INTRODUCTION

Cancer is the second leading cause of mortality in Latin America and The Caribbean (LAC), with over 700,000 deaths in 2020 ¹. Significant difficulties already posed to the region by this burden were further exacerbated by the COVID-19 pandemic contingency ². The entire spectrum of cancer care, from prevention to survivorship, has been affected by the COVID-19 pandemic, presenting a new challenge to providers regarding weighing the benefits of anti-cancer treatments and the risk of their administration amidst the pandemic. An early study showed that intravenous (IV) chemotherapy was associated with an increased risk of severe complications in cancer patients infected with SARS-CoV-2 ³. Chemotherapy and disease-induced immunosuppression, treatment-related pulmonary toxicity, the need for hospitalization with the associated risk of nosocomial infections alongside the saturation of the health system, social distancing, and economic issues have been suggested as factors potentially influencing the risk of severe complications and death of cancer patients on active anticancer treatment ^4-6. This was reflected in the recommendations from medical societies and experts suggesting the substitution of chemotherapy with endocrine drugs, the use of treatment protocols with a lower number of cycles, and replacing of IV drugs with oral analogs leading to modifications of the management practice with potential impact on oncological outcomes ^4,5,7,8. During the pandemic, there was also a concern regarding the safety of immunotherapy due to a significant incidence of immune-related pneumonitis requiring corticosteroids and immunosuppressors ^6,9.

Many studies in the field of COVID-19 and cancer have focused on outcomes of oncological patients with proven COVID-19 infection compared to those without cancer or COVID-19 infection. These studies usually used data from COVID-19 positive subjects ^10,11. However, this approach may be less appropriate for assessing the incremental risk of death associated with the COVID-19 pandemic in the general population of ambulatory cancer patients receiving an active IV treatment. On the other hand, the estimation of COVID-19 specific mortality as an indicator of the pandemic impact on oncological patients’ health may be challenging or unreliable due, for instance, to cause of death misclassification, variations in COVID-19 tests procedures and reporting, and the disease displacement phenomenon ¹². All-cause mortality is a measure that encompasses all death from any cause and allows to overcome the cited issues providing a metric of pandemic impact on overall mortality ¹².

Most research on COVID-19 and cancer is carried out in developed countries ¹². However, it is not clear to what extent the results of these studies can be applied to developing countries. In LAC, the pre-pandemic healthcare landscape was already rife with fragmented and underfunded healthcare systems, inequities in access to quality care, and reduced availability of COVID-19 tests and vaccines. Across the region, lockdowns and quarantines were widely implemented ¹³. We aimed to investigate whether all-cause mortality of ambulatory oncological patients receiving active IV cytotoxic drugs or Immune checkpoint inhibitors (ICI) increased during the pandemic compared to the pre-pandemic period.

MATERIALS AND METHODS

RESULTS

Cohorts and matching

Before PSM, the number of patients in the pandemic and pre-pandemic cohorts were 169 and 377, respectively (Figure 1). At baseline, the mean age was 59.2 years (standard deviation [SD ]: 13.7 years) in the pandemic cohort and 59.4 years (SD: 13.5 years) in the pre-pandemic cohort. The ratio of women was 62.7% and 68.7% in both cohorts, respectively. Chemotherapy was the most common treatment (92.6% in the pandemic cohort and 95.5% in pre-pandemic cohort), and a small proportion of patients had received ICI (7.2% and 4.5%, respectively). Neoadjuvant and first-line therapies were the most frequent with 78.7%, and 77.3%, respectively. The proportion of patients with two or more risk factors for severe complications of COVID-19 infection was 32.1% and 32.7%, respectively. The clinical, demographic, and treatment-related characteristics of the participants are summarized in Supplementary Material. The median follow-up time was 6.0 months in both cohorts. In the pandemic cohort, 4.8% had a nasal swab positive for COVID-19. One out of 169 patients from the pandemic cohort was lost from follow-up and did not have data on the main outcome. None out of 377 patients was lost from follow-up in the pre-pandemic cohort.

Figure1. Patients flow in the study. 

