The challenge of COVID-19 and hematopoietic cell transplantation; EBMT recommendations for management of hematopoietic cell transplant recipients, their donors, and patients undergoing CAR T-cell therapy
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Abstract
The new coronavirus SARS-CoV-2 has rapidly spread over the world causing the disease
by WHO called COVID-19. This pandemic poses unprecedented stress on the health care
system including programs performing allogeneic and autologous hematopoietic cell
transplantation (HCT) and cellular therapy such as with CAR T cells. Risk factors
for severe disease include age and predisposing conditions such as cancer. The true
impact on stem cell transplant and CAR T-cell recipients in unknown. The European
Society for Blood and Marrow Transplantation (EBMT) has therefore developed recommendations
for transplant programs and physicians caring for these patients. These guidelines
were developed by experts from the Infectious Diseases Working Party and have been
endorsed by EBMT’s scientific council and board. This work intends to provide guidelines
for transplant centers, management of transplant candidates and recipients, and donor
issues until the COVID-19 pandemic has passed.
Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
Dear Editor, In December 2019, a novel pneumonia caused by a previously unknown pathogen emerged in Wuhan, a city of 11 million people in central China. The initial cases were linked to exposures in a seafood market in Wuhan. 1 As of January 27, 2020, the Chinese authorities reported 2835 confirmed cases in mainland China, including 81 deaths. Additionally, 19 confirmed cases were identified in Hong Kong, Macao and Taiwan, and 39 imported cases were identified in Thailand, Japan, South Korea, United States, Vietnam, Singapore, Nepal, France, Australia and Canada. The pathogen was soon identified as a novel coronavirus (2019-nCoV), which is closely related to sever acute respiratory syndrome CoV (SARS-CoV). 2 Currently, there is no specific treatment against the new virus. Therefore, identifying effective antiviral agents to combat the disease is urgently needed. An efficient approach to drug discovery is to test whether the existing antiviral drugs are effective in treating related viral infections. The 2019-nCoV belongs to Betacoronavirus which also contains SARS-CoV and Middle East respiratory syndrome CoV (MERS-CoV). Several drugs, such as ribavirin, interferon, lopinavir-ritonavir, corticosteroids, have been used in patients with SARS or MERS, although the efficacy of some drugs remains controversial. 3 In this study, we evaluated the antiviral efficiency of five FAD-approved drugs including ribavirin, penciclovir, nitazoxanide, nafamostat, chloroquine and two well-known broad-spectrum antiviral drugs remdesivir (GS-5734) and favipiravir (T-705) against a clinical isolate of 2019-nCoV in vitro. Standard assays were carried out to measure the effects of these compounds on the cytotoxicity, virus yield and infection rates of 2019-nCoVs. Firstly, the cytotoxicity of the candidate compounds in Vero E6 cells (ATCC-1586) was determined by the CCK8 assay. Then, Vero E6 cells were infected with nCoV-2019BetaCoV/Wuhan/WIV04/2019 2 at a multiplicity of infection (MOI) of 0.05 in the presence of varying concentrations of the test drugs. DMSO was used in the controls. Efficacies were evaluated by quantification of viral copy numbers in the cell supernatant via quantitative real-time RT-PCR (qRT-PCR) and confirmed with visualization of virus nucleoprotein (NP) expression through immunofluorescence microscopy at 48 h post infection (p.i.) (cytopathic effect was not obvious at this time point of infection). Among the seven tested drugs, high concentrations of three nucleoside analogs including ribavirin (half-maximal effective concentration (EC50) = 109.50 μM, half-cytotoxic concentration (CC50) > 400 μM, selectivity index (SI) > 3.65), penciclovir (EC50 = 95.96 μM, CC50 > 400 μM, SI > 4.17) and favipiravir (EC50 = 61.88 μM, CC50 > 400 μM, SI > 6.46) were required to reduce the viral infection (Fig. 1a and Supplementary information, Fig. S1). However, favipiravir has been shown to be 100% effective in protecting mice against Ebola virus challenge, although its EC50 value in Vero E6 cells was as high as 67 μM, 4 suggesting further in vivo studies are recommended to evaluate this antiviral nucleoside. Nafamostat, a potent inhibitor of MERS-CoV, which prevents membrane fusion, was inhibitive against the 2019-nCoV infection (EC50 = 22.50 μM, CC50 > 100 μM, SI > 4.44). Nitazoxanide, a commercial antiprotozoal agent with an antiviral potential against a broad range of viruses including human and animal coronaviruses, inhibited the 2019-nCoV at a low-micromolar concentration (EC50 = 2.12 μM; CC50 > 35.53 μM; SI > 16.76). Further in vivo evaluation of this drug against 2019-nCoV infection is recommended. Notably, two compounds remdesivir (EC50 = 0.77 μM; CC50 > 100 μM; SI > 129.87) and chloroquine (EC50 = 1.13 μM; CC50 > 100 μM, SI > 88.50) potently blocked virus infection at low-micromolar concentration and showed high SI (Fig. 1a, b). Fig. 1 The antiviral activities of the test drugs against 2019-nCoV in vitro. a Vero E6 cells were infected with 2019-nCoV