Natasha Clinton, MSN, APRN, AOCNP, BCMAS

The rapid progression of novel immune-based treatment strategies in solid tumors—beginning with the approval of immune checkpoint inhibitors (ICIs) for melanoma in 2011 and subsequent approval of numerous agents in the ICI therapeutic category—has revolutionized treatment of advanced cancers that were deemed invariably fatal until the past decade.

 Faster development of novel biomarker-driven targeted therapies has accelerated hope and optimism about converting advanced solid tumors into chronic diseases. These advances have also led to the recognition of other clinical challenges, including unforeseen observations and complications associated with choosing the sequencing of appropriate therapeutic interventions as well as the management of drug-related complications.

One critical enigma facing clinicians is how to differentiate between pseudoprogression (PSP), true disease progression (TDP), and hyperprogression (HPD). These phenomena are observed in patients treated with ICIs targeting CTLA-4, PD-1, or PD-L1 that are approved for use across multiple types of advanced cancers. The lack of consensus or an analytic framework to decipher and differentiate between early indications of PSP, TDP, and HPD may expose patients to avoidable harm.

Another challenge centers around selecting the most appropriate therapeutic intervention when broad-based genomic profiling results reveal multiple actionable biomarkers vs actionable genomic driver mutations such as those found in 

, and a number of other targetable pathogenic genomic alterations. Selecting the right drug at the right time for patients is further complicated by these considerations:

The disparate timing of receiving results from PD-1/PD-L1 immunohistochemistry testing vs next-generation sequencing (NGS) testing 

 Determining the adequacy of NGS panel testing with negative results, whether using a whole exome sequencing or comprehensive genomic profiling approach

For this review we will confine our discussion to the clinical impact associated with the determination of PSP, TDP, and HPD following ICI therapy. Even the definitions of TDP, PSP, and HPD have not reached uniform consensus, so we will focus on clinical implications.

Although an accurate consensus has not been reached on defining PSP or HPD, differentiating between those clinical states is critically important. PSP indicates efficacy of ICI therapy, whereas HPD portrays ineffective treatment with ICIs resulting in a rapid negative clinical outcome in most cases. PSP is a type of response to ICI therapy accompanied by an apparent initial increase in tumor size or new lesions, which potentially appear upon radiological assessment, followed by an eventual decrease in tumor burden. Although this response favors patients receiving ICI therapy, a lack of awareness can lead to premature discontinuation of treatment because of an incorrect clinical interpretation of disease progression.

The incidence of ICI therapy–associated PSP varies from 3.70% to 15% in different tumor types.

 PSP is a relatively uncommon response defined as an initial increase of tumor size followed by a measurable response to treatment. ICI therapy–associated PSP results from an exacerbated immune cell infiltration in the tumor bed (T cells expressing CD103+ and CD8+).

Another postulated mechanism of PSP described by Cohen et al11 occurred in a case of PSP involving brain metastases in a patient with melanoma after treatment with pembrolizumab (Keytruda). The histology revealed an inflammatory reaction identified as isolated clusters of tumor cells surrounded by reactive astrocytosis and inflammatory cells.

 PSP associated with ICI therapy carried a higher likelihood of 1-year survival when compared with TPD.

 Failure to distinguish PSP from TPD may result in premature discontinuation of treatment with ICI, leading to adverse outcomes. It is crucial to distinguish between TPD and PSP.

HPD can be defined as an accelerated tumor growth pattern after exposure to ICI therapy, with an increase in the absolute mass of tumor cells in a relatively short time. Possible explanations of HPD in response to ICI may include the expansion of PD-1–positive regulatory T cells, exhaustion of compensatory T cells, modulation of protumorigenic immune cell subsets, and activation of aberrant inflammation cell cycle signaling.

