Piñana et al. Exp Hematol Oncol (2020) 9:21 https://doi.org/10.1186/s40164-020-00177-z Experimental Hematology & Oncology RESEARCH Open Access Risk factors and outcome of COVID‑19 in patients with hematological malignancies José Luis Piñana1,2,36* , Rodrigo Martino3, Irene García‑García4, Rocío Parody5, María Dolores Morales6, Gonzalo Benzo7, Irene Gómez‑Catalan8, Rosa Coll9, Ignacio De La Fuente10, Alejandro Luna4, Beatriz Merchán6, Anabelle Chinea4, Dunia de Miguel6, Ana Serrano8, Carmen Pérez10, Carola Diaz11, José Luis Lopez12, Adolfo Jesús Saez4, Rebeca Bailen13, Teresa Zudaire14, Diana Martínez15, Manuel Jurado16, María Calbacho17, Lourdes Vázquez18, Irene Garcia‑Cadenas3, Laura Fox19, Ana I. Pimentel20, Guiomar Bautista21, Agustin Nieto22, Pascual Fernandez23, Juan Carlos Vallejo24, Carlos Solano25, Marta Valero26, Ildefonso Espigado27, Raquel Saldaña28, Luisa Sisinni29, Josep Maria Ribera30, Maria Jose Jimenez30, Maria Trabazo31, Marta Gonzalez‑Vicent32, Noemí Fernández33, Carme Talarn34, Maria Carmen Montoya8, Angel Cedillo35 and Anna Sureda5 on behalf of Infectious Complications Subcommittee of the Spanish Hematopoietic Stem Cell Transplantation and Cell Therapy Group (GETH) Abstract Background: Prognostic factors of poor outcome in patients with hematological malignancies and COVID-19 are poorly defined. Patients and methods: This was a Spanish transplant group and cell therapy (GETH) multicenter retrospective observational study, which included a large cohort of blood cancer patients with laboratory-confirmed SARS-CoV-2 infection through PCR assays from March 1st 2020 to May 15th 2020. Results: We included 367 pediatric and adult patients with hematological malignancies, including recipients of autologous (ASCT) (n = 58) or allogeneic stem cell transplantation (allo-SCT) (n = 65) from 41 hospitals in Spain. Median age of patients was 64 years (range 1–93.8). Recipients of ASCT and allo-SCT showed lower mortality rates (17% and 18%, respectively) compared to non-SCT patients (31%) (p = 0.02). Prognostic factors identified for day 45 overall mortality (OM) by logistic regression multivariate analysis included age > 70 years [odds ratio (OR) 2.1, 95% con‑ fidence interval (CI) 1.2–3.8, p = 0.011]; uncontrolled hematological malignancy (OR 2.9, 95% CI 1.6–5.2, p < 0.0001); ECOG 3–4 (OR, 2.56, 95% CI 1.4–4.7, p = 0.003); neutropenia (< 0.5 × 109/L) (OR 2.8, 95% CI 1.3–6.1, p = 0.01); and a C-reactive protein (CRP) > 20 mg/dL (OR 3.3, 95% CI 1.7–6.4, p < 0.0001). In multivariate analysis of 216 patients with very severe COVID-19, treatment with azithromycin or low dose corticosteroids was associated with lower OM (OR 0.42, 95% CI 0.2–0.89 and OR 0.31, 95% CI 0.11–0.87, respectively, p = 0.02) whereas the use of hidroxycloroquine did not show significant improvement in OM (OR 0.64, 95% CI 0.37–1.1, P = 0.1). *Correspondence: jlpinana@gmail.com 36 Division of Clinical Hematology, Hospital Universitario la Fe de Valencia, Avda Fernando Abril Martorell, 106 CP 46026 Valencia, Spain Full list of author information is available at the end of the article © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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Exp Hematol Oncol (2020) 9:21 Page 2 of 16 Conclusions: In most patients with hematological malignancies COVID-19 mortality was directly driven by older age, disease status, performance status, as well as by immune (neutropenia) parameters and level of inflammation (high CRP). Use of azithromycin and low dose corticosteroids may be of value in very severe COVID-19. Background March 1st 2020 to May 15th 2020 in 41 participating The coronavirus infectious disease 2019 (COVID- Spanish centers. The status of all patients (and thus the 19) pandemic caused by the new zoonotic coronavi- study database) was updated on May 21th 2020. During rus (SARS-CoV-2) is causing a massive impact globally. the study period, hematological patients from participat- Mortality can be as high as 15% in elderly patients, and/ ing centers with COVID-19 were prospectively registered or in patients with comorbidities [1, 2]. Risk factors for through REDcap on-line platform in the GETH database COVID-19 severity and death include older age, diabetes, by completing an essential medical data form, and more hypertension, or cardiac disease [1–4]. Prior experience detailed baseline and outcome data were retrospectively with seasonal community-acquired respiratory virus requested afterwards with follow-up forms. The infor- (CARV) infections showed that, in immunocompro- mation collected included respiratory symptoms (rhi- mised patients, these infections are notable