Giorgio V. Scagliotti, MD, PhD

The rapid outbreak of COVID-19 disease on a global scale found the community of clinicians and scientists largely unprepared to face the devastating effects of the pandemic. The stress on health-care systems revealed their weaknesses and brought about associated financial crises.

Defining the clinical characteristics and patient vulnerabilities to COVID-19 is of great importance for public health and has been a high priority during the spread of the disease. Beginning at the end of 2019, it seemed that almost every peer-reviewed journal featured a weekly growing number of papers reporting on epidemiologic, diagnostic, and therapeutic aspects associated with the spread of SARS-CoV-2, including papers published without a formal peer-review process. A very basic search on Medline showed the term “COVID-19” was included in the title of more than 22,000 publications from January 1 through June 20, 2020.

The sense of urgency led to all health-care practitioners wanting to participate in efforts to collect data on their patients with cancer. In extreme situations, controversial reports¹ ended up in retraction of articles.² The rush to gather and disseminate as much information as quickly as possible is understandable, since we are all desperate to find the best ways to care for our patients. However, a question we must ask is how much of the resultant “chaos” of data has advanced us toward this goal?

Cancer and COVID-19: Revisiting Early Data

Patients with cancer are supposed to be at higher risk for severe complications of COVID-19 due to immunosuppressed status caused by the tumor, oncology treatments, or both. An initial retrospective review from China indicated the risks of severe COVID-19 and more rapid clinical deterioration were higher in patients with cancer compared with patients without cancer.³ Subsequently, another study reported that the infection rate of SARS-CoV-2 was higher in patients with cancer as compared with the general population (0.79% vs 0.37%).⁴

Additional cross-sectional studies with prolonged follow-up were clearly needed beyond the experience in a single region or country to establish whether cancer is associated with a higher infection rate. More organized study was also needed to account for the mortality rates in the overall population reported initially in China (3%) and the higher levels reported in some European countries, including Italy (around 10%).

Recently, at least three different cross-sectional studies have been published: two about the outcomes of patients with different tumor types and one specifically in patients with lung cancer.^5-7 Two of these studies are reviewed in the current issue of The ASCO Post. Although the three studies are pretty similar in terms of investigating the risks for patients with cancer during the COVID-19 pandemic, they differ in terms of patient populations, how the patients were enrolled, collection and extraction of data, and outcomes definitions.

“The rush to gather and disseminate as much information as quickly as possible is understandable, since we are all desperate to find the best ways to care for our patients.”

— Giorgio V. Scagliotti, MD, PhD

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The sense of urgency in collecting data unfortunately generates the detrimental effect of not being able to cross-compare results because of potential biases and confounding factors. The lack of information on COVID-19–related mortality in age-specific subgroups of patients without cancer makes it difficult to conclude that patients with cancer are at higher risk. Taking into consideration the relatively quick evolution of the pandemic in the absence of predefined guidelines (ie, different levels of patient triage, differences in the management of COVID-19 disease, different values for R₀ [number of cases an infected person will cause during an infectious period] in the area where the data were collected, different timing of general lockdown), the results of each individual study could be interpreted differently depending on the time over which they collected data in relation to the
evolution of the pandemic curve. Epidemiologic studies to estimate cancer mortality in a specific time frame are clearly needed to generate more solid conclusions.

This need is essentially driven by two considerations. First, analysis of the effect of the pandemic on mortality over a limited period may be misleading, requiring assessment of cancer-specific mortality over a longer period. Second, fear of COVID-19 may have been responsible for a delay in diagnosis of suspected cancer and a delay in treatment for many individuals, with the potential effect of such delays on mortality also needing long-term assessment.

Differences and Similarities Among Studies

The three studies reported a different level of access to intensive treatments for patients with cancer. In the earliest onslaught of the pandemic, treatment decisions in emergency rooms and intensive care units were essentially dictated by the greater chances of therapeutic success. For the physicians involved in these decisions, those days will forever remain among the saddest moments of their professional lives.

In the end, all three studies confirmed for patients with cancer what had already been observed in a previous study⁸ in an unselected Chinese population with COVID-19—risk factors for mortality include older age and the presence of comorbid conditions. In addition, the studies indicate that higher Eastern Cooperative Oncology Group performance status and active types of cancer represent risk factors, whereas levels of risk associated with cancer-related and other therapeutic interventions differed among the studies, and the impact of active smoking on COVID-19 disease outcomes was not uniformly sorted out.

Digital Technology

Although digital technology will contribute to generating contact tracing tools to better control future outbreaks of COVID-19, it will also be useful to plan in advance a series of digital tools and facilities that, in the setting of human data science, will expand our ability to intercept and fight diseases earlier in their course. These digital tools also will help clinicians by generating machine-learning platforms to produce real-time data to properly treat all patients with cancer in any emergency setting. 

DISCLOSURE: Dr. Scagliotti has received honoraria from AstraZeneca, Roche, Takeda, MSD, BeiGene, and Janssen; has had a consulting or advisory role with BeiGene; has served on a speakers’ bureau for AstraZeneca and Roche; and has received travel expenses from Bayer and AstraZeneca.

REFERENCES

1. Mehra MR, Desai SS, Ruschitzka F, et al: Retracted: Hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19: A multinational registry analysis. Lancet. May 22, 2020 (early release online).

2. The Lancet Editors: Expression of concern: Hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19: A multinational registry analysis. Lancet 395:e102, 2020.

3. Liang W, Guan W, Chen R, et al: Cancer patients in SARS-CoV-2 infection: A nationwide analysis in China. Lancet Oncol 21:335-337, 2020.

4. Yu J, Ouyang W, Chua MLK, et al: SARS-CoV-2 transmission in patients with cancer at a tertiary care hospital in Wuhan, China. JAMA Oncol. March 25, 2020 (early release online).

5. Kuderer NM, Choueiri TK, Shah DP, et al: Clinical impact of COVID-19 on patients with cancer (CCC19): A cohort study. Lancet 395:1907-1918, 2020.

6. Lee LYW, Cazier JB, Starkey T, et al: COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: A prospective cohort study. Lancet 395:1919-1926, 2020.

7. Garassino MC, Whisenant JG, Huang LC, et al: COVID-19 in patients with thoracic malignancies (TERAVOLT): First results of an international, registry-based, cohort study. Lancet Oncol 21:914-922, 2020.

8. Guan WJ, Liang WH, Zhao Y, et al: Comorbidity and its impact on 1590 patients with COVID-19 in China: A nationwide analysis. Eur Respir J 55:2000547, 2020.

Dr. Scagliotti is currently employed at the University of Turin, Orbassano, Italy.