3
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      COVID-19 outcomes in patients with hematologic disease

      letter

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          To the Editor: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a novel coronavirus of zoonotic origin that emerged in China at the end of 2019. The infection, named Coronavirus Disease 2019 (COVID-19), is now spreading worldwide. As of April 16, 2020, the virus had affected more than 2,000,000 individuals and resulted in over 125,000 deaths worldwide. Mortality can be as high as 15% in elderly patients, and/or in patients with comorbidities [1, 2]. Based on the current available data, the incubation period (time from exposure to symptom development) is estimated as between 2 and 14 days [3]. At present, there are no approved treatment options in Europe and no available vaccine. Avoiding exposure by adhering to recommended hygiene procedures, isolation of infected persons and social distancing are the only prevention strategies recommended by the WHO [4]. Risk factors for COVID-19 severity and death include older age, along with comorbidities such as diabetes, hypertension, or cardiac disease [1, 2]. In addition, data from China suggest that patients with cancer have a significantly higher incidence of severe events (including intensive care unit admission, need of assisted ventilation, death) after contracting the virus (39% versus 8% in patients without cancer) [5]. Another study reported that cancer patients appear to be twice as likely to contract infection with SARS-CoV-2 [6]. Importantly, that study suggests that hospital admission and recurrent hospital visits, inherent to cancer patients’ management, are potential risk factors for SARS-CoV-2 infection [6]. To date, very few data are available on COVID-19 outcomes in patients with hematologic diseases. Only one 47-year-old patient with a lymphoma has been included in a previous report [5], and two articles have reported on the course of COVID-19 infection in a 39-year-old patient with chronic lymphocytic leukemia [7] and in a 60-year-old patient with multiple myeloma (MM) [8]. All three patients had a favorable outcome. Nevertheless, these were relatively young, unlike the overall patient population with hematologic neoplasms which is usually aged, comorbid and highly immunosuppressed. These patients are therefore expected to be a particularly vulnerable group for COVID-19. A better characterization of those infected with the virus is important. Here we describe the demographic characteristics, coexisting conditions, imaging findings, and outcomes among patients with hematologic disease and COVID-19 infection. We included all consecutive adult patients with a hematologic disease admitted to the Hematology Department (inpatient and outpatient admissions) of the Saint-Antoine-Hospital, AP-HP, Paris, France, with laboratory-confirmed COVID-19 infection between March 9 and April 4, 2020 and with at least 10 days of follow-up. A confirmed case of COVID-19 was defined by a positive result on a real-time RT-PCR assay of a specimen collected on a nasopharyngeal swab. We reviewed medical records to collect demographic, clinical, and treatment data and outcomes of COVID-19. All laboratory tests and radiologic assessments, including plain chest radiography and computerized chest tomography, were performed at the discretion of the treating physician. COVID-19 was suspected and screened by PCR in 48 patients with a hematologic disease and the infection was identified in 25. Clinical details on hematologic and treatment history and COVID-19 infection are listed in Table 1. The median patient age was 72 (range, 40–96) years, 68% were male. The median duration of symptoms before the COVID-19 PCR assay was performed, was 4 (range, 0–22) days. None of the patients had recently traveled to a country with known transmission such as China, Iran, or Italy, but five had direct contact with a COVID-19 positive family member. Among the remaining patients, six were already hospitalized (none of them in the hematology department) at the time of viral infection symptoms’ onset due to a fall episode (n = 2), MM diagnosis (n = 3) or accidental cardiac drug overdose (n = 1). Ten patients had one or more outpatient visits to the hematology department, suggesting a possible nosocomial origin of their infection. In the remaining four patients, the origin of COVID-19 infection was unknown. Table 1 Clinical characteristics, treatments and outcomes of patients with hematological malignancies and SARS-CoV-2 infection. Patient No Age Sex BMI Hemalogical