for prolonged norrhea, cough, dyspnea, oxygen requirement, sinusitis, viral shedding, higher rates of pneumonia and mortal- otitis, and fever), SARS-COV-2-related hospital admis- ity [5, 6]. Thus, it would be expected that COVID-19 be sion, oxygen requirement, ICU admission, antiviral particularly life threatening in patients with hematologi- COVID-19 therapy given for at least 3 consecutive days, cal malignancies. In fact, initial reports suggested that corticosteroid use and anti-cytokine therapy. The dose of patients with cancer had an estimated two-fold increased corticosteroids was divided in 2 groups, ≤ or > 0.5 mg/kg/ risk of contracting SARS-CoV-2 than the general popu- day of methylprednisolone (or equivalent doses of pred- lation and, if infected, also had a higher risk of severe nisone, dexamethasone or hydrocortisone). Details on events [intensive care unit (ICU) admission, invasive the underlying disease and its treatment(s) were also cap- ventilation, or death] compared to patients without can- tured (details not shown). Baseline laboratory variables, cer [7–9]. The outcomes of COVID-19 in patients with if available [absolute lymphocyte and neutrophil counts, hematological disorders such as leukemia, lymphoma, C-reactive protein (CRP), IL6, ferritin and D-dimer lev- myeloma and recipients of autologous (ASCT) or alloge- els], were also requested at the time or within 3 days neic hematopoietic stem cell transplantation (allo-SCT) after SARS-CoV-2 detection. Detailed microbiological are of utmost interest due to their high degree of humoral findings and radiological pulmonary patterns were also and cellular immunosuppression status. Recent studies required for each episode. have reported an overall COVID-19 related mortality of 32 to 40% in hematological patients [10–14]. Future chal- Definitions lenges include the identification of prognostic factors We classified COVID-19 stages according to the recent that could help in risk assessment and decision-making published staging proposal [15]. Briefly, stage 1 refers to for effective supportive care and antiviral therapy or in early establishment of disease (symptomatic infection of cases of limited access to ICU. the upper respiratory tract only, with or without fever The current study addresses the COVID-19 clinical and generalized malaise). In stage 1 we included patients course, outcome and risk factors for severe disease and reported as being asymptomatic by the registering phy- mortality in a large series of patients with hematological sician, as well as patients with upper respiratory symp- disorders, including recipients of ASCT and allo-SCT. toms (rhinorrhea, sinusitis, otitis, or pharyngitis) and/or systemic symptoms (fever, diarrhea, nausea or vomiting, Patients and methods fatigue and myalgia) in the absence of lower respiratory Study population tract disease (LRTD) symptoms and/or any indication of This is a retrospective multicenter cohort study of the pulmonary infiltrates by radiology, either chest X-ray or Infectious Complications Subcommittee (GRUCINI) of computed tomography (CT) scan. Stage II was divided the Spanish Hematopoietic Stem Cell Transplantation into IIA and IIB. Stage IIA refers to patients with LRTD and Cell Therapy Group (GETH). with radiological proof of pulmonary involvement but without requirements for oxygen support to maintain Inclusion criteria and data preparation an oxygen saturation > 92%. Stage IIB included patients This series included patients (pediatric and adult) with meeting the IIA criteria but who required oxygen sup- PCR-documented SARS-CoV-2 infection diagnosed from port (i.e., patients with acute respiratory failure). Finally, Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 3 of 16 we did not classify cases as stage III since we did not analysis, only variables with parameter estimates show- have sufficient inflammatory blood markers in all cases, ing a p value ≤ 0.10 in the univariate analysis were finally which are required for upgrading a stage IIB to a stage included. Two-sided exact P values were reported and III. Patients with stage IIB thus comprise all patients with p values ≤ 0.05 were considered statistically significant. severe COVID-19, while stage IIA can be considered to COVID-19 related mortality according to different clini- have moderate COVID-19. We considered very severe cal and biological variables was estimated from time of COVID-19 those who developed stage IIB and those who SARS-CoV-2 detection using Kaplan–Meier curves and required ICU admission due to respiratory failure and/or univariate comparisons were made with the log-rank test. hemodynamic