 HPD may be observed as a rapid escalation in the size and bulk of masses of measurable tumor volume, the appearance of numerous new lesions, and/or rapid deterioration in organ function leading to symptomatic disease progression (similar to jaundice from a rise in bilirubin and liver enzymes), and/or shortness of breath from the progression of metastases in the lungs or deterioration of brain metastases leading to worsening central nervous system symptoms. Efforts have been made to define HPD based on tumor growth rate (TGR), tumor growth kinetics (TGK), and other RECIST parameters to better define HPD. However, such efforts are often in isolation and limited to institution-based criteria.

 published a study after exhaustive and systematic analysis to define HPD. They concluded that the clinical interpretation of HPD appears diverse, with the incidence of HPD varying from 5.9% to 43.1% across studies examined in their meta-analysis. They also highlighted the critical unmet need for establishing uniform and clinically relevant criteria based on currently available evidence to define HPD. One of the most compelling reasons to identify true HPD is the association of patients with HPD with extremely poor prognosis. Several studies reported worse progression-free survival and overall survival in the subgroup analysis of patients with HPD.

 Earlier identification of patients with HPD could lead to quicker adjustment of therapeutic selection to improve the dismal clinical outcomes currently associated with HPD. Because there remains no clear consensus around the definition of HPD at the time of writing this article, we simply define HPD as resulting in the rapid clinical acceleration of tumor growth resulting in shortened patient survival.

With the rapid strides in immune-based treatment options in patients with advanced solid tumors in the past decade, we have seen significant clinical improvement in patient quality of life and quantitative improvement of clinical outcomes. However, increased utilization of ICI therapies has also led to the recognition of new clinical challenges associated with a small but not insignificant number of patients, where failure to distinguish between TPD, PSP, and HPD clearly has an impact on patient lives. It is critical that our research communities start paying more attention to and providing clinical guidance around the following issues:

Recognition of HPD as a critical clinical phenomenon and not just a concept characterized by acceleration of measurable and quantifiable disease by radiologic assessment 

With the reported incidence of HPD being higher compared with PSP, emphasizing the importance of identifying HPD as early as possible, because it can occur within weeks of starting ICI therapy and result in higher mortality 

Establish clear criteria that may facilitate and support conclusive assessment of HPD vs either true PD or PSP, which may include assessment of TGR, TGK, number and increase in metastatic lesions, growth in the size of the target lesions, and additional RECIST-defined criteria

Create a consensus of baseline timing of imaging studies prior to starting ICI treatment as it can impact interpretation of subsequent studies either as a standard of care or symptom directed protocols to make it easier to correlate to pretreatment findings to distinguish between TPD, PSP, and HPD 

Continue research to establish whether HPD is related to specific cancer subtypes or other patient comorbidities, including preexisting conditions

 Identify whether HPD is therapeutic agent specific or class specific (ie, like anti– CTLA, anti–PD-1, or anti–PD-L1 therapies)

Although ICI approaches are now a mainstay in therapy, challenges to optimal benefit, such as PSP, TDP, and HPD, require continued vigilance.

1. Balar AV, Weber JS. PD-1 and PD-L1 antibodies in cancer: current status and future directions. 

. 2017;66(5):551-564. doi:10.1007/s00262-017-1954-6 

2. Ribas A, Wolchok JD. Cancer immunotherapy using checkpoint blockade. 

. 2018;359(6382):1350-1355. doi:10.1126/science.aar4060 

3. Nishino M. Pseudoprogression and measurement variability. 

. 2016;34(28):3480-3481. doi:10.1200/JCO.2016.67.6759

4. Reckamp KL. Real-world pseudoprogression: an uncommon phenomenon. 

. 2018;13(7):880-882. doi:10.1016/j. jtho.2018.05.011 

5. Doherty MK, Jao K, Shepherd FA, Hazrati LN, Leighl NB. Central nervous system pseudoprogression in a patient treated with PD-1 checkpoint inhibitor. 

. 2015;10(10):e100-e101. doi:10.1097/JTO.0000000000000587 

6. Lewis GD, Jonasch E, Shah AY, et al. Renal cell carcinoma brain metastasis with pseudoprogression and radiation necrosis on nivolumab after previous treatment with stereotactic radiosurgery: an illustrative case report and review of the literature. 

. 2018;8(5):e262-e265. doi:10.1016/j.prro.2018.03.003 

7. Fujimoto D, Yoshioka H, Kataoka Y, et al. Pseudoprogression in previously treated patients with non–small cell lung cancer who received nivolumab monotherapy. 