As a result of PSM, 168 subjects were matched. In the pre-pandemic cohort, 209 subjects were left out while only one subject was dropped from the pandemic cohort. Patients’ characteristics in pandemic and pre-pandemics cohorts after matching are shown in Table 2. No statistically significant difference was found between cohorts by covariates included in the model. The distribution of propensity scores in both matched cohorts and unmatched subjects is shown in Supplementary Material. The absolute SMD for each covariate is shown in Supplementary Material.

Mortality and admissions

After PSM, the all-cause mortality rate was 30/168 (17.9%, 95%CI: 12.4% - 24.5%) in the pandemic cohort and 31/168 (18.5%, 95%CI: 12.9% - 25.2%) in the pre-pandemic cohort (RR: 0.97, 95%CI: 0.61 - 1.52; p=0.888 and adjusted RR [aRR ]: 1.07, 95%CI: 0.63 - 1.79; p=0.810). The rate of serious complications in the pandemic cohort was 8/167 (4.8%, 95%CI: 2.1% - 9.2%). Of the 30 patients who died in the pandemic cohort, 29 died from cancer progression, 0 patients (0.0%, 95%CI: 0.0% - 1.2%) from SARS-CoV-2 virus infection, and one patient (3.3%, 95%CI: 0.0% - 1.7%) from another cause. No statistically significant association was found between vital status at the end of follow-up and COVID-19 positivity (Fisher’s exact test p-value equal to 1). In the pandemic cohort, 8/167 (4.8%, 95%CI: 2.1% - 9.2%) patients were admitted to an Intensive Care Unit (ICU), 7/167 (4.2%, 95%CI: 1.7% - 8.4%) to a High Dependency Unit, and 47/167 (28.1%, 95%CI: 21.5% - 35.6%) to an ordinary ward. No statistically significant relationship was found between admissions and COVID-19 test positivity (Fisher’s exact test p-value equal to 1).

Sensitivity Analysis

To assess whether our results were influenced by the inclusion of patients on immunological treatment, we performed a sensitivity analysis by eliminating them from the cohorts. After PSM, all-cause mortality was 17.9% (28/56) and 17.5% (27/154) in the pandemic and pre-pandemic cohorts, respectively; aRR: 1.07 (95% CI: 0.57- 1.99; p=0.329).

Missing data

BMI data had a moderate proportion (7.5%) of missing values. On the other hand, the rest of covariates had significantly fewer missing values (ranging from 0.0% to 0.5%).

DISCUSSION

Unlike most published studies that usually focus on the outcomes of patients with COVID-19 and cancer, we addressed the risk of IV cancer therapy in the pandemic context differently. We compared the mortality rate of oncological patients on active IV chemotherapy or immunotherapy regardless of their COVID-19 status to a matched cohort from the pandemic and pre-pandemic period. The study was conducted in a developing country before vaccine use ²³.

After adjusting for potential confounders (age, sex, health insurance, drug type, primary tumor group, line of treatment, number of drugs, risk factors, ECOG functional status and obesity), we found no statistically significant difference in the all-cause mortality rate of patients treated during the pandemic (17.9%) versus those treated before the pandemic (18.5%) (RR: 0.97; 95%CI: 0.61-1.52, p=0.888).

We found a mortality rate of 18% at 6-months of follow-up, which is higher than the 4% to 8% rate reported by a large cohort study from the United Kingdom (UK). This British study included patients on target drugs and oral chemotherapy who progressed favorably, which could be a possible explanation. However, differences in the quality of care cannot be ruled out ²⁴.

To date, many studies with differences in their design, size, population, follow-up time, definitions, diagnostic methods, and events of interest assessed mortality in cancer patients during the pandemic. Many were retrospective, comparing patients with COVID-19 and cancer, who were on anti-cancer therapy to those without any active treatment. Several systematic reviews attempted to summarize the available evidence. Meta-analyses by Wang et al., Yekeduz et al., Park et al., and Wu et al., included mostly retrospective studies from China, Europe, and Northern America with partial overlap ^25-27. These studies compared mortality in patients with COVID-19 with solid and hematological neoplasms on chemotherapy with the control arm, typically by combining patients who were receiving cancer treatment with those receiving non-cytotoxic treatment. All of them found increments in mortality in the chemotherapy arm. In contrast, Lin et al., concluded that chemotherapy and ICI did not increase mortality in patients with cancer and COVID-19 ^28,29.