instability. All the analyses were performed using the statistical soft- Disease status at the time of SARS-CoV-2 detection ware SPSS v. 20. was defined according to each specific disease’s revised criteria for leukemia, myeloproliferative neoplasm, mul- Results tiple myeloma and lymphoma [16–18]. Performance sta- Patient characteristics tus at the time of COVID-19 was graded according to the Overall, 388 pediatric and adult patients with hema- Eastern Cooperative Oncology Group (ECOG) [19]. Car- tological malignancies were initially registered. How- diomyopathy was defined by the patient’s medical history ever, 21 cases were excluded due to negative results for or when the left ventricular ejection fraction was < 50%, SARS-CoV-2 PCR testing, irrespective of being clas- as were moderate to severe valvular disease, prior or cur- sified as “probable COVID-19” by their hospital or rent history of coronary artery disease, or heart failure. regional epidemiologists based on a compatible clinical presentation and the large numbers of infections in the Technical and diagnostic considerations community. Thus, the study includes 367 patients with Patients with URTD and/or LRTD symptoms underwent laboratory-confirmed SARS-CoV-2. Patient and disease nasopharyngeal aspiration, nasopharyngeal swabs, or characteristics according to whether they received or not an induced sputum test, while BAL was performed very a hematopoietic stem cell transplant (ASCT or allo-SCT) rarely and only in patients with negative PCR in the upper are detailed in Table 1. The median age was 64 years airway with radiology-proven LRTD and whenever an (range 1–93.8). Overall, the most common hemato- alternative diagnosis for the patient was deemed possible logical disease was non-Hodgkin’s lymphoma (n = 91, by each treating team. Most patients underwent weekly 25%) followed by plasma cell disorders (n = 81, 22%). As PCR test monitoring until negativity of SARS-CoV-2, expected, patients who did not receive SCT were older, especially when the patients improved and discharge was had been diagnosed more recently of their hematological being considered, or for epidemiological reasons. The malignancy and/or had received chemotherapy less than specific method used for performing the PCR was not 40 days before the SARS-CoV-2 infection, and thus they captured. During this pandemic, GETH published on- also had higher rates of uncontrolled hematological dis- line recommendations on the diagnosis, management, ease (not in partial or complete remission). Of note, they testing and infectious control measures (available in the had higher comorbidities such as hypertension, cardio- following website; https​://www.geth.es/). myopathy and dyslipidemia (p < 0.01 for all comparisons). In contrast, recipients of SCT had received more prior Endpoints and statistical analysis lines of therapy, while allo-SCT recipients were com- The primary objective of the study was to describe clini- monly receiving immunosuppressive drugs at the time of cal characteristics of COVID-19 in onco-hematological COVID-19 diagnosis (p < 0.01 for all comparisons). patients. We also analyzed potential risk factors (RFs) for the development of severe COVID-19 (stage IIB) and Clinical characteristics of COVID‑19 in non‑transplant day 45 mortality after SARS-CoV-2 detection. Lastly, we and transplant patients explored the effect of antiviral and anti-cytokine therapy Detailed clinical and laboratory characteristics of on mortality in patients with very severe COVID-19. COVID-19 by patient category (non-SCT, ASCT and The main characteristics of patients were reported allo-SCT recipients) are shown in Table 2. Most patients by descriptive statistics on the total of the available (n = 250, 68%) were diagnosed from March 19th to April information. Median and range were used for continu- 8th (see Fig. 1). Out of the 367 cases, 285 (78%) were ous variables, while absolute and percentage frequen- diagnosed in the outpatient or emergency units, and cies were used for categorical variables. Univariate and non-SCT patients were more commonly diagnosed dur- multivariate analyses of clinical, laboratory and thera- ing a hospital admission for treatment of their hemato- peutic variables associated with outcomes were calcu- logical disease or its complications (23% vs. 12% in SCT lated using logistic regression models. For multivariate recipients). Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 4 of 16 Table 1 Patient’s characteristics Characteristics Hematological disease, ASCT (n = 58) Allo-SCT (n = 65) p value non-SCT (n = 244) Age (years), median (range) 71 (7–93) 61 (34–75) 48 (1–70) < 0.0001 0–40 years, n (%) 20 (8) 1 (2) 25 (39) < 0.0001 41–60 years, n (%) 51 (22) 22 (38) 21 (32) 61–70 years, n (%) 45 (18) 30 (52) (17) (26) >71 years, n (%) 128 (52) 5 (8) 2 (3) Male, n (%) 132 (54) 34 (59) 40 (61) 0.5 Baseline disease, n (%) < 0.0001 AML 44 (19) 0 23 (35) ALL 12 (5) 1 (2) 12 (18) MDS 12 (5) 0 10 (15) CMPD 27 (11) 0 2 (3) NHL 68 (28) 17 (30) 6 (9) CLL 2 (10) 0 2 (3) Plasmatic cell disorder 40 (16) 38 (66) 3 (5) AA or auto-immune disorders 13 (6) 1 (2) 5 (8) Disease status, n (%) < 0.0001 CR/PR 81 (33)/45 (18) 28 (48)/16 (28) 56 (86)/0 Not in remission (Rel/Ref/Prog) 10 (4)/8 (3)/23 (9) 5 (8)/1 (2)/6 (10) 6 (9)/0/2 (3) Active disease not requiring therapy 22 (9) 0 0 Prior lines of therapy 0–1 189 (77) 21 (36) 26 (40) < 0.001 >1 55 (23) 37 (64) 39 (60) Allo-SCT, n (%) HLA identical sibling 29 (45) Unrelated Donor 22 (34) Haplo-identical family donor 14 (21) Time from transplant to COVID-19, days (range) 790 (10–10661) 441 (6–7597) 0.1 Prior therapy/conditioning 40 days before COVID-19, n (%) 102 (42) 24 (41) 10 (15) < 0.0001 Disease diagnosed within 40 days of COVID-19, n (%) 60 (25) 0 0 < 0.0001 Under immunosuppressive drugs before COVID-19 CNI or sirolimus or MMF 0 0 28 (43) < 0.0001 Performance status, n (%) 0.2 ECOG 0–1 166 (68) 48 (82) 50 (77) ECOG 2/ECOG 3–4 45 (18)/28 (11) 7 (12)/2 (3) 7 (11)/5 (8) Pulmonary/cardiovascular risk factors, n (%) Active smoking 27 (11) 4 (7) 2 (3) 0.12 Arterial hypertension 118 (48) 12 (21) 12 (18) < 0.0001 Cardiomyopathy 51 (21) 10 (17) 4 (6) 0.021 Dyslipidemia 78 (32) 11 (19) 5 (8) < 0.0001 Diabetes 9 (4) 3 (5) 3 (5) Median F/U after COVID-19, days (range) 21 (0–74) 30 (0–72) 35 (0–72) 0.2 Median F/U in survivors, days (range) 33 (10–74) 34 (11–72) 40 (12–72) 0.2 SCT: stem cell transplantation; ASCT: autologous stem cell transplantation; allo-SCT: allogeneic hematopoietic stem cell transplantation; AML: acute myeloid leukemia; ALL: acute lymphoblastic leukemia; MDS: myelodysplastic syndrome; cMPD: chronic myeloproliferative disease; NHL: non-Hodgkin lymphoma; CLL: chronic lymphocytic leukemia; AA: aplastic anemia; CR: complete remission; PR: partial remission; Rel: relapse; Ref: refractory; Prog: progression; CNI: calcineurin inhibitors; MMF: mycophenolate mophetil acid; F/U: follow-up Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 5 of 16 Table 2 Clinical and laboratory characteristics Characteristics Hematological disease, ASCT (n = 58) Allo-HCT (n = 65) p value non-SCT (n = 244) Place of SARS-CoV-2 infection, n (%) 0.1 Outpatient 180 (74) 50 (86) 55 (85) Inpatient in specialized hospital 55 (23) 7 (12) 8 (12) Hospice institution 9 (4) 1 (2) 2 (3) COVID-related hospital admission, n (%) 163 (67) 42 (72) 44 (68) 0.079 Symptoms, n (%) Asymptomatic 19 (8) 6 (10) 5 (8) 0.9 Fever 178 (73) 40 (69) 41 (63) 0.6 Rhinorrhea 29 (12) 11 (19) 14 (22) 0.3 Pharyngitis 15 (6) 3 (5) 9 (14) 0.09 Fatigue 140 (57) 24 (41) 32 (49) 0.25 Myalgia 51 (21) 9 (16) 13 (20) 0.38 Cough 175 (72) 30 (52) 39 (60) 0.069 Diarrhea 54 (22) 15 (26) 12 (18) 0.5 Emesis 23 (9) 8 (14) 6 (9) 0.46 COVID-19 ­stagea, n (%) Stage 1 41 (17) 15 (26) 18 (28) 0.075 Stage 2A 70 (29) 22 (38) 19 (29) 0.38 Stage 2B 133 (55) 21 (36) 28 (43) 0.027 Oxygen support, n (%) 136 (56) 24 (41) 32 (49) 0.021 Abnormal radiological pulmonary finding, n (%) 200 (82) 44 (76) 46 (71) 0.35 Antiviral COVID-19 therapy, n (%) 0.05 None 49 (20) 16 (28) 13 (20) HCQ 15 (6) 0 11 (17) HCQ + AZT 36 (15) 5 (9) 8 (12) HCQ + AZT + lop/rit 14 (5) 3 (5) 1 (1) lop/rit 29 (12) 4 (9) 5 (8) HCQ + lop/rit 32 (13) 14 (24) 8 (12) AZT + lop/rit 39 (16) 6 (12) 8 (12) AZT 24 (10) 5 (7) 7 (11) Remdesivir 3 (1) 3 (5) 2 (3) Other 4 (2) 3 (5) 3 (5) Corticosteroid therapy 0.029 No 132 (54) 40 (69) 45 (69) ≤0.5 mg/kg/dayb 29 (12) 7 (12) 9 (14) >0.5 mg/kg/dayb 83 (34) 11 (19) 11 (17) Anti-cytokine supportive therapy, n (%) Tocilizumab 26 (11) 10 (17) 14 (21) 0.05 Anakinra 10 (4) 3 (5) 5 (8) Baricitinib 6 (2) 1 (2) 0 Laboratory characteristics at the time of SARS-CoV-2 detection ANC < 0.5 × 109/L, n (%) 36 (15) 4 (7) 4 (6) 0.089 ALC < 0.5 × 109/L, n (%) 99 (41) 22 (38) 19 (29) 0.27 Platelet count (× ­109/L), median (range) 109 (1–1075) 127 (5–410) 115 (10–548) 0.4 < 20 × ­109/L 28 (13) 2 (4) 4 (7) 21–50 × ­109/L 27 (12) 7 (14) 9 (15) > 50 × ­109/L 166 (75) 42 (82) 46 (78) CRP > 20 mg/dL (n/evaluable, %) 152/217 (70) 23/48 (48) 25/54 (46) 0.001 IL-6 > 50 pg/mL (n/evaluable, %) 28/70 (40) 6/15 (40) 11/25 (44) 0.9 Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 6 of 16 Table 2 (continued) Characteristics Hematological disease, ASCT (n = 58) Allo-HCT (n = 65) p value non-SCT (n = 244) Ferritin > 500 