. 2019;14(3):468-474. doi:10.1016/j.jtho.2018.10.167 

8. Ribas A, Wolchok JD, Robert C, et al. P0116 Updated clinical efficacy of the anti–PD-1 monoclonal antibody pembrolizumab (MK-3475) in 411 patients with melanoma. 

. 2015;51(suppl 2):e24. doi:10.1016/j.ejca.2015.06.072

9. Nishino M, Giobbie-Hurder A, Manos MP, et al. Immune-related tumor response dynamics in melanoma patients treated with pembrolizumab: identifying markers for clinical outcome and treatment decisions. 

. 2017;23(16):4671-4679. doi:10.1158/1078- 0432.CCR-17-0114 

10. Rocha P, Hardy-Werbin M, Naranjo D, et al. CD103+CD8+ lymphocytes characterize the immune infiltration in a case with pseudoprogression in squamous NSCLC. 

. 2018;13(10):e193-e196. doi:10.1016/j.jtho.2018.05.008 

11. Cohen JV, Alomari AK, Vortmeyer AO, et al. Melanoma brain metastasis pseudoprogression after pembrolizumab treatment. 

. 2016;4(3):179-182. doi:10.1158/2326-6066.CIR-15-0160 

12. Kurra V, Sullivan RJ, Gainor JF, et al. Pseudoprogression in cancer immunotherapy: rates, time course and patient outcomes. 

. 2016;34(suppl 15):6580. doi:10.1200/JCO.2016.34.15_suppl.6580

13. Frelaut M, Le Tourneau C, Borcoman E. Hyperprogression under immunotherapy. 

. 2019;20(11):2674. doi:10.3390/ ijms20112674

14. Park HJ, Kim KW, Won SE, et al. Definition, incidence, and challenges for assessment of hyperprogressive disease during cancer treatment with immune checkpoint inhibitors: a systematic review and meta-analysis. 

. 2021;4(3):e211136. doi:10.1001/ jamanetworkopen.2021.1136 

15. Champiat S, Dercle L, Ammari S, et al. Hyperprogressive disease is a new pattern of progression in cancer patients treated by anti–PD-1/ PD-L1. 

. 2017;23(8):1920-1928. doi:10.1158/1078- 0432.CCR-16-1741 

16. Saâda-Bouzid E, Defaucheux C, Karabajakian A, et al. Hyperprogression during anti–PD-1/PD-L1 therapy in patients with recurrent and/or metastatic head and neck squamous cell carcinoma.

. 2017;28(7):1605-1611. doi:10.1093/annonc/mdx178 

17. Ferrara R, Mezquita L, Texier M, et al. Hyperprogressive disease in patients with advanced non–small cell lung cancer treated with PD-1/ PD-L1 inhibitors or with single-agent chemotherapy. 

. 2018;4(11):1543-1552. doi:10.1001/jamaoncol.2018.3676 

18. Sasaki A, Nakamura Y, Mishima S, et al. Predictive factors for hyperprogressive disease during nivolumab as anti-PD1 treatment in patients with advanced gastric cancer. 

. 2019;22(4):793- 802. doi:10.1007/s10120-018-00922-8

Articles

Advances in the field have also led to the recognition of other clinical challenges, including unforeseen observations and complications associated with choosing the sequencing of appropriate therapeutic interventions as well as the management of drug-related complications.

Differentiating Pseudoprogression From Hyperprogression in Patients Treated With Immunotherapies

Precision Medicine (PM) is “an approach to disease prevention and treatment that seeks to maximize effectiveness by considering individual variability in genes, environment, and lifestyle,” according to the Precision Medicine Initiative (PMI).

 After former President Obama announced the PMI in his State of the Union address on January 20, 2015—“to bring us closer to curing diseases like cancer and diabetes and to give all of us access to the personalized information we need to keep ourselves and our families healthier”—the National Health Institute and other global agencies commenced a group under the PMI called the PMI Cohort Program.

The goal of PM is to advance medical and scientific discoveries to offer more tailored, precise, and accurate health interventions to maximize the health benefits for patients.

