The Oncology Nursing Society Rapid Review and Research Priorities for Cancer Care in the Context of COVID-19

oncology, nursing, coronavirus, COVID-19, SARS-CoV-2, disparities, research
ONF 2021, 48(2), 131-145. DOI: 10.1188/21.ONF.131-145

Objectives: To identify research priorities addressing COVID-19 that build on the 2019–2022 Oncology Nursing Society (ONS) Research Agenda, in alignment with ONS’s mission to promote excellence in oncology nursing and quality cancer care.

Methods & Variables: Priority areas were identified using a multistep approach combining rapid review of the literature; consultation with experts/stakeholders; and review of priorities from other funding agencies, public health, and cancer-focused organizations.

Results: The rapid research response team identified five priority areas for research related to COVID-19: (a) effect of COVID-19 on disparities in cancer care; (b) symptom science, palliative care, and end-of-life care research; (c) access to safe and effective cancer care, clinical trials, and research; (d) communication and partnerships with patients and caregivers; and (e) effect of COVID-19 on nursing workforce, support, and professional development. Cross-cutting themes were also identified.

Implications for Nursing: Oncology nurses are well positioned to address the research priorities and cross-cutting themes identified through this review. The use of innovative methodologic approaches and attention to disparities are necessary to advance cancer care related to COVID-19.

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    During the past year, the novel coronavirus (SARS-CoV-2) has caused unprecedented disruption to the fabric of cancer care worldwide (Richards et al., 2020). In addition to affecting patients’ ability to access screening, diagnosis, treatment, and survivorship care for their cancer, growing data indicate that the pandemic has deepened existing racial, socioeconomic, geographic, and other disparities in disease burden and care (Killerby et al., 2020; Selden & Berdahl, 2020), undercutting decades of work in these areas. To continue providing safe, effective cancer care and continue the mission of providing just, equitable cancer care for all, oncology nurses need clear, rigorous evidence to drive clinical decision-making, health policy, and public health messaging. 

    To address these needs, the Oncology Nursing Society (ONS) tasked a team of researchers to review the literature related to oncology and COVID-19. Goals of the resulting research agenda were to (a) identify critical gaps in the knowledge related to COVID-19 and cancer care and (b) describe research priorities to guide nurse-led research during the pandemic and its aftermath. The resulting priorities build on the 2019–2022 ONS Research Agenda (Von Ah et al., 2019). The priorities were refined related to COVID-19 and introduce new areas for knowledge discovery, translational research, and policy development that will be critical for addressing the evolving pandemic.


    Search Strategy

    To account for the rapid pace of research and evidence that emerged related to COVID-19, the team employed a broad strategy using PubMed®, Scopus®, CINAHL®, and medRxiv databases to search for full-text, freely available, English-language original studies, reviews, meta-analyses, clinical guidelines, and opinions addressing COVID-19, cancer, and nursing published from January 1, 2020, to August 12, 2020. Peer-reviewed and non–peer-reviewed articles were considered. Articles meeting these criteria were reviewed for knowledge gaps, and research priorities addressing these gaps were identified. During the review process, to minimize the potential for bias, anonymous feedback on the proposed priorities was solicited via electronic survey from oncology nurse researchers from diverse locations, practice settings, and research foci, as well as the ONS Board of Directors and key stakeholders. In addition, because of the extremely high rate of publication during the pandemic, authors reviewed the literature in each area multiple times over several months to ensure initial topics identified as priorities continued to be relevant.

    Key Definitions

    The ONS team defined several terms for the purpose of this review. “Cancer care” refers to all aspects of the cancer continuum including screening, diagnosis, treatment, supportive care (e.g., palliative care, hospice, end-of-life care, bereavement services), psychosocial and spiritual care, survivorship, and long-term follow-up care. “Caregiver” refers to members of patients’ personal networks (e.g., family, friends) who directly support their well-being during cancer care. The term “underrepresented group” refers to individuals who have been systematically excluded from equitable access to services that promote health based on social constructs of race, ethnicity, religion, culture, sexual orientation, gender identity, socioeconomic status, or other characteristics.


    Research Priorities

    Synthesis of available literature identified five areas in which research is urgently needed related to COVID-19 and oncology. These include research addressing (a) effect of COVID-19 on disparities in cancer care; (b) symptom science, palliative care, and end-of-life care research; (c) access to safe and effective cancer care, clinical trials, and research; (d) communication and partnerships with patients and caregivers; and (e) effect of COVID-19 on nursing workforce, support, and professional development (see Figure 1). Knowledge gaps related to each priority are summarized in Table 1, with recommendations for disparities-focused research corresponding to each priority. Relationships between new COVID-19 research priorities and existing ONS research priorities are illustrated in Figure 2.

    Cross-Cutting Themes

    After review of the literature related to COVID-19 and cancer and discussion with external stakeholders, the ONS Board of Directors and current authors identified a number of cross-cutting topics or themes for COVID-19 research that would apply equally to each of the five research priorities. These include the need for descriptive and interventional research in each priority area addressing (a) the need for new healthcare delivery models tailored for COVID-19; (b) methods for reducing inequities in care; (c) faster, more accurate public health communication methods; (d) research employing collaborative, interprofessional methods; and (e) use of data science and other innovative research methods. Details on these cross-cutting themes for the current research agenda are summarized in Figure 3. 