µg/mL, (n/evaluable, %) 80/104 (77) 14/21 (67) 25/29 (86) 0.4 D dimer > 500 ng/mL (n/evaluable, %) 127/197 (64) 20/42 (48) 25/46 (54) 0.085 Recovery from COVID-19 (n/evaluable, %) 107/218 (49) 42/57 (74) 33/59 (56) 0.001 PCR negativity documented (n/evaluable, %) 49/131 (37) 15/30 (50) 13/27 (48) 0.01 Median time from diagnosis to negativity, days (range) 20 (4–48) 26 (7–53) 26 (7–43) 0.5 Overall mortality, n (%) 80 (33) 12 (21) 13 (20) 0.1 COVID-19 related mortality, n (%) 76 (31) 10 (17) 12 (18) 0.02 Median time from diagnosis to death, days (range) 7.5 (0–38) 13 (0–51) 8 (0–42) 0.18 Admission to the ICU, n (%) 28 (11) 8 (14) 7 (11) 0.8 ICU mortality rate, n (%) 16 (57) 2 (25) 3 (43) 0.2 SCT: stem cell transplantation; ASCT: autologous stem cell transplantation; allo-SCT: allogeneic hematopoietic stem cell transplantation; HCQ: hydroxi-cloroquine; AZT: azithromycin; lop/rit, lopinavir/ritonavir; ANC: absolute neutrophil count; ALC: absolute lymphocyte count; CRP: C-reactive protein; IL: interleukin; PCR: polymerase chain reaction; ICU: intensive care unit a As suggested in Siddiqi et al. [15] b Refers to dose of IV methylprednisolone or an equivalent dose of another corticosteroid Fig. 1 Number of cases and mortality rate according to the severity of COVID-19 and the date of diagnostic During follow-up, 30 patients (8%) who were asymp- amongst groups (83%, 74% and 72% of non-SCT, ASCT tomatic at the time SARS-CoV-2 infection was made and allo-SCT, respectively, p = 0.2), non-SCT and allo- did not develop symptoms during follow-up (no dif- SCT patients had higher rates of acute respiratory ferences by patient type). Otherwise, the most com- failure (stage IIB) than ASCT (55% vs. 48% vs. 36%, mon clinical features were fever (n = 259, 71%) cough respectively, p = 0.027). (n = 244, 66%), fatigue (n = 192, 53%) and diarrhea Regarding the available laboratory data, non- (n = 81, 22%). COVID-19 was in stage I in 74 cases SCT patients had higher rates of severe neutropenia (20%), stage IIA in 111 patients (30%) and stage IIB in (< 0.5 × 109/mL) and high CRP (> 20 mg/dL) as com- 182 cases (50%). We did not observe significant varia- pared to ASCT and allo-SCT (p < 0.0001), whereas high tions in clinical symptoms among groups. Although IL-6, ferritin and D-dimer levels were similar among pulmonary involvement was not significantly different groups, although these latter laboratory values were available in less than half of the patients (see Table 2). Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 7 of 16 Outcome and mortality Effect of anti‑viral and anti‑cytokine supportive therapy The overall median follow-up after SARS-CoV-2 infec- on day 45 COVID‑19‑related mortality tion was 25 days (range 0-74) for the entire cohort Most patients (n = 289, 79%) received therapy against (see Table 1). At the time of the last follow-up, centers SARS-CoV-2, with azithromycin (n = 156, 42%) and reported a higher proportion of full clinical recovery hidroxycloroquine (n = 147, 40%) being the most com- from COVID-19 in ASCT recipients (74%) as com- mon agents prescribed (details are shown in Table 2). pared to allo-SCT (56%) and non-SCT patients (48%) However, each center established its own treatment algo- (p < 0.0001). The proportion of documented SARS- rithms, which also probably varied on a patient by patient CoV-2 PCR negativity during follow-up screening was basis according to the stage and progression of COVID- also higher in SCT patients (ASCT 50% and allo-SCT 19. Unfortunately, we did not capture the exact date of 48%) as compared to non-SCT (37%) (p = 0.01) with- start and end of these therapeutic interventions. Thus, in out any significant differences in time to negativity order to evaluate the potential effect of therapy, we per- (see Table 2). formed a second multivariate analysis of COVID-19-re- Overall mortality at day 45 after SARS-CoV-2 lated mortality including only the 216 patients (59%) with detection was 29% (n = 105), whereas day 45 very severe disease. Results of these univariate and multi- COVID-19-related mortality was 27% (n = 98). The variate analyses are shown in Table 4. COVID-19-related mortality was higher in non-SCT Treatments which led to lower mortality in multi- (31%) as compared to ASCT (17%) and allo-SCT (18%) variate analysis were (i) the use of azithromycin (OR (p = 0.02). Median time to death was similar among 0.42, 95% CI 0.2–0.89, p = 0.02), and (ii) the use of cor- groups (see Table 2). Overall mortality in patients ticosteroids at doses ≤ 0.5 mg/kg/day (OR 0.31, 95% who were considered suitable candidates for the ICU CI 0.11–0.87, p = 0.02); higher doses of corticosteroids (n = 43) was high (n = 21, 49%) without differences (> 0.5 mg/kg/day) did not show any effect on mortal- between groups. Overall mortality rate according to ity. Of note, the use of hidroxycloroquine did not show the date of COVID-19 diagnosis is shown in Fig. 1. significant improvement in OM. Other variables asso- Overall mortality according to the COVID-19 stage ciated with higher mortality in this subset analysis of in the entire cohort and by patient groups is shown in severely ill patients were; (iii) age > 70 years (OR 2.54, 95% Fig. 2a–d. CI 1.2–5.2, p = 0.011); (iv) uncontrolled hematological disease (OR 3.5, 95% CI 1.6–7.5, p = 0.001); (v) platelet count ≤ 20 × 109/L (OR, 5.66, 95% CI 1.44–22, p = 0.013); Risk factors for severe COVID‑19 (stage IIB) and mortality (vi) platelet count 21–0 × 109/L (OR 3.3, 95% CI 1.2–9.2, Logistic regression univariate and multivariate analy- p = 0.021); (vii) history of arterial hypertension (OR, 2, ses of conditions associated with COVID-19 stage IIB 95% CI 1.3–3.2, p = 0.002); and (viii) CRP > 20 mg/dL and related mortality in all 367 patients are shown in (OR 2.7, 95% CI 1.1–6.5, p = 0.029). Table 3. By multivariate analysis we identified 3 conditions Discussion associated with stage IIB or severe COVID-19; history of We report herein a real-life experience with COVID- hypertension [Odds ratio (OR) 2, 95% confidence interval 19 diagnosed in a large number of Hematology units in (CI) 1.3–3.2, p = 0.02], baseline lymphopenia (< 0.5 × 109/ Spain over a two-month period during the first pandemic mL) (OR 1.7, 95% CI 1.1–2.7, p = 0.015) and baseline wave of the SARS-CoV-2 infection. Our results show an CRP > 20 mg/dL (OR 2.67, 95% CI 1.6–4.3, p < 0.0001). overall mortality rate at day 45 after diagnosis of 29% Finally, 5 conditions were associated with increased (27% COVID-19-related according to the treating physi- COVID-19-related mortality: (i) age > 70 years (OR 2.1, cians). Of note, a lower mortality was seen in recipients 95% CI 1.2–3.8, p = 0.011); (ii) uncontrolled hemato- of a SCT (including allo-SCT recipients) as compared to logical disease (OR 2.9, 95% CI 1.6–5.2, p < 0.0001); (iii) non-SCT patients. ECOG 3–4 (OR, 2.56, 95% CI 1.4–4.7, p = 0.003); (iv) For its simplicity and the ability to classify cases into neutropenia (< 0.5 × 109/L) (OR 2.8, 95% CI 1.3–6.1, moderate or severe cases of pneumonia, we used the p = 0.01); and (v) CRP > 20 mg/dL (OR 3.3, 95% CI 1.7– COVID-19 stages classification, as developed by Siddiqi 6.4, p < 0.0001). Mortality rates progressively increased et al. [15], and as expected found that stage IIB (pneu- according to the presence of 0–1, 2 or > 2 of these 5 RFs, monia with acute respiratory failure) significantly cor- as shown in Fig. 3a. Rising mortality by number of RFs related with higher mortality (shown in different study was also observed in patients with stages IIA-IIB only, in groups in Fig. 1a–d). This easy-to-implement classifica- patients with or without uncontrolled malignancy, and in tion could be of value for future observational studies non-SCT patients or SCT recipients (shown in Fig. 3b–f ). and for the design of future randomized clinical trials. Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 8 of 16 Fig. 2 Day 45 overall mortality. a In the entire cohort, according to the COVID-19 stage, mortality was 8% in patients with stage I, 18% in those with stage IIA and 53% in those who evolved to stage IIB ((p < 0.0001). b Mortality rate in non-SCT patients was 10% vs. 23% vs. 53% in patients with stage I, stage IIA and Stage IIB, respectively (p < 0.0001). c Mortality in autologous SCT recipients was 13%, 11% and 50% in patients with stage I, stage IIA and Stage IIB, respectively (p < 0.09). d Mortality in allo-SCT recipients was 0%, 17% and 47% in patients with stage I, stage IIA and Stage IIB, respectively (p < 0.01) Additionally, we found that hypertension, lymphopenia predictors of mortality in the general population and we and high CRP predicted for the development of stage IIB can thus postulate that with larger patient numbers they COVID-19. Although hypertension and lymphopenia would also have had an impact on survival. On the other were not found to independently increase mortality in hand, higher mortality was linked with age > 70 years, our study, both variables have been shown to be strong uncontrolled hematological malignancy, baseline poor Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 9 of 16 Table 3 Univariate and multivariate analysis of risk factors for stage IIB COVID-19 and COVID-19-related mortality Variables ­ a (n = 367) Log. Regr. COVID-19 Stage II B