 Essential components of PM include the integration of information from several different sources, including genetic and genomic profiles, imaging data, records from wearable health-tracking devices and lifestyle choices, germline data, and pharmacogenomics. The access and application of these data and associated bioinformatics, using computing power and technological expertise to translate PM into personalized health care, are key.

For community practices, using PM will be greatly beneficial to patients and the practice. To maximize these benefits, PM needs to be integrated into the fabric of the community setting. All professionals in a practice will have to be involved in the development of a PM system, including physicians, pharmacists, lab personnel, nurses, and the patients. Although there have been obstacles to implementing diagnostic and screening tests, these can be overcome and will provide more options for patients with cancer.

Next-generation sequencing (NGS), which is rapidly replacing Sanger sequencing, has matured enough as a technology and found its place both in clinical practice and research. In addition, whole exome sequencing (WES) and/or whole genome sequencing (WGS) are becoming part of daily operation for oncologists and hematologists for exploring clinical trials and drug development for malignancies. The cost efficiency of NGS has improved significantly due to technological, scientific, and operational advances. The cost of deciphering the entire human genome has dropped from $10,000 in 2011 to approximately $1000 in 2021.

 Other drivers of PM include more accurate sequencing, a growing number of targeted therapies, and the recognition of biodiversity in the human genome— especially in oncology and rheumatic illnesses.

Even in monetary aspects, the global market for PM is growing rapidly. Market research estimated the 2016 global market at $44 billion in revenue, and this revenue is forecast to more than triple to $140 billion by 2026.

The rapid strides in sequencing techniques, bioinformatics, and PM have not been matched with efforts of implementation in day-to-day practice. Factors like integration into practice guidelines, lack of consensus and standardization between different stakeholders regarding minimum number of mutational analysis, germline studies, platforms for testing, and payer coverage threaten realization of PM.

In addition to factors mentioned above, the biggest challenge for success in PM adoption is lack of diversity in the knowledge of genomics and bioinformatics in research and studies. Minority communities often face discrimination in health care and receive poor medical treatment.

 Outreach to these communities, especially in the research field, has also been characterized by a long history of exploitation, abuse, and marginalization.

 Although hesitancy from ethnic minorities is frequently cited as an excuse for the lack of representative data in PM and clinical trials, real-life observation is somewhat different, with researchers observing that willingness to participate did not differ significantly between ethno-racial groups.

 They also argued that underrepresentation of minority populations is more likely due to the research design of the study or limited accessibility.

Results from genome-wide association studies (GWAS) representing 1.7 million samples conducted in 2009 showed that 96% of participants were of European ancestry. Seven years later, the same GWAS analysis revealed that despite the colossal 35 million samples collected, 81% of participants were still of European ancestry. Clearly, racial and ethnic diversity of the samples still had a long way to go.10 The successful implementation of PM requires the clinical integration of the following (FIGURE 1):

Molecular testing of patients for actionable mutations

Interpretation of molecular profiling results and identification of matched therapies

Identification of patients for clinical trials

The creation of a longitudinal journey to understand pharmacogenomics

Equitable access to genomic and genetic as well as treatment data

With so many testing options, including NGS, WES, WGS, and whole transcriptome sequencing, healthcare providers now face a complex decision: whether to outsource this testing to centralized laboratories, implement it in their own labs, or create a hybrid model bringing part of the testing in house and using tertiary labs with full bioinformatics and sophisticated testing for thousands of genes for support. With the advent of NGS panels, genomic profiling has become leaner, cheaper, and more user friendly. Everything is quicker in house, with much less chance of losing important material or information. One of the best arguments for in-house genomic profiling is the control it affords over the preanalytical parameters, tissue specimen selection, and sample quality.

For many community oncologists, the latter option to create a collaborative model may enhance the uptake of appropriate molecular testing and address an unmet need, as most of the underserved, marginalized population is served by small- to medium-sized community cancer clinics. We must focus on doing those routine tests quickly, cost effectively, and as locally as possible in collaboration with tertiary labs that have additional testing capabilities and bioinformatics.

