key: cord-0972755-4y18oqyh
authors: Ruiz-Garcia, Erika; Peña-Nieves, Adriana; Alegria-Baños, Jorge; Cornejo-Juarez, Patricia; Meneses-García, Abelardo; Rivera, Samuel Rivera; Sánchez, Juan José; Gerson-Cwilich, Raquel; Gerson, Daniela Shveid; Franco, Heriberto Medina; Buerba, Gabriela Alejandra; Espinoza, Alicia Acosta; Mijares, Norma Valencia; Fernández-Figueroa, Edith A.; Vázquez, Roberto A.; Vilar-Compte, Diana
title: Prognostic factors in cancer patients infected with SARS-CoV-2: a Latin American country results
date: 2021-09-26
journal: Ther Adv Chronic Dis
DOI: 10.1177/20406223211047755
sha: b9549acbc099949937ea8de7925643d726518dcf
doc_id: 972755
cord_uid: 4y18oqyh

PURPOSE: The aim of this study was to evaluate the demographic characteristics, clinical and pathological factors, and the outcome of cancer and COVID-19 patients in Mexico. PATIENTS AND METHODS: A prospective, multicentric study was performed through a digital platform to have a national registry of patients with cancer and positive SARS-CoV-2 test results through reverse transcription quantitative polymerase chain reaction (RT-qPCR). We performed the analysis through a multivariate logistic regression model and Cox proportional hazard model. RESULTS: From May to December 2020, 599 patients were registered with an average age of 56 years with 59.3% female; 27.2% had hypertension. The most frequent diagnoses were breast cancer (30.4%), lymphoma (14.7%), and colorectal cancer (14.0%); 72.1% of patients had active cancer and 23.5% of patients (141/599) were deceased, the majority of which were men (51.7%). This study found that the prognostic factors that reduced the odds of death were gender (OR = 0.42, p = 0.031) and oxygen saturation (OR = 0.90, p = 0.0001); meanwhile, poor ECOG (OR = 5.4, p = 0.0001), active disease (OR = 3.9, p = 0.041), dyspnea (OR = 2.5, p = 0.027), and nausea (OR = 4.0, p = 0.028) increased the odds of death. In the meantime, the factors that reduce survival time were age (HR = 1.36, p = 0.035), COPD (HR = 8.30, p = 0.004), having palliative treatment (HR = 10.70, p = 0.002), and active cancer without treatment (HR = 8.68, p = 0.008). CONCLUSION: Mortality in cancer patients with COVID-19 is determined by prognostic factors whose identification is necessary. In our cancer population, we have observed that being female, younger, non-COPD, with non-active cancer, good performance status, and high oxygen levels reduce the probability of death.

The severity of the coronavirus disease 2019 caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to a pandemic crisis, with dramatic loss of human life worldwide. According to a survey from the World Health Organization, 90% of countries report one or more disruptions to essential health services. 1 Until 11 June 2021, there have been about 175 million cases with 3,775,180 deaths. 2 During the same period, Mexico had 2,413,742 cases and 223,568 deaths. 3 In general population, elderly males, presence of diabetes, and obesity have been identified as biological vulnerabilities for more severe COVID-19 outcomes. 4 On the contrary, cancer is among the top causes of death. 5 Higher mortality of COVID-19 seems to be related to cancer, but until today, there is no consistency on data. 6 Reports about racial/ethnic disparities found that Latinos at the United States bear a disproportionate burden of COVID-19-related outcomes. One possible explanation is that they underline many comorbidities. 7, 8 Available data of prognostic factors in Latin American cancer patients with COVID-19 are currently limited. A recent report from the COVID- 19 and Cancer Consortium (CCC- 19) , which included 4966 patients (where only 15% were Hispanic), showed that besides age, male gender, obesity, and comorbidities, being Hispanic, having a worse performance status, a hematological malignancy, and recent chemotherapy are associated with more severe COVID- 19. 9 Mexico is an upper-middle-income country where cancer has remained the third leading cause of death. 10 On one hand, 10 .4% of the population had diabetes and 25.5% had hypertension; on the other hand, 65% of the population has overweight and 30% has obesity. 11, 12 The aim of this study was to evaluate the specific demographic characteristics and clinical factors associated with survival and death of cancer patients with SARS-CoV-2 from the north, center, and south of Mexico.