disease Hematological status Hematological treatment Ongoing corticosteroids Number of treatment lines Previous transplant Comorbidities Time between onset of symptoms and diagnosis (days) Radiologic diagnosis ARDS Invasive mechanical ventilation COVID-19 management Follow-up since first symptoms (days) Survival status 1 65 M 28.7 Myeloma Complete remission Ongoing isatuximab + DXM maintenance Yes 2 Autologous HBP 3 Positive CT Yes Yes Best supportive care 17 Dead 2 73 F 30.2 Myeloma Diagnosis None No 0 No Diabetes, HBP, stroke, obesity 4 Positive X-ray Yes Yes Best supportive care 13 Dead 3 65 M 24.3 Myeloma Complete remission Ongoing lenalidomide maintenance No 1 Autologous HBP 4 ND No No HCQ/AZT + Tociluzumab 40 Alive 4 61 M 41.5 Lymphoma (DLBCL) Complete remission None, 3 months post CAR T-cell No 4 Autologous and allogeneic Diabetes, HBP, obesity 7 Positive CT Yes Yes Best supportive care 38 Alive 5 61 F 31.6 Myeloma Partial remission Ongoing carfilzomib + lenalidomide + DXM Yes 6 Autologous Diabetes, HBP, stroke, obesity 7 Positive CT No No Lopinavir-ritonavir 34 Alive 6 45 M 45.8 PNH Partial remission Ongoing eculizumab No 1 No Obesity 4 Positive CT Yes Yes Best supportive care 32 Alive 7 40 F 26.7 ALL Complete remission None, 9 months post allo-HSCT No 1 Allogeneic No 0 Positive CT Yes Yes Best supportive care 23 Alive 8 78 M 26.3 MDS Progressive disease Best supportive care Yes 0 No Glioma, stroke 1 Positive X-ray Yes No Tociluzumab + corticosteroids 10 Dead 9 79 M 37.8 Lymphoma (hairy cell) Complete remission None, 12 years post Cladribine No 2 No HBP, obesity, CKD, MDS, MGUS 2 Positive X-ray No No Lopinavir-ritonavir 26 Alive 10 62 F 24.2 LGL leukemia Complete remission None, 18 months post cyclophosphamide No 1 No No 1 Positive CT No No Best supportive care 32 Alive 11 75 M 28.7 MDS Progressive disease Best supportive care No 0 No Diabetes, HBP 7 Positive CT Yes No Best supportive care 27 Dead 12 81 M 21.3 Myeloma Partial remission Ongoing lenalidomide + DXM Yes 1 No HBP 3 Positive CT Yes No Best supportive care 10 Dead 13 81 M 30.1 Lymphoma (Marginal zone) Progressive disease None, 14 months post rituximab + bendamustine No 1 No Diabetes, HBP, stroke, obesity, COPD 0 ND No No Best supportive care 35 Alive 14 63 M 25.0 Lymphoma (hairy cell) Complete remission None, 5 years post rituximab No 2 No HBP 5 ND No No Best supportive care 32 Alive 15 92 M 20.0 Myeloma Progressive disease Ongoing cyclophosphamide + prednisone Yes 3 No HBP 14 Positive X-ray Yes No Best supportive care 14 Dead 16 89 M 23.6 Myeloma Stable disease Ongoing lenalidomide + DXM Yes 2 No CKD 6 Positive CT Yes No Best supportive care 21 Dead 17 61 M 23.9 Myeloma Complete remission Ongoing bortezomib maintenance No 2 Autologous Cardiomyopathy 12 Positive X-ray No No Best supportive care 29 Alive 18 86 M 22.3 CLL Stable disease Wait and watch No 0 No HBP, stroke, CKD 10 Positive X-ray Yes No Lopinavir-ritonavir + corticosteroids 17 Dead 19 68 F 24.4 Myeloma Partial remission Ongoing daratumumab + lenalidomide + DXM Yes 2 No Diabetes, HBP 1 Positive CT Yes Yes Lopinavir-ritonavir + corticosteroids + tociluzumab 17 Alive 20 72 F 31.5 Myeloma Partial remission Ongoing daratumumab + lenalidomide + DXM Yes 1 No HBP, obesity 0 Positive CT No No Best supportive care 20 Alive 21 76 M 19.3 MDS Progressive disease Best supportive care No 1 No CKD, COPD 3 Positive CT No No Best supportive care 20 Alive 22 97 F 17.2 MDS Progressive disease Best supportive care No 1 No Pancreatic adenocarcinoma, CKD 2 ND Yes No Best supportive care 4 Dead 23 71 M 24.1 Lymphoma (DLBCL) Complete remission Ongoing rituximab maintenance No 2 Autologous HBP, stroke 22 Positive CT No No Anakinra 29 Alive 24 63 M 22.8 Lymphoma (Poppema) Complete remission Ongoing rituximab-CHOP Yes 1 No HBP 10 Positive X-ray No No Best supportive care 19 Alive 25 75 F 41.4 Waldenström macroglobulinemia Partial remission Ongoing rituximab + cyclophosphamide + DXM Yes 3 No HBP, obesity, epidermoid carcinoma of the anal canal 1 Positive CT No No Best supportive care 14 Alive M male, F female, BMI body mass index (kg/m2), DLBLC diffuse large B-cell lymphoma, PNH paroxysmal nocturnal hemoglobinuria, ALL acute lymphoblastic leukemia, MDS myelodysplastic syndrome, LGL large granular lymphocyte, CLL chronic lymphoid leukemia, DXM dexamethasone, allo-HSCT allogeneic hematopoietic stem cell transplantation, HBP high blood pressure, CKD chronic kidney disease, MGUS monoclonal gammopathy of undertemined significance, COPD chronic obstructive pulmonary disease, CT computed tomography, HCQ hydroxychloroquine, AZT azithromycine. The most common symptoms at diagnosis