung AE, Shoenbill K, Mitchell SA, et al: Patient free text reporting of symptomatic adverse events in cancer clinical research using the National Cancer Institute's Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). J Am Med Inform Assoc 26:276-285, 2019
43.
Putkonen. M, Salmi. T, Virtanen. H, et al: Web-based symptom tracking of multiple myeloma patients. 44th Annual Meeting of the European Society for Blood and Marrow Transplantation, Lisbon, Portugal, March 18–21, 2018 (abstract B238)
44.
Izmailova ES, Ellis R, Benko C: Remote monitoring in clinical trials during the COVID-19 pandemic. Clin Transl Sci 13:838-841, 2020
45.
Tonino RPB, Larimer K, Eissen O, et al: Remote patient monitoring in adults receiving transfusion or infusion for hematological disorders using the VitalPatch and accelerateIQ monitoring system: Quantitative feasibility study. JMIR Hum Factors 6:e15103, 2019
46.
Velikova G, Booth L, Smith AB, et al: Measuring quality of life in routine oncology practice improves communication and patient well-being: A randomized controlled trial. J Clin Oncol 22:714-724, 2004
47.
Gentile D, Markham MJ, Eaton T: Patients with cancer and social media: Harness benefits, avoid drawbacks. JCO Oncol Pract 14:731-736, 2018
48.
Gries KS, Fastenau J: Using a digital patient powered research network to identify outcomes of importance to patients with multiple myeloma. J Patient Rep Outcomes 4:74, 2020
49.
Chari A, Romanus D, DasMahapatra P, et al: Patient-reported factors in treatment satisfaction in patients with relapsed/refractory multiple myeloma (RRMM). Oncologist 24:1479-1487, 2019
50.
Rifkin RM, Bell JA, DasMahapatra P, et al: Treatment satisfaction and burden of illness in patients with newly diagnosed multiple myeloma. Pharmacoecon Open 4:473-483, 2020
51.
Pew Research Center: Mobile Fact Sheet. Washington, DC, The Pew Research Foundation, 2019, pp 1-7
52.
Nipp RD, Horick NK, Deal AM, et al: Differential effects of an electronic symptom monitoring intervention based on the age of patients with advanced cancer. Ann Oncol 31:123-130, 2020
53.
Ganguly S, Mailankody S, Ailawadhi S: Many shades of disparities in myeloma care. Am Soc Clin Oncol Ed Book 39:519-529, 2019
54.
Nielsen LK, King M, Möller S, et al: Strategies to improve patient-reported outcome completion rates in longitudinal studies. Qual Life Res 29:335-346, 2020
55.
Dinh-Le C, Chuang R, Chokshi S, et al: Wearable health technology and electronic health record integration: Scoping review and future directions. JMIR Mhealth Uhealth 7:e12861, 2019
56.
Furlow B: Information overload and unsustainable workloads in the era of electronic health records. Lancet Respir Med 8:243-244, 2020
57.
U.S. Department of Health and Human Services. US Food and Drug Administration: Conduct of Clinical Trials of Medical Products During the COVID-19 Public Health Emergency: Guidance for Industry, Investigators, and Institutional Review Boards, March 2020. Updated January 27, 2021.
58.
Waterhouse DM, Harvey RD, Hurley P, et al: Early impact of COVID-19 on the conduct of oncology clinical trials and long-term opportunities for transformation: Findings from an American Society of Clinical Oncology Survey. JCO Oncol Pract 16:417-421, 2020
59.
Schinkothe T, Praveen S, Lal A, et al: CANKADO PRO-React: E-Health solution with dynamic symptom questionnaires and automated recommendations for cancer patients. J Clin Oncol 36, 2018 (suppl; abstr 7)
60.
Russell L, Pascoe MC, Seymour JF, et al: The trials and tribulations of conducting an m-health pilot randomized controlled trial to improve oral cancer therapy adherence: Recommendations for future multisite, non-drug clinical trials. BMC Res Notes 12:226, 2019
61.
Clinical Trials Transformation Initiative: Digital Health Technologies, 2021. https://www.ctti-clinicaltrials.org/projects/digital-health-technologies
62.
National Comprehensive Cancer Network: NCCN History, 2021. https://www.nccn.org/home/about/nccn-history
63.
Multiple Myeloma Research Foundation: Myeloma Mentors, 2021. https://themmrf.org/resources/myeloma-mentors/
64.
The HealthTree Foundation: Myeloma Coach, 2021. https://healthtree.org/myeloma/coach
65.
International Myeloma Working Group. Criteria for the classification of monoclonal gammopathies, multiple myeloma and related disorders: a report of the International Myeloma Working Group. Br J Haematol 121(5):749-757, 2003
66.
Rifkin RM, Abonour R, Durie BGM, et al: Treatment patterns from 2009 to 2015 in patients with newly diagnosed multiple myeloma in the United States: A report from the Connect® MM Registry. Blood 128:4489, 2016
67.
Verelst SGR, Blommestein HM, De Groot S, et al: Long-term outcomes in patients with multiple myeloma: A retrospective analysis of the Dutch Population-based HAematological Registry for Observational Studies (PHAROS). Hemasphere 2:e45, 2018
68.
Costello C, Davies FE, Cook G, et al: INSIGHT MM: A large, global, prospective, non-interventional, real-world study of patients with multiple myeloma. Future Oncol 15:1411-1428, 2019
69.
Martino M, Montanari M, Ferrara F, et al: Very low rate of readmission after an early discharge outpatient model for autografting in multiple myeloma patients: An Italian multicenter retrospective study. Biol Blood Marrow Transpl 20:1026-1032, 2014
70.
Martino M, Paviglianiti A, Memoli M, et al: Multiple myeloma outpatient transplant program in the era of novel agents: State-of-the-art. Front Oncol 10:592487, 2020
71.
Myeloma Crowd by the HealthTree Foundation: Keeping Track of Your Multiple Myeloma Medications, 2021
72.
Perakslis E, Ginsburg GS: Digital health—The need to assess benefits, risks, and value. JAMA 325:127-128, 2020
73.
Sisodia RC, Dankers C, Orav J, et al: Factors associated with increased collection of patient-reported outcomes within a large health care system. JAMA Netw Open 3:e202764, 2020