Log. Regr. COVID-19 Mortality (n = 367) Univariate analysis Multivariate analysis Univariate analysis Multivariate analysis OR (95% CI) p OR (95% CI) p OR (95% CI) p R (95% CI) p value Patient age > 70 years old 2.25 (1.45–3.5) < 0.0001 ns 3.1 (1.9–5) < 0.0001 2.1 (1.2–3.8) 0.011 Patient age ns ns 0–20 1 1 21–70 5.6 (1.2–25) 0.02 0.7 (0.22–2.3) 0.59 >70 11.5 (2.5–52) 0.002 2.3 (0.7–7.5) 0.16 Sex male 1.41 (0.93–2.1) 0.09 ns 0.95 (0.6–1.5) 0.8 Baseline disease ns ns AML 1 1 ALL 0.8 (0.3–2) 0.68 0.6 (0.22–1.67) 0.3 MDS 1.3 (0.5–3.4) 0.5 0.69 (0.25–1.9) 0.47 CMPD 2.7 (1.1–6.8) 0.032 0.6 (0.23–1.5) 0.3 NHL 1.37 (0.7–2.6) 0.3 0.63 (0.3–1.2) 0.3 CLL 2.9 (1.12–7.6) 0.03 0.7 (0.35–1.06) 0.06 Plasmatic cell disorder 0.98 (0.5–1.8) 0.9 0.7 (0.35–1.4) 0.3 AA or auto-immune disorders 0.3 (0.09–1.1) 0.07 0.08 (0.01–0.69) 0.02 Disease status ns CR/PR/not requiring therapy 1 1 Rel/Ref/Prog 1.49 (0.96–2.3) 0.076 3.78 (2.3–6) < 0.0001 2.9 (1.6–5.2) < 0.0001 Procedure ns ns Allo-SCT 1 1 ASCT 0.75 (0.37–1.5) 0.4 1.04 (0.43–2.5) 0.9 Non-SCT 1.57 (0.92–2.6) 0.09 1.95 (1.03–3.7) 0.048 ns Chemotherapy 40 days before COVID-19 1.18 (0.7–1.8) 0.4 ns 1.76 (1.1–2.79) 0.016 ns Disease Dx within 40 days of COVID-19 1.1 (0.6–1.9) 0.7 ns 2.2 (1.24–3.9) 0.007 ns ECOG 3–4 1.8 (1.14–2.98) 0.012 ns 3.7 (2.2–6.1) < 0.0001 2.56 (1.4–4.7) 0.003 Active smoking 1.88 (0.89–3.9) 0.094 ns 1.3 (0.6–2.79) 0.4 Arterial hypertension 2.26 (1.4–3.49) < 0.0001 2 (1.3–3.2) 0.002 2.6 (1.6–4.16) < 0.0001 ns Cardiomyopathy 1.98 (1.1–3.4) 0.015 ns 1.6 (0.9–2.88) 0.089 ns Dyslipidemia 1.6 (1–2.59) 0.049 ns 1.86 (1.1–3) 0.015 ns Place of SARS-CoV-2 infection ns Outpatient 1 1 Inpatient in specialized hospital 1.1 (0.6–1.8) 0.69 1.05 (0.3–3.6) 0.9 ALC < 0.5 × 109/L 1.7 (1.1–2.68) 0.014 1.7 (1.1–2.7) 0.015 2.25 (1.6–3.6) 0.001 ns ANC < 0.5 × 109/L 1.4 (0.7–2.7) 0.27 ns 3.4 (1.8–6.67) < 0.0001 2.8 (1.3–6.1) 0.01 Platelet count (× ­109/L) ns < 20 × ­109/L 1.7 (0.8–3.66) 0.16 4.44 (2.1–9.4) < 0.0001 21–50 × ­109/L 1.18 (0.6–2.26) 0.6 3.6 (1.8–7.05) < 0.0001 > 50 × ­109/L 1 1 CRP > 20 mg/dL 3.1 (1.9–4.9) < 0.0001 2.67 (1.6–4.3) < 0.0001 4 (2.2–7.18) < 0.0001 3.3 (1.7–6.4) < 0.0001 IL-6 > 50 pg/mLb 3.2 (1.38–7.35) 0.007 NT 2.7 (1.1–6.59) 0.028 NT Ferritin ­levelsb NT NT <500 µg/mL 1 1 501–1000 µg/mL 1.18 (0.4–3.2) 1 (0.24–4.1) 0.99 >1001 µg/mL 2.4 (1.1–5.35) 0.03 2.8 (1–7.9) 0.05 D dimer > 500 ng/mLb 1.6 (1.02–2.6) 0.04 NT 1.34 (0.8–2.3) 0.2 NT SCT: stem cell transplantation; ASCT: autologous stem cell transplantation; allo-SCT: allogeneic hematopoietic stem cell transplantation; AML: acute myeloid leukemia; ALL: acute lymphoblastic leukemia; MDS: myelodysplastic syndrome; cMPD: chronic myeloproliferative disease; NHL: non-Hodgkin lymphoma; CLL: chronic lymphocytic leukemia; AA: aplastic anemia; CR: complete remission; PR: partial remission; Rel: relapse; Ref: refractory; Prog: progression; Dx: diagnostic; ANC: absolute neutrophil count; ALC: absolute lymphocyte count; CRP: C-reactive protein; IL: interleukin; ns: not significant; NT: not tested a Stage IIB refers to severe disease, with pulmonary involvement and acute respiratory failure, as suggested in Siddiqi et al. [15] b These variables were not included in the multivariate analyses due to the low number of patients with complete data Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 10 of 16 (See figure on next page.) Fig. 3 COVID-19-related mortality according to the presence of 0-1, 2 and > 2 risk factors. a In the entire cohort. Mortality rate was 18% vs. 35% vs. 54%, respectively (p < 0.0001). b In patients with lower respiratory involvement (stages IIA and IIB), the mortality was 22% vs. 40% vs. 58%, respectively (p < 0.0001). c In patients with uncontrolled hematological malignancy at the time of COVID-19 the mortality was 33% vs. 63% vs. 80%, respectively (p < 0.0001). d In patients with controlled hematological disease at the time of COVID-19 the mortality was 7% vs. 22% vs. 44%, respectively (p < 0.0001). e In stem cell transplant (SCT) recipients the mortality was 17% vs. 34% vs. 56%, respectively (p < 0.0001). f In non-stem cell transplant (SCT) patients the mortality was 19% vs. 34% vs. 54%, respectively (p < 0.0001) performance status, baseline severe neutropenia and a patients before any scheduled treatments, including a high CRP. With these RFs, we built a simple prognostic planned SCT procedure, at least while the incidence in score based on the presence of 0–1, 2 or > 2 RFs, which the community remains high. clearly segregated the day 45 mortality into 3 groups. In contrast with infections by other CARVs in hema- This segregation was obvious in the overall population tological