were fever (n = 22, 89%), cough (n = 19, 79%), and shortness of breath (n = 19, 79%). The majority (n = 20, 80%) of patients had a lymphoid malignancy, including 10 with MM (40%), and only 4 (16%) had a myeloid malignancy (myelodysplastic syndrome). One patient had paroxysmal nocturnal hemoglobinuria. Patients received a median of 1 (range, 0-6) line of treatment. Fourteen patients (56%) were being treated for their underlying disease at the time of COVID-19 diagnosis, with 10 (40%) receiving corticosteroids. Seven patients had a history of hematopoietic stem cell transplantation (autologous, n = 5, allogeneic, n = 1, and both, n = 1) and one had been treated with anti-CD19 CAR T cells 3 months before. Of note, the four patients with myelodysplastic syndrome received only supportive care, one patient with MM had just been diagnosed and had not initiated therapy, and one with stage A chronic lymphoid leukemia was on a ‘wait and watch’ strategy. In addition, all patients but two (92%) had additional chronic medical conditions. In particular, 17 (68%) patients had high blood pressure, 8 (32%) were obese, and 6 (25%) had diabetes mellitus. Fourteen (56%) patients had more than one coexisting condition besides the hematologic disease. As reported elsewhere [1], lymphopenia was common at hospital admission (n = 23, 92%), with a median lymphocyte count of 760/µL (range, 150–5910). Only one patient had severe neutropenia at the time of COVID-19 diagnosis (median, 2,350/µL; range, 70–11,400). A computerized tomographic scan of the chest was performed in 14 patients and bilateral ground glass opacities were evident in all of them. A chest radiography was performed in seven additional patients and all radiographs showed bilateral pulmonary opacities. As of April 16, 2020, with a median follow-up since symptom onset of 29 days (range, 14–40), 13 of the 18 patients (52%) developed acute respiratory distress syndrome (ARDS) [9] and 6 received mechanical ventilation (Supplementary Fig. 1). It was decided not to transfer the remaining seven patients with ARDS to the intensive care unit because of their age and hematological disease history. All patients who did not develop ARDS were alive at last follow-up. Of patients with ARDS, nine died, including two who received mechanical ventilation. The Kaplan–Meier estimate of overall survival at 1 month was 60%. It is hypothesized that similarly to patients with solid malignancies, those with hematologic neoplasms are more susceptible to COVID-19 and develop severe forms. This study highlighted the following observations: patients with a hematologic malignancy harbored a higher risk of developing a severe form of COVID-19 with ARDS, requiring mechanical ventilation, compared to those in the general French population without an underlying medical condition [1]. This translated into a very high mortality (estimated as 40% at 1 month) which we can expect to be even higher with a longer follow-up. Furthermore, fewer than half of the patients were receiving active anti-neoplastic treatment before COVID-19, highlighting that vigilance must remain high in every patient given the long-term immunosuppressive effect of prior therapies. Interestingly, for the majority of the patients, a nosocomial origin was suspected, owing to their hospitalized status or to outpatient visits within the 14 previous days. We observed an overrepresentation of patients with MM in our cohort (although MM is not overrepresented in our department), suggesting that such patients are particularly vulnerable, owning to the immunosuppression associated with the disease and its treatment, in particular steroids. In fact, the detrimental effect of steroids on patient outcome has been established during previous coronavirus outbreaks (SARS-CoV-1 and MERS-CoV) [10, 11], and a similar impact is expected in patients infected with SARS-CoV-2 [12]. Finally, we must emphasize that more than half of the patients were over 65 years of age, and 92% had at least one additional comorbidity, factors which have been associated with COVID-19 severity [1, 2], and which have possibly contributed to the seriousness of the infection and high mortality rate observed in our study. Overall, patients with hematologic malignancies appear to be a population very vulnerable to COVID-19 infection. Therefore, hematology departments should remain COVID-19 free zones dedicated solely to hematologic treatment. Furthermore, patients should strictly comply with social distancing and hospital outpatient visits should be reduced to mitigate the risk of COVID-19. Supplementary information Supplementary Figure