at an MOI of 0.05 in the treatment of different doses of the indicated antivirals for 48 h. The viral yield in the cell supernatant was then quantified by qRT-PCR. Cytotoxicity of these drugs to Vero E6 cells was measured by CCK-8 assays. The left and right Y-axis of the graphs represent mean % inhibition of virus yield and cytotoxicity of the drugs, respectively. The experiments were done in triplicates. b Immunofluorescence microscopy of virus infection upon treatment of remdesivir and chloroquine. Virus infection and drug treatment were performed as mentioned above. At 48 h p.i., the infected cells were fixed, and then probed with rabbit sera against the NP of a bat SARS-related CoV 2 as the primary antibody and Alexa 488-labeled goat anti-rabbit IgG (1:500; Abcam) as the secondary antibody, respectively. The nuclei were stained with Hoechst dye. Bars, 100 μm. c and d Time-of-addition experiment of remdesivir and chloroquine. For “Full-time” treatment, Vero E6 cells were pre-treated with the drugs for 1 h, and virus was then added to allow attachment for 2 h. Afterwards, the virus–drug mixture was removed, and the cells were cultured with drug-containing medium until the end of the experiment. For “Entry” treatment, the drugs were added to the cells for 1 h before viral attachment, and at 2 h p.i., the virus–drug mixture was replaced with fresh culture medium and maintained till the end of the experiment. For “Post-entry” experiment, drugs were added at 2 h p.i., and maintained until the end of the experiment. For all the experimental groups, cells were infected with 2019-nCoV at an MOI of 0.05, and virus yield in the infected cell supernatants was quantified by qRT-PCR c and NP expression in infected cells was analyzed by Western blot d at 14 h p.i. Remdesivir has been recently recognized as a promising antiviral drug against a wide array of RNA viruses (including SARS/MERS-CoV 5 ) infection in cultured cells, mice and nonhuman primate (NHP) models. It is currently under clinical development for the treatment of Ebola virus infection. 6 Remdesivir is an adenosine analogue, which incorporates into nascent viral RNA chains and results in pre-mature termination. 7 Our time-of-addition assay showed remdesivir functioned at a stage post virus entry (Fig. 1c, d), which is in agreement with its putative anti-viral mechanism as a nucleotide analogue. Warren et al. showed that in NHP model, intravenous administration of 10 mg/kg dose of remdesivir resulted in concomitant persistent levels of its active form in the blood (10 μM) and conferred 100% protection against Ebola virus infection. 7 Our data showed that EC90 value of remdesivir against 2019-nCoV in Vero E6 cells was 1.76 μM, suggesting its working concentration is likely to be achieved in NHP. Our preliminary data (Supplementary information, Fig. S2) showed that remdesivir also inhibited virus infection efficiently in a human cell line (human liver cancer Huh-7 cells), which is sensitive to 2019-nCoV. 2 Chloroquine, a widely-used anti-malarial and autoimmune disease drug, has recently been reported as a potential broad-spectrum antiviral drug. 8,9 Chloroquine is known to block virus infection by increasing endosomal pH required for virus/cell fusion, as well as interfering with the glycosylation of cellular receptors of SARS-CoV. 10 Our time-of-addition assay demonstrated that chloroquine functioned at both entry, and at post-entry stages of the 2019-nCoV infection in Vero E6 cells (Fig. 1c, d). Besides its antiviral activity, chloroquine has an immune-modulating activity, which may synergistically enhance its antiviral effect in vivo. Chloroquine is widely distributed in the whole body, including lung, after oral administration. The EC90 value of chloroquine against the 2019-nCoV in Vero E6 cells was 6.90 μM, which can be clinically achievable as demonstrated in the plasma of rheumatoid arthritis patients who received 500 mg administration. 11 Chloroquine is a cheap and a safe drug that has been used for more than 70 years and, therefore, it is potentially clinically applicable against the 2019-nCoV. Our findings reveal that remdesivir and chloroquine are highly effective in the control of 2019-nCoV infection in vitro. Since these compounds have been used in human patients with a safety track record and shown to be effective against various ailments, we suggest that they should be assessed in human patients suffering from the novel coronavirus disease. Supplementary information Supplementary information, Materials and Figures