    Priority 1: Effect of COVID-19 on Disparities in Cancer Care

    The full portrait of how COVID-19 has affected disparities in cancer care is still emerging. However, early evidence paints a disturbing picture, emphasizing multiple ways that the pandemic has amplified (and continues to amplify) disparities, including many biases and systemic barriers that have plagued underrepresented groups throughout history (Killerby et al., 2020; Selden & Berdahl, 2020; Yancy, 2020). Current data indicate that COVID-19 infection rates and outcomes in the general population mirror many of the existing patterns of inequality (Kim & Bostwick, 2020; Millet et al., 2020; Webb Hooper et al., 2020) while similar patterns emerge at the intersection of cancer and COVID-19. For example, a study of COVID-19 treatments and outcomes in patients with cancer found that non-Hispanic White patients were more likely to receive treatments thought to have an effect on COVID-19 survival than patients of other races and ethnicities (Rivera et al., 2020). In addition, data from the Centers for Disease Control and Prevention (CDC) show that age-adjusted death rates for African Americans with COVID-19 are 2.6 times higher than for White Americans (National Academies of Sciences, Engineering, and Medicine, 2020). Recently, the U.S. Department of Health and Human Services (2020) issued guidance on strategies to increase enrollment of underrepresented populations in clinical trials to support new drug or biologic license applications; however, these remain recommendations and not requirements. 

    Given the often-unpredictable spread of COVID-19 in the United States and globally, difficulty in understanding how the virus is affecting screening, diagnosis, and treatment for cancer in different populations was inevitable. However, emerging health disparities research related to COVID-19 is highlighting what researchers have long known but have yet to address: data collection for characteristics needed to evaluate equity in cancer care, such as race, ethnicity, gender, age, and socioeconomic status, is poor (Chowkwanyun & Reed, 2020). Many of the constructs specifically needed to perform health equity research for COVID-19 have yet to be defined, leading to critical research gaps in this science. For example, in a national analysis of COVID-19 disparities, fewer than half of U.S. states were able to contribute to the report because of inadequate collection of data on race and ethnicity and inadequate levels of testing in underrepresented communities (Hatcher et al., 2020).

    The following are recommendations for research:

    •  Examine the effect of COVID-19 on cancer care and health outcomes in underrepresented groups.

    •  Improve data collection needed to characterize underrepresented groups accurately and holistically.

    •  Explore the experiences of underrepresented patients, caregivers, and families related to cancer and COVID-19.

    •  Identify the social determinants of health (e.g., discrimination, experienced racism, multigenerational housing, community density, pollution, clean water and food access, transportation access, distance to services for employment options, insurance coverage) affecting COVID-19 morbidity and mortality in underrepresented patients with cancer.

    •  Develop and evaluate community-informed and culturally responsive interventions to address disparities in COVID-19 prevention and treatment and access to cancer care.

    •  Develop systematic efforts to monitor and include underrepresented groups in cancer and COVID-19 research going forward.

    Priority 2: Symptom Science, Palliative Care, and End-of-Life Care Research

    As of February 15, 2021, more than 480,000 individuals in the United States have died from COVID-19, and that number increases daily (CDC, 2021). Despite the magnitude of this number, research investigating the role that palliative and end-of-life care—cornerstones of evidence-based care—play in caring for patients with cancer who have COVID-19 is limited (Paterson et al., 2020). In addition, studies show that supportive care, which includes palliative and end-of-life care and efforts to improve quality of life across the entire cancer continuum, may be vital in enhancing patients’ physical and psychological well-being, particularly in the context of alternative care delivery models that have emerged in response to COVID-19 (Paterson et al., 2020).

    People of all ages affected by cancer during the pandemic can have supportive care needs requiring unique responses (Sullivan et al., 2020), but evidence describing these needs is lacking. For example, although children are less likely to be infected with and experience serious illness from COVID-19, children with cancer may be disproportionately affected by policies restricting visitors and social interaction in hospitals and community settings (Sullivan et al., 2020).

    In addition, many individuals affected by cancer and their loved ones are deeply concerned about the real-life effects of COVID-19 (Paterson et al., 2020). Oncology nursing has a rich history of leading symptom science, emphasizing quality of life, and supporting patient autonomy (Cooley & Siefert, 2016; Withycombe et al., 2019). Given that much about the experience of COVID-19 remains unknown, nurses’ holistic perspectives and unique expertise can provide essential insights into what is meaningful to patients and caregivers related to their symptoms. These insights include helping to understand the mechanisms underlying severe, persistent, or particularly disabling symptoms; documenting the experiences of patients living with long-term symptoms from COVID-19; and developing interventions to help patients with cancer better manage symptoms related to COVID-19 (Hsiao et al., 2020).

    The following are recommendations for research:

    •  Identify characteristics needed to distinguish COVID-19 symptoms from symptoms of cancer, cancer treatment, and treatment-induced toxicities.

    •  Determine the effects of COVID-19 on palliative and supportive care services for patients with cancer and caregivers; develop interventions to address these needs and preferences.

    •  Determine best practices for reporting symptoms remotely, including use of mobile applications and technology, to facilitate timely initiation of interventions.

    •  Explore strategies for managing symptoms in patients with cancer who have COVID-19 while minimizing the effect of symptoms on quality of life.

    •  Evaluate interventions to decrease loneliness and increase social functioning among patients with cancer who have COVID-19.

    Priority 3: Access to Safe and Effective Cancer Care, Clinical Trials, and Research

    The arrival of COVID-19 to the United States in early 2020 sent shock waves through the healthcare system as entities scrambled to redistribute resources and develop safe methods to care for patients (Ćurković et al., 2020). The risks and benefits of providing care to patients with cancer, once well understood, have had to be largely reimagined in the context of COVID-19, leading to sweeping changes in how cancer care is being accessed and delivered (Johnston et al., 2020; Zeidan et al., 2020).

    Initial publications addressing access to cancer care during COVID-19 consisted of recommendations from expert panels and oncology-focused organizations (Chen et al., 2020; Maniakas et al., 2020; Pothuri et al., 2020; Yahalom et al., 2020). Many guidelines discussed how to make priorities and decisions about changes in care delivery; however, research evaluating the implementation and effects of these guidelines has been limited (Al-Shamsi et al., 2020; Garg et al., 2020). Most articles focused primarily on treatment and secondarily on screening, with relatively sparse information on prevention, follow-up, and survivorship care. In particular, research addressing innovative strategies for accessing specific elements of cancer care, such as telechaplaincy (Sprik et al., 2020), remote genetic counseling (Mahon, 2020), and telehealth for tobacco-dependent patients with cancer, is lacking (Kotsen et al., 2020).