A large study from the UK by Russel et al., which is similar to our study, used a cohort from a pre-pandemic period (2019) as a control group ³⁰. Besides patients on cytotoxic drugs and immunotherapy, the study included patients who received biological and targeted therapy. The cohorts were not balanced by PSM. The authors found that systemic chemotherapy during the first wave of the COVID-19 pandemic did not increase the mortality in patients with solid tumors compared to those during the pre-pandemic period. Low COVID-19 infection and mortality rates were reported by the research, which is similar to our findings ³⁰.

To reconcile the controversial conclusions of previously published analyses, we hypothesize that even though cytotoxic drugs still may increase mortality in the general population of cancer patients, it could be difficult to detect this effect in environments with low prevalence and transmission rates. The type of neoplasm, hematological or solid, can also be a factor. A large study would be necessary to test this hypothesis. Researchers should consider designing future studies with greater data granularity to better assess relevant subgroups.

In our study, the absence of excess mortality in the pandemic cohort, which is different with many previous publications, could provide potential explanations. For example, the overall impact of the COVID-19 pandemic in the general population of cancer patients may be less than in those with clinically overt infection or positive COVID-19 tests. Most published studies evaluated the latter populations. If SARS-CoV-2 virus infection in the general population of patients with solid tumors is predominantly asymptomatic, overall mortality will not increase unless the infection is highly lethal. In this sense, the low pandemic burden in Argentina during the study period might be a possible explanation. However, more than 2 million cases of SARS-CoV-2 virus infection were reported in Argentina during the mentioned period ³¹. The true cumulative number of cases may be even higher, considering that the capacity for analysis was limited even in high-income countries. ³².

The strengths of our study are the prospective enrollment in the pandemic cohort, the inclusion of multiple centers widely distributed across the national territory, the inclusion of both private and public healthcare systems, and the cohort matching by propensity score. Our study has several limitations. The comparison of a prospectively enrolled cohort with a retrospective one is the main source of bias and the main limitation of our study. The utilization of PSM is a way in which we sought to reduce bias. Another important limitation is the small sample size. The study was designed to detect only large increments in mortality as the assumptions made during the design process at the very beginning of the pandemic were influenced by the information of a potentially very significant impact of COVID-19 on oncological patients’ health ^3,5. The proportion of subjects tested for COVID-19 was low. Which is probably due to the significantly reduced test availability in Argentina during the first phase of the pandemic alongside a low rate of symptomatic COVID-19 infection in our study. We hypothesize that the latter could be a result of reduced viral spread in the study population because of massive and strict lockdowns, although their adherence gradually diminished over time due to fatigue ¹³. The short follow-up period is another limitation of our work. The follow-up was discontinued once vaccination started in Argentina. Our findings may not be representative of the entire population of cancer patients or applicable to different geographic regions or time periods.

According to a review conducted by the authors of this paper, this is the first propensity score-matched cohort study evaluating the impact of the COVID-19 pandemic on unvaccinated oncology patients receiving IV anticancer therapy compared to those during a non-pandemic period. Despite the discussed limitations, our study provides some empirical support for the idea that IV chemotherapy and immunotherapy could be safely administered during the pandemic prior to the use of COVID-19 vaccine in a middle-income country and contributes to the debate on the interaction between the COVID-19 pandemic and oncology care. Our results suggest that, even in the midst of a pandemic, it remains crucial to prioritize and ensure adequate access to non-COVID-19 health care, such as cancer treatment and management. These results should be interpreted in the context of individual risk factors and prioritize vaccination as a preventive measure to protect vulnerable populations. Public health strategies should continue to promote vaccination against COVID-19 along with maintaining access to essential non-COVID-19 health services. Our results may aid in chemotherapy decision making in the event of an outbreak of vaccine-resistant variant COVID-19.