China and the rest of the world are experiencing an outbreak of a novel betacoronavirus known as severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). 1 By Feb 12, 2020, the rapid spread of the virus had caused 42 747 cases and 1017 deaths in China and cases have been reported in 25 countries, including the USA, Japan, and Spain. WHO has declared 2019 novel coronavirus disease (COVID-19), caused by SARS-CoV-2, a public health emergency of international concern. In contrast to severe acute respiratory system coronavirus and Middle East respiratory syndrome coronavirus, more deaths from COVID-19 have been caused by multiple organ dysfunction syndrome rather than respiratory failure, 2 which might be attributable to the widespread distribution of angiotensin converting enzyme 2—the functional receptor for SARS-CoV-2—in multiple organs.3, 4 Patients with cancer are more susceptible to infection than individuals without cancer because of their systemic immunosuppressive state caused by the malignancy and anticancer treatments, such as chemotherapy or surgery.5, 6, 7, 8 Therefore, these patients might be at increased risk of COVID-19 and have a poorer prognosis. On behalf of the National Clinical Research Center for Respiratory Disease, we worked together with the National Health Commission of the People's Republic of China to establish a prospective cohort to monitor COVID-19 cases throughout China. As of the data cutoff on Jan 31, 2020, we have collected and analysed 2007 cases from 575 hospitals (appendix pp 4–9 for a full list) in 31 provincial administrative regions. All cases were diagnosed with laboratory-confirmed COVID-19 acute respiratory disease and were admitted to hospital. We excluded 417 cases because of insufficient records of previous disease history. 18 (1%; 95% CI 0·61–1·65) of 1590 COVID-19 cases had a history of cancer, which seems to be higher than the incidence of cancer in the overall Chinese population (285·83 [0·29%] per 100 000 people, according to 2015 cancer epidemiology statistics 9 ). Detailed information about the 18 patients with cancer with COVID-19 is summarised in the appendix (p 1). Lung cancer was the most frequent type (five [28%] of 18 patients). Four (25%) of 16 patients (two of the 18 patients had unknown treatment status) with cancer with COVID-19 had received chemotherapy or surgery within the past month, and the other 12 (25%) patients were cancer survivors in routine follow-up after primary resection. Compared with patients without cancer, patients with cancer were older (mean age 63·1 years [SD 12·1] vs 48·7 years [16·2]), more likely to have a history of smoking (four [22%] of 18 patients vs 107 [7%] of 1572 patients), had more polypnea (eight [47%] of 17 patients vs 323 [23%] of 1377 patients; some data were missing on polypnea), and more severe baseline CT manifestation (17 [94%] of 18 patients vs 1113 [71%] of 1572 patients), but had no significant differences in sex, other baseline symptoms, other comorbidities, or baseline severity of x-ray (appendix p 2). Most importantly, patients with cancer were observed to have a higher risk of severe events (a composite endpoint defined as the percentage of patients being admitted to the intensive care unit requiring invasive ventilation, or death) compared with patients without cancer (seven [39%] of 18 patients vs 124 [8%] of 1572 patients; Fisher's exact p=0·0003). We observed similar results when the severe events were defined both by the above objective events and physician evaluation (nine [50%] of 18 patients vs 245 [16%] of 1572 patients; Fisher's exact p=0·0008). Moreover, patients who underwent chemotherapy or surgery in the past month had a numerically higher risk (three [75%] of four patients) of clinically severe events than did those not receiving chemotherapy or surgery (six [43%] of 14 patients; figure ). These odds were further confirmed by logistic regression (odds ratio [OR] 5·34, 95% CI 1·80–16·18; p=0·0026) after adjusting for other risk factors, including age, smoking history, and other comorbidities. Cancer history represented the highest risk for severe events (appendix p 3). Among patients with cancer, older age was the only risk factor for severe events (OR 1·43, 95% CI 0·97–2·12; p=0·072). Patients with lung cancer did not have a higher probability of severe events compared with patients with other cancer types (one [20%] of five patients with lung cancer vs eight [62%] of 13 patients with other types of cancer; p=0·294). Additionally, we used a Cox regression model to evaluate the time-dependent hazards of developing severe events, and found that patients with cancer deteriorated more rapidly than those without cancer (median time to severe events 13 days [IQR 6–15] vs 43 days [20–not reached]; p<0·0001; hazard ratio 3·56, 95% CI 1·65–7·69, after adjusting for age; figure). Figure Severe events in patients without cancer, cancer survivors, and patients with cancer (A) and risks of developing severe events for patients with cancer and patients without cancer (B) ICU=intensive care unit. In this study, we analysed the risk for severe COVID-19 in patients with cancer for the first time, to our knowledge; only by nationwide analysis can we follow up patients with rare but important comorbidities, such as cancer. We found that patients with cancer might have a higher risk of COVID-19 than individuals without cancer. Additionally, we showed that patients with cancer had poorer outcomes from COVID-19, providing a timely reminder to physicians that more intensive attention should be paid to patients with cancer, in case of rapid deterioration. Therefore, we propose three major strategies for patients with cancer in this COVID-19 crisis, and in future attacks of severe infectious diseases. First, an intentional postponing of adjuvant chemotherapy or elective surgery for stable cancer should be considered 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 SARS-CoV-2, especially in older patients or those with other comorbidities.