    Access to clinical trials in the wake of COVID-19, another vital dimension of cancer treatment for many patients, also remains a serious concern. In the short term, the pandemic has caused massive disruption to clinical trials, triggering waves of protocol deviations, challenges with recruitment, and trial discontinuations. This has disrupted much of the fabric of modern oncology research (Cancer Research Institute, 2020). However, research investigating the specific effects that the pandemic has had on different aspects of oncology trials, including trial access, patient monitoring, specimen collection, questionnaire completion, physical examinations, and experimental treatment administration, is lacking (Upadhaya et al., 2020).

    The following are recommendations for research:

    •  Develop and evaluate new models for delivering cancer care designed to reduce risk of COVID-19 exposure and improve access, particularly among those most at risk.

    •  Develop and validate decision tools designed to help patients and caregivers assess the risks and benefits of pursuing cancer care during COVID-19.

    •  Evaluate the ability of existing support service models to holistically address treatment coordination, basic needs (e.g., housing, food, water, medication), mental health, and household responsibilities (e.g., patients with cancer who care for children and family members) during COVID-19.

    •  Examine barriers to accessing cancer care during COVID-19, including social distress, isolation, and financial insecurity; develop and test interventions to reduce these barriers.

    •  Determine care and support needs for patients with dual diagnoses of COVID-19 and cancer.

    Priority 4: Communication and Partnerships With Patients and Caregivers

    Two of the areas of cancer care most affected by COVID-19 have been communication and partnerships with patients with cancer and their caregivers. Early data suggest that social distancing—one of the principal strategies used to reduce COVID-19 transmission—has had a profound impact on the delivery of family-centered care in the oncology setting (Hart et al., 2020). Policies restricting the presence of visitors, including families who are critical to the success of cancer treatment in the home setting, have only increased the need for skilled communication by oncology nurses to promote psychological adjustment, quality of relationships, patient and family education, and goal-concordant cancer care (Bowman et al., 2020; Hart et al., 2020). As crisis standards and response protocols continue to be developed and refined, the effect of new practices on the roles of communication and partnerships with caregivers, as well as the health and well-being of caregivers themselves, must be considered (Kent et al., 2020).

    The following are recommendations for research:

    •  Assess caregiver readiness and capacity for providing serious illness care in the home before, during, and after COVID-19 onset in both patients and caregivers.

    •  Explore the experiences of caregivers caring for patients with dual diagnoses of cancer and COVID-19.

    •  Develop and evaluate technological interventions to enhance clinical communication and social engagement as means to mitigate loneliness in patients and caregivers.

    •  Develop and test communication strategies to reduce inequities in access to information and resources.

    •  Develop communication guides with palliative care, pastoral, social services, and behavioral health teams to help patients, families, and clinicians navigate the unprecedented conversations focused on anticipatory grief, cognitive and emotional acceptance of death, and other elements of grief, loss, and bereavement.

    •  Evaluate outcomes of family meetings used to support patients and families during serious illness conversations related to COVID-19, particularly in the context of poor prognosis.

    •  Establish and evaluate clinical practice guidelines to advocate for patients with serious illness and their families.

    Priority 5: Effect of COVID-19 on Nursing Workforce, Support, and Professional Development

    Prior to COVID-19, groups like the National Academy of Medicine (2020) had already issued a nationwide call-to-action to address workforce issues facing healthcare staff, such as well-being, burnout, and suicide. The arrival of COVID-19 added a veritable avalanche of new stressors to the tens of thousands of healthcare staff that make up the U.S. healthcare workforce. These stressors included serious risks to staff’s short- and long-term physical, psychological, and emotional safety, triggered by issues ranging from shortages of personal protective equipment (PPE), to questions about how to maintain safe working conditions, to ethically challenging situations related to COVID-19 (ONS, 2020). Early evidence suggests that clinical and nonclinical staff, particularly those working on the front line, faced significant feelings of loss of control and difficulty making decisions during the pandemic (Dewey et al., 2020; Gasper et al., 2020; Paterson et al., 2020). In addition, growing evidence indicates that nurses have been disproportionately affected by COVID-19, including having some of the highest rates of COVID-19–related hospitalizations (Kambhampati et al., 2020). Although it is clear that frontline staff bore much of the brunt of these stressors, these risks were not limited to frontline staff; spouses, partners, and families of healthcare workers shared many of the risks related to the pandemic as well.

    At the same time, schools of nursing began to shift didactic teaching to virtual platforms, shorten academic terms, and eliminate on-site clinical placements for students (Jones et al., in press). Professional meetings integral to supporting education and the dissemination of research were canceled or converted to virtual meetings. Many healthcare institutions adopted distance-based approaches to care delivery, shifting large segments of their workforce off-site. In consequence, much of the research conducted by nurse scientists and nursing faculty was deemed nonessential, slowing the advancement of oncology nursing science and requiring immediate modifications in study procedures to allow continued progress of studies (Jones et al., in press).

    The following are recommendations for research:

    •  Explore the impact of COVID-19 on burnout and moral distress among oncology nurses; develop short- and long-term interventions to support nurses and other oncology providers.

    •  Investigate the effects that factors related to COVID-19 (e.g., changing staffing policies, staffing shortages, PPE shortages, changing workflows, staff redeployment) had and continue to have on the oncology nursing workforce; develop interventions to address the effects on frontline oncology nursing staff.

    •  Develop and evaluate strategies to optimize the use of PPE safely and effectively by oncology nurses in various care settings.

    •  Evaluate the effectiveness of distance-based and hybrid learning strategies to complement on-site clinical training for nurses and students.

    •  Evaluate the impact of COVID-19 on nursing student training (e.g., restrictions, delays, and modifications in training quality for pre-RN licensure and clinical/research doctorate training), and evaluate implications for the oncology nursing workforce.