Between March and April 2020, oncologists from public and private institutions serving cancer patients of all 32 states of Mexico and serving patients infected with COVID-19 were invited to the study. After their confirmation, two meetings were held to establish the relevant variables for the current study from the clinical and epidemiologic point of view and its definition. A digital platform was created (https://www.oncovid-19. org) with restricted access to enter the information of the participating centers across the country. Three pilot tests were performed and reviewed by experts to streamline the registry process. This was a prospectively planned study, but the data collection could be retrospective, after the infection by SARS-CoV-2.

The inclusion criteria were subjects ⩾18 years old, any sex, with confirmed cancer diagnosis, and positive SARS-CoV-2 test results through reverse transcription quantitative polymerase chain reaction (RT-qPCR). We excluded patients with cancer whose diagnoses were 10 or more years ago without any recurrence. The obtained information spans from May to December 2020. Once the information of all institutions was received, the database was validated up to the cutoff date. Given the sensible nature of the journals.sagepub.com/home/taj 3 study, personal identification data of individual patients were not included. This protocol was approved by the Review Board of the Instituto Nacional de Cancerología (Rev/0016/20). Informed consent was waived.

The following definitions were considered for this analysis: the functionality was measured through Eastern Cooperative Oncology Group (ECOG), which was clustered in two categories: low functionality (ECOG 2, 3, and 4) and high functionality (ECOG 0 and 1). The type of malignancy was divided in two categories: solid tumors and hematologic. Then, the clinical stage was defined as non-metastatic and metastatic. For hematologic malignancies that are not anatomically staged, like leukemias, they were considered disseminated at diagnosis, with some exceptions. The cancer status was categorized as in remission or without evidence and active disease. The 'treatment' variable clustered all patients who receive systemic (neoadjuvant, adjuvant, palliative, or maintenance) or radical (surgery or radiotherapy) management. Also, the 'non-treatment' variable included cases that were on vigilance or recently diagnosed, therefore, without an allocated treatment. Regarding comorbidities, chronic kidney disease was defined as the presence of kidney damage or an estimated glomerular filtration rate less than 60 ml/min/per 1.73 m 2 , persisting for 3 months or more; 13 meanwhile, chronic obstructive pulmonary disease (COPD) includes emphysema and chronic bronchitis. Finally, both COVID-19 comorbidities and related symptoms were defined as present or absent. The follow-up time was calculated as the difference between initial COVID-19 symptom date and the patient outcome date (death or last visit, accordingly).

The data were represented as absolute and relative frequency tables for the categorical variables, and as medians and interquartile range (IQR) for the quantitative variables. For the analysis, patients were divided according to their outcome (death or alive On the overall population, the most frequent COVID-19 symptoms were cough (58%) and fever (56.8%), whereas dyspnea was shown in 45.8% (see Figure 1 ). When considering deceased patients, the cough and fever reached 77.1% and 76.3%, respectively.

The oncologic patient sample included in this study had a median follow-up of 22 days (10-47 days). We observed that 23.5% of patients died (141/599). Men died more frequently (30.9% versus 19.6%, p = 0.002) and the eldest (54 versus 62.5 years, p = 0.0001). Our analysis highlights a high frequency of diabetes and kidney failure on deceased patients (p = 0.01 and p = 0.001, respectively). Meanwhile, BMI was not relevant on the statistic evaluation (p = 0.095). A greater death frequency was shown on the group with low ECOG functionality (51.6%, p = 0.0001).

Death frequency was reduced on the patient group without oncologic treatment (13.4% versus 28.3%). A similar situation was observed with the survivor group (p = 0.0001). In addition, patients with hematologic tumors were deceased more frequently than those with solid tumors (33.3% versus 22.4%, p = 0.020). Lymphoma was the most frequent diagnosis among the hematologic group, and breast cancer was the most frequent solid tumor, with significant death frequency differences among the oncologic diagnosis (p = 0.0001, 33.9% versus 12.7%).