          Related collections

          Most cited references5

          • Record: found
          • Abstract: found
          • Article: not found

          Clinical Characteristics of Coronavirus Disease 2019 in China

          Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. Methods We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Results The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. Conclusions During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

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

            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.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Clinical evidence does not support corticosteroid treatment for 2019-nCoV lung injury

              The 2019 novel coronavirus (2019-nCoV) outbreak is a major challenge for clinicians. The clinical course of patients remains to be fully characterised, little data are available that describe the disease pathogenesis, and no pharmacological therapies of proven efficacy yet exist. Corticosteroids were widely used during the outbreaks of severe acute respiratory syndrome (SARS)-CoV 1 and Middle East respiratory syndrome (MERS)-CoV, 2 and are being used in patients with 2019-nCoV in addition to other therapeutics. 3 However, current interim guidance from WHO on clinical management of severe acute respiratory infection when novel coronavirus (2019-nCoV) infection is suspected (released Jan 28, 2020) advises against the use of corticosteroids unless indicated for another reason. 4 Understanding the evidence for harm or benefit from corticosteroids in 2019-nCoV is of immediate clinical importance. Here we discuss the clinical outcomes of corticosteroid use in coronavirus and similar outbreaks (table ). Table Summary of clinical evidence to date Outcomes of corticosteroid therapy * Comment MERS-CoV Delayed clearance of viral RNA from respiratory tract 2 Adjusted hazard ratio 0·4 (95% CI 0·2–0·7) SARS-CoV Delayed clearance of viral RNA from blood 5 Significant difference but effect size not quantified SARS-CoV Complication: psychosis 6 Associated with higher cumulative dose, 10 975 mg vs 6780 mg hydrocortisone equivalent SARS-CoV Complication: diabetes 7 33 (35%) of 95 patients treated with corticosteroid developed corticosteroid-induced diabetes SARS-CoV Complication: avascular necrosis in survivors 8 Among 40 patients who survived after corticosteroid treatment, 12 (30%) had avascular necrosis and 30 (75%) had osteoporosis Influenza Increased mortality 9 Risk ratio for mortality 1·75 (95% CI 1·3–2·4) in a meta-analysis of 6548 patients from ten studies RSV No clinical benefit in children10, 11 No effect in largest randomised controlled trial of 600 children, of whom 305 (51%) had been treated with corticosteroids CoV=coronavirus. MERS=Middle East respiratory syndrome. RSV=respiratory syncytial virus. SARS=severe acute respiratory syndrome. * Hydrocortisone, methylprednisolone, dexamethasone, and prednisolone. Acute lung injury and acute respiratory distress syndrome are partly caused by host immune responses. Corticosteroids suppress lung inflammation but also inhibit immune responses and pathogen clearance. In SARS-CoV infection, as with influenza, systemic inflammation is associated with adverse outcomes. 12 In SARS, inflammation persists after viral clearance.13, 14 Pulmonary histology in both SARS and MERS infections reveals inflammation and diffuse alveolar damage, 15 with one report suggesting haemophagocytosis. 16 Theoretically, corticosteroid treatment could have a role to suppress lung inflammation. In a retrospective observational study reporting on 309 adults who were critically ill with MERS, 2 almost half of patients (151 [49%]) were given corticosteroids (median hydrocortisone equivalent dose [ie, methylprednisolone 1:5, dexamethasone 1:25, prednisolone 1:4] of 300 mg/day). Patients who were given corticosteroids were more likely to require mechanical ventilation, vasopressors, and renal replacement therapy. After statistical adjustment for immortal time and indication biases, the authors concluded that administration of corticosteroids was not associated with a difference in 90-day mortality (adjusted odds ratio 0·8, 95% CI 0·5–1·1; p=0·12) but was associated with delayed clearance of viral RNA from respiratory tract secretions (adjusted hazard ratio 0·4, 95% CI 0·2–0·7; p=0·0005). However, these effect estimates have a high risk of error due to the probable presence of unmeasured confounders. In a meta-analysis of corticosteroid use in patients with SARS, only four studies provided conclusive data, all indicating harm. 1 The first was a case-control study of SARS patients with (n=15) and without (n=30) SARS-related psychosis; all were given corticosteroid treatment, but those who developed psychosis were given a higher cumulative dose than those who did not (10 975 mg hydrocortisone equivalent vs 6780 mg; p=0·017). 