    •  Describe and evaluate the consequences of the shift to virtual meetings on professional development and continuing education for oncology nurses.

    •  Describe and evaluate the effects of the changing scope of practice for oncology-focused providers, such as oncology-focused advanced practice RNs, on patient outcomes.

    •  Describe and evaluate the consequences of institutional restrictions on the work of oncology nurse scientists and the advancement of oncology nursing science.

    Methodologic Considerations for COVID-19–Focused Research

    To advance the science related to COVID-19 and cancer, researchers will need to employ methods capable of addressing the scale and complexity of the issues that have emerged during the pandemic. Methodologic considerations to support COVID-19 research priorities are highlighted in the following sections.


    The term “infodemic” refers to a deluge or overabundance of information, including information that can be inaccurate or harmful (Tangcharoensathien et al., 2020). The sheer volume of information that emerged related to COVID-19 since the onset of the pandemic has made it difficult for the public at large to separate fact from fiction (Bunker, 2020), contributing to media fatigue, decline in public trust, and resistance to even fact-based messaging (Ceron et al., 2020; Chong et al., 2020). In addition, the negative impact of the infodemic was exacerbated by the nearly unrestricted reach of modern social media (Bunker, 2020), absence of fact-checking on many platforms (Ceron et al., 2020), and widespread sharing of false information related to the virus, which was extensive at points (Nsoesie et al., 2020).

    In response, the World Health Organization (WHO) convened its first international conference focusing on infodemics in June 2020, underscoring the importance of infodemiology (the branch of health informatics dedicated to studying “the determinants and distribution of health information and misinformation in an electronic medium” [Eysenbach, 2009, p. e11]) as a critical area for research (Mavragani, 2020). In addition, WHO introduced a framework for managing the COVID-19 infodemic, summarized in Figure 4. Because of the instrumental role that information has played and continues to play in all aspects of the pandemic, research using infodemiology will be essential to not only understand the impact of the infodemic on cancer care, but also develop strategies for protecting patients and families. Because nurses consistently rank among the most trusted health professions (Reinhard, 2020), continued engagement by nurses with the public around science and health information will be vital (Chong et al., 2020).

    Social Media

    With an estimated 3.8 billion users worldwide, social media platforms, such as Twitter and Facebook, are among the most widely used sources of information (Cuello-Garcia et al., 2020). During the pandemic, use of social media—already at an all-time high—grew exponentially as public and health professionals alike sought to find and share information related to the virus (Nsoesie et al., 2020). Although filled with potential pitfalls, social media platforms have proven to be powerful tools for oncology nurses to engage the public in discussions about the safety and timeliness of cancer care, including how to optimize the delivery of different forms of cancer care, encourage healthy habits, and reduce loneliness and isolation (Elran-Barak & Mozeikov, 2020; Lai et al., 2020; Lucini et al., 2020; Prochaska et al., 2017; Subbiah et al., 2019).

    These same social media platforms also provide nurse scientists with new methods for raising public awareness of clinical trials and enhancing study recruitment, intervention delivery, and retention, particularly for hard-to-reach communities (Burke-Garcia et al., 2017). Social media has also been used to educate clinicians in academic and community settings about opportunities for oncology clinical trials; however, issues such as unblinding participants have been raised (Thompson, 2014; Thompson & O’Regan, 2018). New resources, such as the National Cancer Institute (2020) workshop on social media and clinical trials and the Social Media ADEPT framework for online patient–investigator communication about clinical trials (Lynch et al., 2018), are helpful for researchers wanting more information on research using social media, such as consenting, data security, bias, and representation of different populations on various platforms (Pozzar et al., 2020).

    Reliance on Best Evidence at the Time

    Information on COVID-19 continues to emerge at an astounding pace, with articles and pre-prints related to the pandemic emerging multiple times per day. In this environment, evidence and perspectives related to COVID-19 are evolving almost continuously as new research emerges and new local, regional, national, and global data become available (El-Jardali et al., 2020). The fluidity of knowledge around different aspects of the virus throughout the pandemic has led to the concept of best evidence at the time (BET) as nurses and other providers adapt to an environment in which changes to their understanding of the critical topics needed to care for their patients become the norm, not the exception (Eysenbach, 2020). The urgency of the pandemic also led to strategies for developing reliable evidence-based guidelines under pandemic conditions (Akl et al., 2020).

    Organizations that synthesize and update BET (see Figure 5) can be helpful for clinicians, policymakers, and researchers navigating rapidly changing knowledge (El-Jardali et al., 2020). In addition, because of the high degree of uncertainty in the current knowledge environment, studies addressing COVID-19 and cancer should prioritize producing the strongest evidence possible to support effective public health policy and clinical decision-making.

    Epidemiologic Methods

    The pandemic has highlighted many of the challenges inherent in community surveillance and observational research, such as confounding, selection bias, and information bias, which are particularly common in initial reports describing a new phenomenon. These limitations underscore the need to interpret findings cautiously when developing policy and practice guidance. Oncology researchers should consider whether patients with cancer and patients receiving certain therapies are adequately represented in epidemiologic studies, and whether patterns suggesting that COVID-19 susceptibility, prevention, treatment, or outcomes are different in these subpopulations. With two vaccines approved for use in the United States and multiple candidate vaccines in clinical trials as of January 2021, questions about the safety and efficacy of COVID-19 vaccines in patients who are immunosuppressed or undergoing treatment with immune checkpoint inhibitors are important to ask. With previous vaccines (e.g., influenza), clinicians were left with little evidence guiding use of vaccines for certain patients with cancer, having to rely on data generated from clinical studies with inherent design limitations. Moving forward, oncology researchers should generate definitive evidence using study designs that reduce bias.