Patients receiving treatment were grouped as follows: chemotherapy (39.1%), hormone therapy (9.9%), and targeted therapy and immunotherapy (7.41% and 3.0%, respectively). Meanwhile, 7.2% had gone through surgery and 4.2% under radiotherapy. The remaining 29.2% had no treatment description.

Treatment of COVID-19 was as follows: antibiotics (57.2%, n = 343), oseltamivir (8.0%, n = 48), remdesivir (0.3%, n = 2), lopinavir/ritonavir (1.5%, n = 9), atazanavir/ritonavir (0.25%, The pink color shows the main role of cough and fever, followed by dyspnea, headache, and myalgia. with all federative entities to collect information of cancer patients infected with SARS-CoV-2 confirmed by RT-qPCR. This work had no financing and is the effort of physicians worried by the vulnerability of their patients; regardless of the increased workload generated by this emergency, they voluntarily gathered the information that is analyzed in this work. ORs that correspond with p values <0.05 were marked with pink, whereas those with p ⩾ 0.05 were colored blue and the 95% confidence interval ranges were colored navy for both groups.

journals.sagepub.com/home/taj 11 Previous reports describe that comparing patients with cancer to non-cancer patients, apart from being more susceptible to SARS-CoV-2 infections, cancer patients are at an increased risk of more severe sequelae. [16] [17] [18] This study analyzes the prognostic factors related to Latin American patients, specifically Mexican patients, with cancer and with a SARS-CoV-2 infection during 2020.

The greatest number of registered cases of this study corresponds to the Metropolitan Area of Mexico City. This is due to the concentration of cancer attention sites along with its population density (around 20 million inhabitants) and, although this first report observes a low percentage of patients from other states (12.7%), it helps to reflect the situation of the infection country-wise.

The study population showed a female predominance (60%) with an age average of 56 years. This is contrary to other published series [19] [20] [21] where the average age was 66 years without gender majority. This situation may probably be due to the fact that 30.4% of cases had been diagnosed with breast cancer, which is developed earlier in Latin American women when compared with other populations. 22 Although it is a 'younger' group, it was found that one out of every three patients had HBP and one out of every five had diabetes mellitus. Overweight, which is present in 50% of patients, and obesity, observed in one out of every four, were discarded from the univariate analysis as a relevant factor for death. This coincides with the study of Al-Salameh et al., 23 However, our death frequency is very similar to the UK cohort (n = 800), which was reported as 28%. 21 When adjusted for other variables, the logistic regression showed that being male (p = 0.031) increased the odds of death, which coincides with previously published studies, both in the general and in the oncologic populations. 9,24 A CCC-19 study reported that having active cancer and ECOG 2, 3, or 4 was associated to a negative prognosis in cancer patients infected with SARS-CoV-2. 20 In this study, we observed an increase of between 3 and 5 for the odds of death in patients with active cancer and a poor ECOG score. Although a third of the population had an ECOG ⩾ 2, it was observed that this parameter has great influence when determining a patient's death. We also observed that the fatality rate was not associated to advanced stage as other reports; we believe that is because 30.4% of our cohort had breast cancer. Some reports have shown that women with breast cancer have fewer severe forms of COVID-19 and less likely to die. 25, 26 Regarding the oncologic treatment, when performing the step-by-step regression, it was detected that receiving treatment increased the odds of death. However, this effect was diluted upon inclusion on the multivariate analysis and variable adjustment. Our results were like some previous reports where the oncological treatments such as chemotherapy did not increase adverse outcomes. 27 The same behavior was noted with hematologic versus solid tumors: univariate analysis detected that the frequency of death in hematologic tumors was higher (p = 0.020). However, after the multivariate analysis, the difference did not withhold its significance and the odds of death were not increased unlike other studies 9, 19, 21, 25 maybe as a consequence of the high rate of hematological patients on surveillance (34.3%). On the contrary, subjective symptoms such as vomiting, nausea, and abdominal pain could be attributed not only to the oncological treatment and the cancer itself but also to COVID-19, and despite we are unable to identify the cause, we found that nausea increased the odds of death. 25 Cancer is a heterogeneous disease, where besides the treatment type, primary tumor subtype, stage, age, and gender also play a role. 30 Another limitation is that the presented results on cancer patients with COVID-19 in Mexico cannot be generalized to the whole Mexican population due to most of the data coming from the National Cancer Institute, which is one of the largest oncology centers of the country. Furthermore, the collected information from hospitals and the patient outcomes has been partial given their organization: they remitted patients to COVID-19-exclusive hospitals, which limited the information analysis.