Additionally, centralized testing in a collaborative model is another very valuable option. When an FDA-approved treatment option is not available based on local minipanel testing results, additional testing with a much larger panel may provide options for clinical trials for new drug development. This testing may also identify germline mutations, such as BRCA1/2 or other homologous repair defects, and identify other family members at risk. This would allow others to implement appropriate clinical interventions to monitor their risk for disease. A bioinformatics platform will enhance assimilation of genomic, pharmacogenomics, and germline data to create a longitudinal journey and ultimately bring health care equity, address disparities, and enhance new drug developments. Benefits of insourcing NGS include the following (FIGURE 2):

In summary, even though the field of PM is still evolving and changing, driver mutation and biomarker-guided therapies have already improved treatment options for thousands of patients with cancer and thousands more are eligible for clinical trials. Because of limitations in access to overall testing, limited uptake of testing—at the most, 25% in non–small cell lung cancer in Caucasians and 14% in ethnic minorities—and skewed data disproportionately representative of Caucasians, the success of PM is not likely to be accomplished unless we explore different ways to approach testing. These include:

Making widespread testing accessible locally;

Improving access to testing for minorities;

Performing additional testing at tertiary centers when an actionable mutation is not identified; and

Adding germline testing (if NGS panel only includes somatic testing)

1. National Institutes of Health. The Precision Medicine Initiative Cohort Program —building a research foundation for 21st century medicine. September 17, 2015. Accessed April 19, 2021. https://bit.ly/2S4v8mF

2. Collins FS, Varmus H. A new initiative on precision medicine. 

. 2015;372(9):793-795. doi:10.1056/NEJMp1500523 

3. Ashley EA. Towards precision medicine. 

. 2016;17(9):507-522.doi:10.1038/nrg.2016.86 

4. Thermo Fisher Ion 520 DNA sequencing chip comparison and cost analysis report. ResearchAndMarkets.com. News release. February 9, 2018. Accessed April 27, 2021. https://bit.ly/3vimZcC 

5. Global precision medicine market to reach $141.70 billion by 2026, reports BIS Research. BIS Research. News release. December 15, 2017. Accessed April 18, 2021. https://prn.to/3sYEwF6 

6. Sholl LM, Aisner DL, Varella-Garcia M, et al; LCMC Investigators. Multi-institutional oncogenic driver mutation analysis in lung adenocarcinoma: the lung cancer mutation consortium experience. 

. 2015;10(5):768-777. doi:10.1097/JTO.0000000000000516 

7. Bhopal RS. Racism in health and health care in Europe: reality or mirage? 

. 2007;17(3):238-241. doi:10.1093/eurpub/ckm039 

8. Cohn EG, Henderson GE, Appelbaum PS. Distributive justice, diversity, and inclusion in precision medicine: what will success look like? 

. 2017;19(2):157-159. doi:10.1038/gim.2016.92 

9. Wendler D, Kington R, Madans J, et al. Are racial and ethnic minorities less willing to participate in health research? 

. 2006;3(2):e19. doi:10.1371/journal.pmed.0030019 

10. Popejoy AB, Fullerton SM. Genomics is failing on diversity. 

. 2016;538(7624):161-164. doi:10.1038/538161a

The goal of precision medicine is to advance medical and scientific discoveries to offer more tailored, precise, and accurate health interventions to maximize the health benefits for patients.

The Role of In-Office Next Generation Sequencing to Advance Precision Medicine in Community Oncology

The crisis of coronavirus disease 2019, also known as COVID-19, presents a set of unprecedented circumstances to the health care community. The disease has a particular impact on patients with cancer and their oncology care teams who are trying to maintain the right balance between the use of immunosuppressive treatment and risk of cancer progression. Wenhua Liang, PhD, and colleagues analyzed the risk for severe COVID-19 in patients with cancer.1 They reported that patients with cancer might have a higher risk of COVID-19 than individuals without cancer. They emphasized that patients with malignancy had poorer outcomes from COVID-19, providing a timely reminder to physicians that more intensive attention should be paid to patients with cancer to prioritize treatment versus risk of death and adverse outcomes. Patients who underwent chemotherapy or surgery in the past month had a numerically higher risk (3 of 4 patients [75%]) of clinically severe events than did those not undergoing chemotherapy or surgery, observed by logistic regression (odds ratio, 5.34; 95% CI, 1.80-16.18; 

 = .0026) after adjusting for other risk factors, including age, smoking history, and other comorbidities. 