    Data Science, Big Data, and Machine Learning

    Data have been at the heart of nearly every effort to stay ahead of the pandemic and provide timely, accurate information about the virus to clinicians, patients, and their families. In particular, the growing availability of big data, which refers to datasets so large that they require specialized methods for analyzing, related to the virus provides important opportunities for studies modeling phenomena such as viral incubation, transmission, and symptoms, which can be used to track the virus, deliver tailored public health messaging, and provide real-time updates about COVID-19 (Bullock et al., 2020). Although gaining access to data related to COVID-19 has been easier than in the past because of the ubiquity of electronic health records (EHRs) and improvements in data infrastructure, the heterogeneity of COVID-19 data (which often reflect multiple datasets, time periods, and formats, each with varying degrees of precision) highlights the need to combine traditional research methods with emerging methods from areas like data science.

    In particular, techniques like machine learning and artificial intelligence (AI) have garnered attention for their potential to provide insights into issues like which symptoms and laboratory values are most predictive of infection and outcomes (Soltan et al., 2020). In addition, algorithms have been developed to improve the speed and accuracy of time-consuming activities, such as COVID-19 triage, screening, and diagnosis, by synthesizing information from multiple sources, including medical imaging, comorbidities, and other details from the patient’s EHR (Tayarani-Najaran, 2020). These technologies have created alternative methods for tracking the spread of the virus using noninvasive devices and making predictions on potential outcomes for patients who test positive for COVID-19 (Bullock et al., 2020; Debnath et al., 2020; Soltan et al., 2020). Future applications using techniques like AI for COVID-19 have been proposed (Tayarani-Najaran, 2020). For example, using machine learning to stratify individuals based on their risk for deterioration from COVID-19 may allow clinicians to prioritize patients who require more resource-intensive care and avoid unnecessary hospital admission (Debnath et al., 2020).

    Despite the tremendous potential that techniques like machine learning and AI have for improving the understanding of the effects of COVID-19 on different aspects of cancer care, significant challenges remain (Zame et al., 2020). These challenges include practical issues, such as variability in the quality and completeness of COVID-19 data coming from different data sources, regions, and time periods, which will require careful analysis, as well as input from multiple stakeholders (including nurses) to generate accurate conclusions (Zame et al., 2020). In addition, challenges like the continued lack of accessibility of COVID-19 data in many settings, lack of availability of researchers with expertise in data science, pressure to implement AI or machine-learned algorithms before being properly validated, and basic questions about which data techniques are best suited for different COVID-19–related issues are all hurdles that researchers will need to address moving forward (Zame et al., 2020). Ongoing concerns around data privacy, ownership, and consumer protections (already critical to responsible research) have become particularly salient as public trust in research and public health institutions vacillates and the power of datasets grows (Ienca & Vayena, 2020; Zame et al., 2020).


    For the many individuals on the cancer care continuum, the emergence of the novel coronavirus in late 2019 represented a seismic shift in health care, tilting the axis of cancer care worldwide. The ensuing pandemic (which, as of this writing, continues to spread aggressively in many locations) has had a profound effect on the field of oncology that researchers are only beginning to understand. Over the past year, oncology nurses showed unheralded bravery, resilience, and ingenuity—often at great personal risk to themselves—to continue to provide care to their patients. In addition, nurse scientists, faculty, research nurses, public health nurses, nurse informaticists, epidemiologists, and other knowledge workers labored around the clock in many locations to build infrastructure, analyze data, share ideas, and develop the evidence needed to inform practice and policy and protect frontline workers. Their contributions, along with those of many others, laid the foundation for a new generation of COVID-19–compatible cancer care needed to continue to improve outcomes for patients with cancer.

    However, to ensure that oncology nurses can continue to offer safe and effective cancer care and protect the well-being of their fellow healthcare providers, evidence related to a variety of COVID-19 topics is needed. Current literature related to the intersection of COVID-19 and cancer care is remarkably sparse, and those gaps must be filled to keep pace with the ongoing public health crisis. In this research agenda, the authors have identified five critical areas with insufficient evidence, as well as five cross-cutting themes for research in these areas, needed to fill current gaps to inform policy and guide clinical decision-making.

    The authors dedicate this research agenda to the countless nurses and healthcare providers who continue to selflessly provide care to patients with cancer and their families during the COVID-19 pandemic. They also acknowledge the tireless work of researchers everywhere who continue to light the path forward.

    About the Author(s)

    Noah Zanville, PhD, BSN, BA, is a former nurse scientist at Miami Cancer Institute in Florida and a current nurse scientist scholar at Mission Health, HCA Healthcare North Carolina Division, in Asheville; Bevin Cohen, PhD, MPH, MS, RN, is the director of research and evidence-based practice at Mount Sinai Hospital in New York, NY; Tamryn F. Gray, PhD, RN, MPH, is an instructor in medicine at Harvard Medical School and a scientist in the Department of Psychosocial Oncology and Palliative Care in the Phyllis F. Cantor Center at the Dana-Farber Cancer Institute, both in Boston, MA; Janice Phillips, PhD, RN, CENP, FAAN, is the director of nursing research and health equity at Rush University Medical Center in Chicago, IL; Lauri Linder, PhD, APRN, CPON®, is an associate professor and vice chair of the Division of Acute and Chronic Care in the College of Nursing at the University of Utah, and a clinical nurse specialist in the Center for Cancer and Blood Disorders at Primary Children’s Hospital, both in Salt Lake City; Angela Starkweather, PhD, ACNP-BC, FAAN, is a professor and associate dean for academic affairs in the School of Nursing, and a professor in the department of Genetics and Genome Sciences in the School of Medicine, both at the University of Connecticut in Storrs; Katherine A. Yeager, PhD, RN, FAAN, is an associate professor in the Nell Hodgson Woodruff School of Nursing at Emory University in Atlanta, GA; and Mary E. Cooley, PhD, RN, FAAN, is a nurse scientist at the Dana-Farber Cancer Institute in Boston, MA, and the scholar-in-residence at the Oncology Nursing Society in Pittsburgh, PA. Zanville, Cohen, Gray, Phillips, Linder, Starkweather, and Cooley contributed to the conceptualization and design. Zanville, Gray, Phillips, Linder, Starkweather, Yeager, and Cooley completed the data collection. Zanville, Gray, Linder, Starkweather, Yeager, and Cooley provided the analysis. All authors contributed to manuscript preparation. Zanville can be reached at, with copy to (Submitted November 2020. Accepted January 6, 2021.)