[1
]ISNI 0000 0000 9241 5705, GRID grid.24381.3c, Department of Cellular Therapy and Allogeneic Stem Cell Transplantation, , Karolinska University Hospital Huddinge, ; Stockholm, Sweden
[2
]ISNI 0000 0004 1937 0626, GRID grid.4714.6, Division of Hematology, Department of Medicine Huddinge, , Karolinska Institutet, ; Stockholm, Sweden
[3
]ISNI 0000 0001 2151 3065, GRID grid.5606.5, Division of Infectious Diseases, , University of Genoa and Ospedale Policlinico San Martino, ; Genova, Italy
[4
]ISNI 0000 0004 1767 647X, GRID grid.411251.2, Department of Hematology, , Hospital de la Princesa, ; Madrid, Spain
[5
]ISNI 0000000113287408, GRID grid.13339.3b, Department of Hematology, Oncology and Internal Medicine, , Medical University of Warsaw, ; Warsaw, Poland
[6
]Institut Paoli Calmettes & Inserm CBT-1409, Centres d’Investigations Cliniques en
Biothérapies, Marseille, France
[7
]ISNI 0000 0001 2190 5763, GRID grid.7727.5, Pediatric Hematology, Oncology and Stem Cell Transplantation Department, , University of Regensburg, ; Regensburg, Germany
[8
]ISNI 0000 0004 1767 8416, GRID grid.73221.35, Servicio de Hematologia y Hemoterapia, , Hospital Universitario Puerta de Hierro, ; Madrid, Spain
[9
]ISNI 0000 0004 0444 9382, GRID grid.10417.33, Laboratory of Hematology, Department of Laboratory Medicine, , Radboud University Medical Center, ; Nijmegen, the Netherlands
[10
]ISNI 0000000089452978, GRID grid.10419.3d, Willem-Alexander Children’s Hospital, Department of Pediatrics, , Leiden University Medical Centre Leiden, ; Leiden, the Netherlands
[11
]ISNI 0000 0004 1937 1100, GRID grid.412370.3, Department of Hematology, , Hospital Saint Antoine, ; Paris, France
[12
]ISNI 0000 0000 9244 0345, GRID grid.416353.6, St. Bartholomew’s Hospital, Barts Health NHS Trust, ; London, UK
[13
]ISNI 0000 0004 0430 9259, GRID grid.412917.8, The Christie NHS Foundation Trust, ; Manchester, UK
[14
]BMT Unit, Department of Hematology, Hospital St. Louis, Paris, France
[15
]ISNI 0000 0000 9422 8284, GRID grid.31410.37, Department of Haematology, , Sheffield Teaching Hospitals NHS Foundation Trust, ; Sheffield, UK
[16
]ISNI 0000 0004 0471 8845, GRID grid.410463.4, CHU de Lille, Univ Lille, INSERM, ; U1285 Lille, France
[17
]ISNI 0000000089452978, GRID grid.10419.3d, Willem-Alexander Children’s Hospital, Department of Pediatrics, , Leiden University Medical Center, ; Leiden, the Netherlands
[18
]ISNI 0000 0001 2180 3484, GRID grid.13648.38, Department of Stem cell Transplantation, , University Hospital Eppendorf, ; Hamburg, Germany
[19
]ISNI 0000 0001 0943 6490, GRID grid.5374.5, Pediatric Hematology and Oncology, , University Hospital, Collegium Medicum, Nicolaus Copernicus University Torun, ; Bydgoszcz, Poland
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