The authors of this study have proposed 3 major strategies for treating patients with cancer in the COVID-19 crisis. The first approach is an intentional postponing of adjuvant chemotherapy or elective surgery for stable cancer in endemic areas. Second, stronger personal protection provisions should be made for patients with cancer or cancer survivors. Third, more intensive surveillance or treatment should be considered when patients with cancer are infected with COVID-19, especially in older individuals or those with other comorbidities.

Oncologists and institutions caring for these patients face the continued challenges of administering treatment while simultaneously reducing the risk of complications in the event they end up contracting COVID-19. Stopping chemotherapy may be an option for patients in complete remission on maintenance therapy. In those patients, we may be able to switch chemotherapy from intravenous to oral therapies. This change would decrease the frequency of clinic visits. A chemotherapy break may be an option when feasible. Delays or modifying adjuvant treatment may be balanced with the risk of recurrence. The prophylactic growth factors and antibiotics in high-risk chemotherapy regimens is of paramount importance. When the absolute benefit of adjuvant chemotherapy may be quite small, and if non-immunosuppressive options are available (eg, hormonal therapy in estrogen receptorpositive early-stage breast cancer), risk of COVID-19 infection may be considered as an additional factor in weighing the patient’s available treatment options.

Providers caring for patients with cancer undergoing cytotoxic chemotherapy need to consider changing their treatment plan when feasible to reduce the risk of life-threatening complications as well as reducing the frequency of their clinic visits. Targeted therapies are approved for a number of aggressive cancers from non–small cell lung cancer, stage IV melanoma, to acute myeloid and lymphoid leukemia. These therapeutic options offer an opportunity to consider treatment of patients with the likelihood of a better response while at the same time increasing dose density and intensity without raising the toxicity profile.

Precision medicine–guided targeted therapies as well as immunotherapy may have a special role in identifying patients who may need cancer treatment. Most targeted agents are orally administered. The toxicity and adverse event profiles of many orally administered targeted therapies is significantly different from chemotherapy. A much higher complication rate from cytotoxic chemotherapy places patients with cancer at a much higher risk of complications from COVID-19 infection. Rigorous biomarker testing and appropriate therapeutic choice should be considered in this patient population, especially in the face of a global pandemic.

Assessing Cancer by Treatment Priority Determination: Top, Intermediate, and Low Priority

Instead of an arbitrary approach, a system to determine the priority for consultation and treatment of patients with cancer may provide a consistent approach for all patients and providers (

 It is also important to avoid, as much as possible, having different levels of care. We recommend following an “assessment for patients with cancer and treatment priority determination” that would assist cancer clinics and decision makers in the management of these patients. Given the dynamic situation, it is likely that this will vary from day to day, and daily accommodation reassessment may be required. The patient priority assessment and classification would allow flexibility determined by the local circumstances and available resources. The local or regional circumstances and the availability of resources may influence a cancer clinic’s ability to follow the criteria.

This virus was previously referred to as novel betacoronavirus severe acute respiratory syndrome virus coronavirus 2 (SARS-CoV-2).

 What started in early December 2019 with 3 patients diagnosed with unexplained pneumonia in the Wuhan province of China has led to a global pandemic. At the time this article was written, more than 3 million cases have been reported and 207,973 deaths across Europe, the Americas, Western Pacific, Eastern Mediterranean, Southeast Asia, and Africa are attributed to the disease.

 The United States alone has 1,005,147 cases and 57,505 deaths.

In March 2020, the World Health Organization declared COVID-19, caused by SARS-CoV-2, a public health emergency of international magnitude and a global pandemic.

 According to the World Health Organization, the definition of pandemic is a worldwide spread of a new disease for which most people do not have immunity.