6 The second was a randomised controlled trial of 16 patients with SARS who were not critically ill; the nine patients who were given hydrocortisone (mean 4·8 days [95% CI 4·1–5·5] since fever onset) had greater viraemia in the second and third weeks after infection than those who were given 0·9% saline control. 5 The remaining two studies reported diabetes and avascular necrosis as complications associated with corticosteroid treatment.7, 8 A 2019 systematic review and meta-analysis 9 identified ten observational studies in influenza, with a total of 6548 patients. The investigators found increased mortality in patients who were given corticosteroids (risk ratio [RR] 1·75, 95% CI 1·3–2·4; p=0·0002). Among other outcomes, length of stay in an intensive care unit was increased (mean difference 2·1, 95% CI 1·2–3·1; p<0·0001), as was the rate of secondary bacterial or fungal infection (RR 2·0, 95% CI 1·0–3·8; p=0·04). Corticosteroids have been investigated for respiratory syncytial virus (RSV) in clinical trials in children, with no conclusive evidence of benefit and are therefore not recommended. 10 An observational study of 50 adults with RSV infection, in which 33 (66%) were given corticosteroids, suggested impaired antibody responses at 28 days in those given corticosteroids. 17 Life-threatening acute respiratory distress syndrome occurs in 2019-nCoV infection. 18 However, generalising evidence from acute respiratory distress syndrome studies to viral lung injury is problematic because these trials typically include a majority of patients with acute respiratory distress syndrome of non-pulmonary or sterile cause. A review of treatments for acute respiratory distress syndrome of any cause, based on six studies with a total of 574 patients, 19 concluded that insufficient evidence exists to recommend corticosteroid treatment. 20 Septic shock has been reported in seven (5%) of 140 patients with 2019-nCoV included in published reports as of Jan 29, 2020.3, 18 Corticosteroids are widely used in septic shock despite uncertainty over their efficacy. Most patients in septic shock trials have bacterial infection, leading to vasoplegic shock and myocardial insufficiency.21, 22 In this group, there is potential that net benefit might be derived from steroid treatment in severe shock.21, 22 However, shock in severe hypoxaemic respiratory failure is often a consequence of increased intrathoracic pressure (during invasive ventilation) impeding cardiac filling, and not vasoplegia. 23 In this context, steroid treatment is unlikely to provide a benefit. No clinical data exist to indicate that net benefit is derived from corticosteroids in the treatment of respiratory infection due to RSV, influenza, SARS-CoV, or MERS-CoV. The available observational data suggest increased mortality and secondary infection rates in influenza, impaired clearance of SARS-CoV and MERS-CoV, and complications of corticosteroid therapy in survivors. If it is present, the effect of steroids on mortality in those with septic shock is small, and is unlikely to be generalisable to shock in the context of severe respiratory failure due to 2019-nCoV. Overall, no unique reason exists to expect that patients with 2019-nCoV infection will benefit from corticosteroids, and they might be more likely to be harmed with such treatment. We conclude that corticosteroid treatment should not be used for the treatment of 2019-nCoV-induced lung injury or shock outside of a clinical trial.
                Bookmark

                Author and article information

                Contributors
                florent.malard@inserm.fr
                Journal
                Bone Marrow Transplant
                Bone Marrow Transplant
                Bone Marrow Transplantation
                Nature Publishing Group UK (London )
                0268-3369
                1476-5365
                6 May 2020
                : 1-5
                Affiliations
                ISNI 0000 0001 2308 1657, GRID grid.462844.8, Service d’Hématologie Clinique et Thérapie Cellulaire, Hôpital Saint-Antoine, , Sorbonne Université, INSERM UMRs 938, ; Paris, France
                Author information
                http://orcid.org/0000-0002-3474-0002
                http://orcid.org/0000-0001-9463-2823
                Article
                931
                10.1038/s41409-020-0931-4
                7201203
                32376969
                bd81c0e9-900c-4a37-a815-7f7365ca6af8
                © Springer Nature Limited 2020

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 16 April 2020
                : 23 April 2020
                : 27 April 2020
                Categories
                Correspondence

                Transplantation
                haematological cancer,infectious diseases
                Transplantation
                haematological cancer, infectious diseases

                Comments

                Comment on this article

                scite_

                Similar content60

                Cited by87

                Most referenced authors1,110