    Akl, E.A., Morgan, R.L., Rooney, A.A., Beverly, B., Katikireddi, S.V., Agarwal, A., . . . Schünemann, H. (2020). Developing trustworthy recommendations as part of an urgent response (1–2 weeks): A GRADE concept paper. Journal of Clinical Epidemiology, 129(1), 1–11.
    Al-Shamsi, H.O., Alhazzani, W., Alhuraiji, A., Coomes, E.A., Chemaly, R.F., Almuhanna, M., . . . Xie, C. (2020). A practical approach to the management of cancer patients during the novel coronavirus disease 2019 (COVID-19) pandemic: An international collaborative group. Oncologist, 25(6), e936–e945.
    Bowman, B.A., Back, A.L., Esch, A.E., & Marshall, N. (2020). Crisis symptom management and patient communication protocols are important tools for all clinicians responding to COVID-19. Journal of Pain and Symptom Management, 60(2), e98–e100.
    Brown, G., & Lutz, B. (2020, July 10). Care delivery models guide cancer practice during COVID-19. ONS Voice.…
    Bullock, J., Luccioni, A., Hoffman Pham, K., Lam, C.S.N., & Luengo-Oroz, M. (2020). Mapping the landscape of artificial intelligence applications against COVID-19. Journal of Artificial Intelligence Research, 69, 807–845.
    Bunker, D. (2020). Who do you trust? The digital destruction of shared situational awareness and the COVID-19 infodemic. International Journal of Information Management, 55, 102201.
    Burke-Garcia, A., Winseck, K., Jouvenal, L.C., Hubble, D., & Kulbicki, K.M. (2017). A review of social media methods and lessons learned from the National Children’s Study. Journal of Clinical and Translational Science, 1(4), 260–264.
    Cancer Research Institute. (2020). COVID-19 and clinical trials.…
    Centers for Disease Control and Prevention. (2021). COVID data tracker.
    Ceron, W., de-Lima-Santos, M.F., & Quiles, M.G. (2020). Fake news agenda in the era of COVID-19: Identifying trends through fact-checking content. Online Social Networks and Media, 21, 100116.
    Chen, W.C., Teckie, S., Somerstein, G., Adair, N., & Potters, L. (2020). Guidelines to reduce hospitalization rates for patients receiving curative-intent radiation therapy during the COVID-19 pandemic: Report from a multicenter New York area institution. Advances in Radiation Oncology, 5(4), 621–627.
    Chong, Y.Y., Cheng, H.Y., Chan, H.Y.L., Chien, W.T., & Wong, S.Y.S. (2020). COVID-19 pandemic, infodemic and the role of eHealth literacy. International Journal of Nursing Studies, 108, 103644.
    Chowkwanyun, M., & Reed, A.L. (2020). Racial health disparities and COVID-19—Caution and context. New England Journal of Medicine, 383(3), 201–203.
    Cooley, M.E., & Siefert, M.L. (2016). Assessment of multiple co-occurring cancer symptoms in the clinical setting. Seminars in Oncology Nursing, 32(4), 361–372.
    Cuello-Garcia, C., Pérez-Gaxiola, G., & van Amelsvoort, L. (2020). Social media can have an impact on how we manage and investigate the COVID-19 pandemic. Journal of Clinical Epidemiology, 127, 198–201.
    Ćurković, M., Košec, A., & Brečić, P. (2020). Redistributing working schedules using the infective principle in the response to COVID-19. Infection Control and Hospital Epidemiology, 41(9), 1123–1124.
    Debnath, S., Barnaby, D.P., Coppa, A., Makhnevich, A., Kim, E.J., Chatterjee, S., . . . Zanos, T.P. (2020). Machine learning to assist clinical decision-making during the COVID-19 pandemic. Bioelectronic Medicine, 6, 14.
    Dewey, C., Hingle, S., Goelz, E., & Linzer, M. (2020). Supporting clinicians during the COVID-19 pandemic. Annals of Internal Medicine, 172(11), 752–753.
    El-Jardali, F., Bou-Karroum, L., & Fadlallah, R. (2020). Amplifying the role of knowledge translation platforms in the COVID-19 pandemic response. Health Research Policy and Systems, 18, 58.
    Elran-Barak, R., & Mozeikov, M. (2020). One month into the reinforcement of social distancing due to the COVID-19 outbreak: Subjective health, health behaviors, and loneliness among people with chronic medical conditions. International Journal of Environmental Research and Public Health, 17(15), 5403.
    Eysenbach, G. (2009). Infodemiology and infoveillance: Framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet. Journal of Medical Internet Research, 11(1), e11.
    Eysenbach, G. (2020). How to fight an infodemic: The four pillars of infodemic management. Journal of Medical Internet Research, 22(6), e21820.
    Garg, P.K., Kaul, P., Choudhary, D., Turaga, K.K., Singh, M.P., Tiwari, A.R., . . . Yendamuri, S. (2020). Discordance of COVID-19 guidelines for patients with cancer: A systematic review. Journal of Surgical Oncology, 122(4), 579–593.
    Gasper, H., Ahern, E., Roberts, N., Chan, B., & Lwin, Z. (2020). COVID-19 and the cancer care workforce: From doctors to ancillary staff. Seminars in Oncology, 47(5), 309–311.
    Hart, J.L., Turnbull, A.E., Oppenheim, I.M., & Courtright, K.R. (2020). Family-centered care during the COVID-19 era. Journal of Pain and Symptom Management, 60(2), e93–e97.
    Hatcher, S.M., Agnew-Brune, C., Anderson, M., Zambrano, L.D., Rose, C.E., Jim, M.A., . . . McCollum, J. (2020). COVID-19 among American Indian and Alaska Native persons—23 states, January 31–July 3, 2020. Morbidity and Mortality Weekly Report, 69(34), 1166–1169.