Information & Authors

Information

Published In

JCO Clinical Cancer Informatics
Pages: 1096 - 1105
PubMed: 34735265

History

Published online: November 04, 2021

Permissions

Request permissions for this article.

Authors

Affiliations

Translational Genomics Research Institute (TGen), City of Hope Cancer Center, Phoenix, AZ
Omar Nadeem, MD
Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
Noopur Raje, MD
Center for Multiple Myeloma, Massachusetts General Hospital, Harvard Medical School, Boston, MA

Notes

Sundar Jagannath, MD, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Pl, New York, NY 10029; e-mail: [email protected].

Author Contributions

Conception and design: All authors
Manuscript writing: All authors
Final approval of manuscript: All authors
Accountable for all aspects of the work: All authors

Disclosures

Sundar Jagannath
Consulting or Advisory Role: BioMED Corp, Bristol Myers Squibb, Janssen, Karyopharm Therapeutics, Legend Biotech, Merck & Co, Surface Oncology, Takeda, Sanofi
Joseph Mikhael
Honoraria: Amgen, Karyopharm Therapeutics, Sanofi, Janssen, Celgene, GlaxoSmithKline, Takeda
Omar Nadeem
Consulting or Advisory Role: Celgene, Janssen, Amgen, Sanofi, Takeda, Adaptive Biotechnologies
Noopur Raje
Consulting or Advisory Role: Bristol Myers Squibb
No other potential conflicts of interest were reported.

Metrics & Citations

Metrics

Altmetric

Citations

Article Citation

Download Citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Format





Download article citation data for:
Sundar Jagannath, Joseph Mikhael, Omar Nadeem, Noopur Raje
JCO Clinical Cancer Informatics 2021 :5, 1096-1105

View Options

View options

PDF

View PDF

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Personal login Institutional Login

Purchase Options

Purchase this article to get full access to it.

Purchase this Article

Subscribe

Subscribe to this Journal
Renew Your Subscription
Become a Member

Media

Figures

Other

Tables

Share

Share

Share article link

Share