Introduction

In China, SARS-CoV-2 was first discovered and subsequently disseminated across the globe. The World Health Organization (WHO) has precisely defined the disease caused by SARS-CoV-2 as Coronavirus Disease 2019 (COVID-19). Symptomatic patients with COVID-19 usually present with dyspnea and fever, and in patients with pneumonia, multilobed lesions can be observed in thorax computed tomography. It was acknowledged a pandemic by WHO on 11 March 2020 [1,2,3,4].

In adults with COVID-19, advanced age and chronic conditions, for instance, hypertension, diabetes, or heart disorders, are vulnerabilities for the severe disease [5]. Moreover, in a previous study, 39% of cancer patients with COVID-19 experienced serious events, such as admission to the intensive care unit (ICU), mechanical ventilation (MV) support, and death; on the other hand, only 8% of cancer-free patients with COVID-19 had such serious conditions [6]. In another study, researchers reported a case fatality rate (CFR) of 5.6% in cancer patients with COVID-19, whereas, in the same study, they reported a CFR of 2.3% in cancer-free patients with COVID-19 [7]. The high risk of cancer patients for more severe course of COVID-19 can be related to immunosuppression due to chemotherapy, radiotherapy, or worsened co-existing medical problems or metastases. Because of the underlying immune system deficiency, patients with hematologic cancers (HC) may be more vulnerable to COVID-19 [6]. Some concerns desperately require answers, such as whether COVID-19 in patients with solid cancers (SC) and HC has a worse outcome than cancer-free patients and whether cancer patients can undergo anticancer therapies as regular in outbreak regions. Nevertheless, only a small number of COVID-19 reports in SC and HC patients have been proposed in the literature. Thus, we aim to reveal the outcome of COVID-19 in HC patients and compare it with COVID-19 patients with SC. The primary outcome of the study was case fatality rate; secondary outcomes were COVID-19 clinical severity, the rates of hospital admission, intensive care unit admission, and mechanical ventilation.

Materials and methods

Patients

Laboratory-confirmed SARS-CoV-2-infected patients identified in the Republic of Turkey, Ministry of Health records, between 11 March 2020 and 22 June 2020 were examined retrospectively. This is a retrospective observational study, including patients aged 18 and over with HC. A cohort of age, gender, and co-existing diseases (diabetes mellitus, hypertension, cardiovascular diseases) matched COVID-19 patients with invasive SC (excluding basal cell carcinoma of the skin) at 1:1 proportion was allocated for assessment.

Laboratory analysis

Nasopharyngeal swabs were utilized to operate a real-time reverse transcriptase-polymerase chain reaction (RT-PCR) test for SARS-CoV-2 RNA. Utilizing coyote and biospeedy extraction processes (Coyote Bioscience Ltd and Bioeksen Ltd.), complete nucleic acid extraction of nasopharyngeal swab samples of virus isolates was undertaken.

Clinical parameters

Demographic information, concomitant diseases, medications used to treat COVID-19, hospital admission, hospital stay, ICU admission, length of ICU stay, the assistance of MV, and the patients' survival status were recorded.

The presence of dyspnea, blood oxygen saturation below 93%, PaO2/FiO2 < 300, and deterioration of lung infiltrations more than 50% in 24–48 h were defined as severe COVID-19. Deterioration of clinical condition to respiratory distress, septic shock, and/or multiple organ failure were defined as critical COVID-19 [8]. COVID-19 severity regarding the criteria stated above was recorded.

Statistical analysis and power analysis

The data processing was carried out by the IBM SPSS v26 program. Age, gender, and co-existing disease paired cohorts were allocated for assessment. Categorical variables were reported as number-percentages, and quantitative variables were reported as median (minimum–maximum). The variables were examined with the Kolmogorov–Smirnov test for normal distribution. Distinctions among the categorical variables were explored with the χ2 test, and the quantitative variables were assessed with the Mann–Whitney U test. A two-sided p value of ≤ 0.05 was assumed significantly important.

The power analysis for sample size estimation was conducted using G*Power version 3.1.9.7 to test the difference between two independent groups using a two-tailed test based on the pilot study conducted by Mehta et al. (N = 218) [9, 10]. The result indicated that a total sample of 464 participants with two equal-sized groups of n = 232 was necessary to achieve a power of 0.80 with an alpha of 0.05.