    Hsiao, C.P., Dickinson, K., Gonzalez-Mercado, V., Kelly, D.L., Lukkahatai, N., McCabe, M., . . . Saligan, L.N. (2020). Consortium building for nurse scientists interested in symptoms research in the era of precision health. Journal of Nursing Scholarship, 52(2), 183–191.
    Ienca, M., & Vayena, E. (2020). On the responsible use of digital data to tackle the COVID-19 pandemic. Nature Medicine, 27(4), 463–464.
    Johnston, P.A., Kitchens, J.L., LaBree, K., Powers, C.A., Segovia, J.H., Viles, J., . . . Kuban, D.A. (2020). COVID-19 and oncology: Operationalizing best practices across collaborative health systems. Clinical Journal of Oncology Nursing, 24(4), 444–447.
    Jones, K., Hein, L.C., & James, L. (In press). A nursing leadership practicum in the time of COVID19: A southeastern university experience. Nurse Leader.
    Kambhampati, A.K., O’Halloran, A.C., Whitaker, M., Magill, S.S., Chea, N., Chai, S.J., . . . Kim, L. (2020). COVID-19–associated hospitalizations among health care personnel—COVID-NET, 13 states, March 1–May 31, 2020. Morbidity and Mortality Weekly Report, 69(43), 1576–1583.
    Kent, E.E., Ornstein, K.A., & Dionne-Odom, J.N. (2020). The family caregiving crisis meets an actual pandemic. Journal of Pain and Symptom Management, 60(1), e66–e69.
    Killerby, M.E., Link-Gelles, R., Haight, S.C., Schrodt, C.A., England, L., Gomes, D.J., . . . Wong, K.K. (2020). Characteristics associated with hospitalization among patients with COVID-19—Metropolitan Atlanta, Georgia, March–April 2020. Morbidity and Mortality Weekly Report, 69(25), 790–794.
    Kim, S.J. & Bostwick, W. (2020). Social vulnerability and racial inequality in COVID-19 deaths in Chicago. Health Education and Behavior, 47(4), 509–513.
    Kotsen, C., Dilip, D., Carter-Harris, L., O’Brien, M., Whitlock, C.W., de Leon-Sanchez, S., & Ostroff, J.S. (2020). Rapid scaling up of telehealth treatment for tobacco-dependent cancer patients during the COVID-19 outbreak in New York City. Telemedicine and e-Health, 27(1), 20–29.
    Lai, D., Wang, D., Calvano, J., Raja, A.S., & He, S. (2020). Addressing immediate public coronavirus (COVID-19) concerns through social media: Utilizing Reddit’s AMA as a framework for public engagement with science. PLOS ONE, 15(10), e0240326.
    Lucini, D., Gandolfi, C.E., Antonucci, C., Cavagna, A., Valzano, E., Botta, E., . . . Biganzoli, E. (2020). #StayHomeStayFit: UNIMI’s approach to online healthy lifestyle promotion during the COVID-19 pandemic. Acta Biomedica, 91(3), e2020037.
    Lynch, H.F., Largent, E.A., Joffe, S., & DeMichele, A.M. (2018). Protecting clinical trial participants and study integrity in the age of social media. Cancer, 124(24), 4610–4617.
    Mahon, S.M. (2020). Telegenetics: Remote counseling during the COVID-19 pandemic. Clinical Journal of Oncology Nursing, 24(3), 244–248.
    Maniakas, A., Jozaghi, Y., Zafereo, M.E., Sturgis, E.M., Su, S.Y., Gillenwater, A.M., . . . Lai, S.Y. (2020). Head and neck surgical oncology in the time of a pandemic: Subsite-specific triage guidelines during the COVID-19 pandemic. Head and Neck, 42(6), 1194–1201.
    Mavragani, A. (2020). Infodemiology and infoveillance: Scoping review. Journal of Medical Internet Research, 22(4), e16206.
    Millet, G.A., Jones, A.T., Benkeser, D., Baral, S., Mercer, L., Beyrer, C., . . . Sullivan, P.S. (2020). Assessing differential impacts of COVID-19 on black communities. Annals of Epidemiology, 47, 37–44.
    National Academies of Sciences, Engineering, and Medicine. (2020). Rapid expert consultations on the COVID-19 pandemic: March 14, 2020-April 8, 2020. National Academies Press.
    National Academy of Medicine. (2020). Action collaborative on clinician well-being and resilience. National Academies of Sciences, Engineering, and Medicine.
    National Cancer Institute. (2020, June 7). At the crossroads of social media and clinical trials: A workshop on the future of clinician, patient, and community engagement (day 1) [Webinar]. Department of Health and Human Services, National Institutes of Health, Center for Information Technology.
    Nsoesie, E.O., Cesare, N., Müller, M., & Ozonoff, A. (2020). COVID-19 misinformation spread in eight countries: Exponential growth modeling study. Journal of medical Internet research, 22(12), e24425.
    Oncology Nursing Society. (2020). ONS interim guidelines during the COVID-19 pandemic.
    Paterson, C., Gobel, B., Gosselin, T., Haylock, P.J., Papadopoulou, C., Slusser, K., . . . Pituskin, E. (2020). Oncology nursing during a pandemic: Critical reflections in the context of COVID-19. Seminars in Oncology Nursing, 36(3), 151028.
    Pothuri, B., Alvarez Secord, A., Armstrong, D.K., Chan, J., Fader, A.N., Huh, W., . . . Naumann, R.W. (2020). Anti-cancer therapy and clinical trial considerations for gynecologic oncology patients during the COVID-19 pandemic crisis. Gynecologic Oncology, 158(1), 16–24.