In this study, we observed that there is a high frequency of death on cancer patients infected with SARS-CoV-2. However, though we adjusted our models, we cannot ensure that this is only due to cancer-related or host-related factors. There is a need to analyze the role of the viral infection per se. Also, this report did not analyze the impact of cancer treatments (meaning, if the dose intensity was maintained or if the treatment was delayed given the fear of patient infection) regarding cancer and COVID-19.

To the best of our knowledge, this is the largest series of Latin American cancer patients with COVID-19 infection reported thus far. We would like to stress the relevance of the study being multicentric. This allows us to observe that 7 out of every 10 patients had active cancer, in which case one out of every four died.

Even in Mexico, which is labeled as a mediumhigh income country, it is not always possible to follow international guidelines 31 to reduce the effects of COVID-19 in cancer patients. The health infrastructure does not allow telemedicine across all levels (with the goal of reducing hospital visits) or intravenous-to-oral therapy change. Another important aspect is that social distancing is not always feasible on cities with high population density. Thus, we must prioritize oncology care through better strategies with the goal of refining institutional protocols based on our own information.

This study shows the prognosis factors related to death in Mexican cancer patients with SARS-CoV-2 infection. In our population, we found characteristics reported previously as gender and age, performance status, active cancer, and oxygen saturation; nevertheless, we did not find that other comorbidities besides COPD increase the probability of death. Meanwhile, we understand how COVID-19 affects our cancer patients; we must be aware of the importance of improving health policies in patients with oncology diseases.

COVID-19 continues to disrupt essential health services in 90% of countries

22° Informe epidemiológico de la situación de COVID-19

Hospitalization rates and characteristics of patients hospitalized with laboratory-confirmed coronavirus disease 2019 -COVID-NET

Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

Commentary: SARS-CoV-2 vaccines and cancer patients

COVID-19 and racial/ethnic disparities

Incremental risk of developing severe COVID-19 among Mexican patients with diabetes attributed to social and health care access disadvantages

Association of clinical factors and recent anticancer therapy with COVID-19 severity among patients with cancer: a report from the COVID-19 and Cancer Consortium

Cancer trends in Mexico: essential data for the creation and follow-up of public policies

Hypertension in Mexican adults: prevalence, diagnosis and type of treatment. Ensanut MC 2016

Ending diabetes in Mexico

Chapter 1: definition and classification of CKD

StataCorp. Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC

SARS-CoV-2 transmission in patients with cancer at a tertiary care hospital in Wuhan, China

The HOLA COVID-19 study: an international effort to determine how COVID-19 has impacted oncology practices in Latin America

Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China

COVID-19 and cancer: lessons from a pooled metaanalysis

Patients with cancer appear more vulnerable to SARS-COV-2: a multi-center study during the COVID-19 outbreak

Clinical impact of COVID-19 on patients with cancer (CCC19): a cohort study

COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study

A review of breast cancer care and outcomes in Latin America

The association between body mass index class and coronavirus disease 2019 outcomes

Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area

Comparison and impact of COVID-19 for patients with cancer: a survival analysis of fatality rate controlling for age, sex and cancer type

Breast cancer management during the COVID-19 pandemic: The Senologic International Society Survey

Chemotherapy and COVID-19 outcomes in patients with cancer

The multidimensional challenge of treating coronavirus disease 2019 (COVID-19): remdesivir is a foot in the door

Mortality in hospitalized patients with cancer and journals.sagepub.com/home/taj 15 coronavirus disease 2019: a systematic review and meta-analysis of cohort studies

Cancer patients and risk of mortality for COVID-19

Cancer patient management during the COVID-19 pandemic

The authors thank all the institutions' and hospitals' staff. The authors also thank Universidad la Salle for the support in the creation of the digital platform (https://www.oncovid-19.org).

The authors received no financial support for the research, authorship, and/or publication of this article.

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Adriana Peña-Nieves https://orcid.org/0000-0003-0632-0585