Results

Patients

Laboratory-confirmed 926 patients with COVID-19 were included; 463 had HC and the remaining 463 consisted of age, gender, and co-existing diseases matched cohort of patients with SC. Hypertension was observed in 40.6% of the patients with HC and 39.5% of the patients with SC and was the most prevalent co-existing disease in both groups. The frequency of diabetes mellitus, hypertension, and cardiovascular diseases was similar across the groups. The rates of favipiravir and high-dose vitamin C use were higher in HC patients (p = 0.001, p = 0.02, respectively). The clinical and demographic features of all cases are shown in Table 1. The frequencies of the diseases are shown in Table 2.

Table 1 Clinical and demographic features of the cases
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Table 2 Diagnosis of the patients
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Outcome

The frequency of severe and critical disease, hospital and ICU referral, MV support were significantly higher in HC patients compared with the SC patients (p = 0.001, p = 0.045, p = 0.001, and p = 0.001, respectively). Duration in the hospital was longer in patients with HC (p = 0.001); however, median duration of ICU stay was 6 days in both groups. The CFR was 14.9% in patients with HC, and it was 4.8% in patients with SC, and there was a significant difference regarding CFR among groups (p = 0.001) (Table 3).

Table 3 The outcome of COVID-19 in each group
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Discussion

This is one of the most extensive studies examining HC patients with COVID-19 and comparing their outcomes with SC patients with COVID-19. In our study, we revealed that frequency of severe and critical disease, hospital and ICU referral, and MV assistance were significantly higher in HC patients compared with SC patients; hospital stay was longer in patients with HC; ICU stay was similar in both groups, and CFR was higher in HC patients compared with the SC patients.

In a previous report, 53.6% of the patients with cancer had dramatic outcomes, 21.4% were referred to ICU, 35.7% had serious conditions, and 28.6% of the patients died [11]. In the community with COVID-19, 4.7% of cases were reported as critical, and almost half of the critical patients (2.3%) died [7]. In our study, the frequencies of severe and critical disease in SC patients were 12.3% and 8.2%, respectively. The frequency of ICU admission was 9.5%, and the frequency of MV assistance was 6.7% among patients with SC. The CFR was 4.8% in COVID-19 patients with SC.

There are still limited data regarding COVID-19 patients with HC in the literature so far. In a prior report, investigators presented data from 105 hospitalized COVID-19 patients with cancer and compared their findings with those without cancer. Of the 105 COVID-19 patients with cancer, 9 had HC. They reported that patients with cancer had higher mortality rate, higher rate of ICU admission, and MV assistance, and higher rate of severe COVID-19 when compared with cancer-free patients. Moreover, they identified the highest frequency of worse incidents in patients with HC, lung cancer, and metastatic cancer [12]. In the study conducted by Mehta et al., ICU referral and MV assistance was observed to be higher in HC patients (26%) compared with SC patients (19%) though statistical significance was not reached. In the same report, CFR was 37% in COVID-19 patients with HC [9].

In another research, He et al. reported the result of 128 hospitalized HC patients with COVID-19 and 16 medical professionals with COVID-19, 11 of whom were admitted to the hospital. They observed that patients with HC had a more severe condition and higher CFR than admitted medical professionals [13]. Another study from Spain examined 34 hospitalized COVID-19 patients with HC and stated that the CFR was 32%. They indicated that the HC remission status during COVID-19 was associated with death; patients without active cancer had better outcome [14]. A previous report including 35 hemato-oncology patients has documented a CFR of 40% [15]. In our analysis, the frequencies of severe and critical COVID-19 in HC patients were 16% and 18.6%, respectively. The rate of ICU admission was 20.7%, and the rate of MV assistance was 14.9% among patients with HC. The CFR was 14.9% in COVID-19 patients with HC.

This study has some limitations. The data about the disease status (active cancer/remission) and anticancer treatments are not available. On the other hand, the report's positive aspect is that groups were matched on various factors.

Cancer patients need prompt diagnosis, assessment, and care, including during an outbreak. Nevertheless, it is essential to address that cancer patients are immunodeficient and at an elevated risk of adverse events (ICU admission, MV need, or mortality) linked to COVID-19 relative to the general population [6, 16]. Studies suggest that cancer patients are highly susceptible to a more severe course of COVID-19 than cancer-free patients. Our research revealed that HC patients with COVID-19 have a more aggressive course of COVID-19 and higher CFR relative to SC patients with COVID-19 and endorsed the high risk of HC patients in the outbreak. The high susceptibility of patients with HC may be attributed to immune function dysfunction and hypogammaglobulinemia that are found in most patients. Due to the high infectivity of SARS-CoV-2, HC patients without COVID-19 should receive health care outside of the COVID-19 pandemic hospitals. Hematology departments should be isolated, and patient follow-up should be maintained as much as feasible by alternative methods, such as teleconference services.