    Pozzar, R., Hammer, M.J., Underhill-Blazey, M., Wright, A.A., Tulsky, J.A., Hong, F., . . . Berry, D.L. (2020). Threats of bots and other bad actors to data quality following research participant recruitment through social media: Cross-sectional questionnaire. Journal of Medical Internet Research, 22(10), e23021.
    Prochaska, J.J., Coughlin, S.S., & Lyons, E.J. (2017). Social media and mobile technology for cancer prevention and treatment. American Society of Clinical Oncology Educational Book, 37, 128–137.
    Reinhard, R.J. (2020, January 6). Nurses continue to rate highest in honesty, ethics.…
    Richards, M., Anderson, M., Carter, P., Ebert, B.L., & Mossialos, E. (2020). The impact of the COVID-19 pandemic on cancer care. Nature Cancer, 1(6), 565–567.
    Rivera, D.R., Peters, S., Panagiotou, O.A., Shah, D.P., Kuderer, N.M., Hsu, C.Y., . . . Warner, J.L. (2020). Utilization of COVID-19 treatments and clinical outcomes among patients with cancer: A COVID-19 and Cancer Consortium (CCC19) cohort study. Cancer Discovery, 10(10), 1514–1527.
    Selden, T.M., & Berdahl, T.A. (2020). COVID-19 and racial/ethnic disparities in health risk, employment, and household composition. Health Affairs, 39(9), 1624–1632.
    Soltan, A.A.S., Kouchaki, S., Zhu, T., Kiyasseh, D., Taylor, T., Hussain, Z.B., . . . Clifton, D.A. (2020). Rapid triage for COVID-19 using routine clinical data for patients attending hospital: Development and prospective validation of an artificial intelligence screening test. Lancet Digital Health.
    Sprik, P., Janssen Keenan, A., Boselli, D., Cheeseboro, S., Meadors, P., & Grossoehme, D. (2020). Feasibility and acceptability of a telephone-based chaplaincy intervention in a large, outpatient oncology center. Supportive Care in Cancer.
    Subbiah, I.M., Hamilton, E., Knoll, M., Shanahan, K., & Meisel, J. (2019). A big world made small: Using social media to optimize patient care. American Society of Clinical Oncology Educational Book, 39, e212–e218.
    Sullivan, M., Bouffet, E., Rodriguez-Galindo, C., Fineman, S.L., Khan, M.S., Kearns, P., . . . Pritchard Jones, K. (2020). The COVID-19 pandemic: A rapid global response for children with cancer from SIOP, COG, SIOP-E, SIOP-PODC, IPSO, PROS, CCI, and St. Jude Global. Pediatric Blood and Cancer, 67(7), e28409.
    Tangcharoensathien, V., Calleja, N., Nguyen, T., Purnat, T., D’Agaostino, M., Garcia-Saiso, S., . . . Briand, S. (2020). Framework for managing the COVID-19 infodemic: Methods and results of an online, crowdsourced WHO technical consultation. Journal of Medical Internet Research, 22(6), e19659.
    Tayarani-Najaran, M.H. (2020). Applications of artificial intelligence in battling against Covid-19: A literature review. Chaos, Solitons, and Fractals, 142, 110338.
    Thompson, M.A. (2014). Social media in clinical trials. American Society of Clinical Oncology Educational Book, 34, e101–e105.
    Thompson, M.A., & O’Regan, R.M. (2018). Social media and clinical trials: The pros and cons gain context when the patient is at the center. Cancer, 124(24), 4618–4621.
    Upadhaya, S., Yu, J.X., Oliva, C., Hooton, M., Hodge, J., & Hubbard-Lucey, V.M. (2020). Impact of COVID-19 on oncology clinical trials. Nature Reviews Drug Discovery, 19(6), 376–377.
    U.S. Department of Health and Human Services, Food and Drug Administration. (2020). Enhancing the diversity of clinical trial populations—Eligibility criteria, enrollment practices, and trial designs: Guidance for industry.
    Von Ah, D., Brown, C.G., Brown, S.J., Bryant, A.L., Davies, M., Dodd, M., . . . Cooley, M.E. (2019). Research agenda of the Oncology Nursing Society: 2019–2022. Oncology Nursing Forum, 46(6), 654–669.
    Webb Hooper, M., Nápoles, A.M., & Pérez-Stable, E.J. (2020). COVID-19 and racial/ethnic disparities. JAMA, 323(24), 2466–2467.
    Weinstein, J.N., Geller, A., Negussie, Y., & Baciu, A. (Eds.). (2017). Communities in action: Pathways to health equity. National Academies Press.
    Withycombe, J.S., Haugen, M., Zupanec, S., Macpherson, C.F., & Landier, W. (2019). Consensus recommendations from the Children’s Oncology Group Nursing Discipline’s state of the science symposium: Symptom assessment during childhood cancer treatment. Journal of Pediatric Oncology Nursing, 36(4), 294–299.
    Yahalom, J., Dabaja, B.S., Ricardi, U., Ng, A., Mikhaeel, N.G., Vogelius, I.R., . . . Specht, L. (2020). ILROG emergency guidelines for radiation therapy of hematological malignancies during the COVID-19 pandemic. Blood, 135(21), 1829–1832.
    Yancy, C.W. (2020). COVID-19 and African Americans. JAMA, 323(19), 1891–1892.
    Zame, W.R., Bica, I., Shen, C., Curth, A., Lee, H.S., Bailey, S., . . . van der Schaar, M. (2020). Machine learning for clinical trials in the era of COVID-19. Statistics in Biopharmaceutical Research, 12(4), 506–517.
    Zeidan, A.M., Boddu, P.C., Patnaik, M.M., Bewersdorf, J.P., Stahl, M., Rampal, R.K., . . . Mascarenhas, J. (2020). Special considerations in the management of adult patients with acute leukemias and myeloid neoplasms in the COVID-19 era: Recommendations from a panel of international experts. Lancet Haematology, 7(8), e601–e612.