A sudden surge in the cases of COVID-19 due to the pandemic, along with efforts to contain it, has led to multiple challenges that no country has experienced in the last several decades. The global pandemic from COVID-19 poses a unique set of challenges not only for patients with cancer who need their treatment, but also for caregivers, oncologists, and the overall care team. It is recognized that there is a need to treat patients with cancer during a pandemic, due to their immunocompromised state from the nature of their disease or type of treatment they are receiving. Further, it is of paramount importance that the oncology care team develop and evolve a systemic approach that prioritizes patients, disease, and types of treatment. So far, the efforts of organizations and individual oncologists are being rapidly outpaced by the increasing number of patients with COVID-19. It is likely that this will be a dynamic situation that will vary each day.

Deaths from COVID-19 have been caused by multiple organ dysfunction. This observation might be attributable to the widespread distribution of angiotensin-converting enzyme 2—the functional receptor for SARS-CoV-2—in multiple organs.

 Patients with cancer are more susceptible to infection than individuals without cancer because of their malignancy and anticancer treatments, such as chemotherapy.

 These patients might be at increased risk of COVID-19 and have a poorer prognosis. 

Rapid growth in the number of patients with COVID-19 symptoms has led to capacity pressures to the health care system on a local, regional, and national level. Cancer clinics and hospital inpatient and outpatient areas have started experiencing capacity challenges. Patients with cancer are faced with difficult decisions and anxieties related to the risks of treatment versus exposure and increased risk of contracting COVID-19. It is expected that the COVID-19 global pandemic will hit in 1 or more waves. At the peak of the COVID-19 wave, a significant portion of hospital or clinic staff will be ill or unavailable to work (eg, due to school closures, family obligations, fear, disease, illness, etc.

COVID-19 has left an indelible mark on the history of the world. Although the death toll world wide approaches 140,000, it is only through humanity’s collective ingenuity and compassion to care for one another will we weather this pandemic. We are making daily progress and we applaud all health care workers who find themselves on the frontlines against this disease.

1. Liang W, Guan W, Chen R, et al. Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China. Lancet Oncol. 2020;21(3):335-337. doi:10.1016/S1470-2045(20)30096-6 

2. Dietz JR, Moran MS, Isakoff SJ, et al. Recommendations for prioritization, treatment, and triage of breast cancer patients during the COVID-19 pandemic. the COVID-19 pandemic breast cancer consortium [published online ahead of print, 2020 Apr 24]. Breast Cancer Res Treat. 2020;1-11. doi:10.1007/s10549-020-05644-z 

3. Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507-513. doi:10.1016/S01406736(20)30211-7. 

4. Coronavirus disease (COVID-19) pandemic. Coronavirus disease (COVID-19) outbreak situation. World Health Organization website. Updated March 31, 2020. Accessed March 31, 2020. bit.ly/2QZvZlg. 

5. Coronavirus Disease 2019 (COVID-19). Cases in U.S. Centers for Disease Control and Prevention website. Updated March 31, 2020. Accessed March 31, 2020. https://bit.ly/2vKBtc6. 

6. WHO Director-General’s opening remarks at the media briefing on COVID-19 - 11 March 2020. World Health Organization website. Published March 11, 2020. Accessed March 31, 2020. https://bit.ly/3al0yJE. 

7. Zhou P, Yang XL, Wang XG, et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature. 2020;579(7798):270-273. doi: 10.1038/s41586-020-2012-7 

8. Hamming I, Timens W, Bulthuis ML, Lely AT, Navis G, van Goor H. Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis. J Pathol. 2004;203(2):631-637. doi: 10.1002/path.1570 

9. Kamboj M, Sepkowitz KA. Nosocomial infections in patients with cancer. Lancet Oncol. 2009;10(6):589-597. doi: 10.1016/S1470-2045(09)70069-5

"We recommend  following an assessment for patients with cancer and treatment priority determination that would assist in the management of these patients."

Natasha Clinton, MSN, APRN, AOCNP, BCMAS | Authors

Articles

Differentiating Pseudoprogression From Hyperprogression in Patients Treated With Immunotherapies

The Role of In-Office Next Generation Sequencing to Advance Precision Medicine in Community Oncology

COVID-19 Presents an Opportunity for Precision Medicine to Play Expanded Role in Care