patients [27], the proportion of patients who [low risk (18% mortality), moderate risk (35% mortality) develop LRTD when infected by SARS-CoV-2 appeared and high-risk (54% mortality); Fig. 2a], and also when to be very high (79%), albeit this propensity for causing tested separately in patients with pneumonia (Fig. 2b), pneumonia has been well described in the general popu- in patients with uncontrolled or controlled underly- lation [3]. In fact, the RFs we found for the development ing disease (Figs. 2c, d) and in SCT recipients as well as of severe COVID-19 pneumonia (stage IIB) were similar non-SCT patients (Fig. 2e, f ). The lowest mortality was to those reported in the general population [3]. Hyper- observed in patients with controlled hematological dis- tension [3, 4, 28, 29], lymphopenia [30–33] and high ease and without RFs (7%) in contrast to that observed blood levels of markers of inflammation (including CRP) in patients with uncontrolled hematological disease [34–36] are among these reported RFs. Due to the lack of with > 2 RFs (80%). Of course, as with any risk score data in up to half of our patients, we were unable to ana- obtained form a single study, its validation and improve- lyze the impact of other inflammatory/procoagulant bio- ment in independent patient cohorts is required before markers, such as ferritin, IL-6 and D-dimer on the risk of one can suggest that it should be used to better predict developing severe pneumonia and death, although they the outcome of COVID-19 in patients with hematologi- did show a clear trend in univariate analysis (as shown in cal malignancies. Table 2). Characteristics of COVID-19 symptoms in hematologi- The day 45 overall and COVID-19-related mortality in cal patients share similarities with the general population this series (29% and 27%, respectively) was comparable [20], with fever, dry cough, fatigue and diarrhea being to other series of hematological patients [10–12], appar- the most common initial signs/symptoms of infection. ently higher than patients with solid tumors (13%) [37] Systemic symptoms, however, were more common than and much higher than in the general population (2.3%) URTD symptoms, as has also been reported in the gen- [38]. Somewhat surprising, however, was the lower eral population. Compared to non-immunosuppressed mortality observed in SCT recipients, a patient group patients [3], SARS-CoV-2 shedding in the upper airway usually linked to the highest risk of death from oppor- seemed longer in our series (median of 24 days) with tunistic infections, including those caused by other long-lasting shedding (> 21 days) in a significant pro- CARV. However, patients who receive a SCT, especially portion of studied cases (55%). The immunodeficiency an allo-SCT, are by definition younger and healthier than driven by hematological malignancies and/or their treat- the overall onco-hematological patients. In fact, in our ment may explain a longer time for virus clearance. In cohort we observed that most of conditions associated the general population, low circulating B cell counts with higher overall mortality in multivariate analysis have been correlated with prolonged viral shedding [21]. (i.e. older age, hypertension, uncontrolled hematologi- In spite of the immunosuppressed status, the propor- cal disease and high levels of CRP) were overrepresented tion of asymptomatic patients (8%) in our cohort was in the non-SCT cohort, which may explain in part the not irrelevant. Although our study was not designed to lower mortality observed in SCT recipients. The fact identify asymptomatic SARS-CoV-2 infections in our that all patients with hematological malignancies were patients, it is obvious that these do exist, even if possibly registered in the current study, without the strict inclu- at a lower rate than in the general population (reported sion criteria used in prospective treatment protocols to be approximately 30% of all infections) [22–26]. These and, especially, in clinical trials and for receiving a SCT, observations support the recommendations for screening creates a much more real-life scenario. Indeed, clini- of SARS-CoV-2 infection in asymptomatic hematological cians are well accustomed to seeing elderly patients with Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 11 of 16 Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 12 of 16 Table 4 Univariate and multivariate analysis of risk factors for COVID-19-related mortality in patients with very severe COVID-19 Variables Log. Regr. COVID-19 Mortality in patients with COVID-19 > stage IIA (n = 216) Univariate analysis Multivariate analysis OR (95% CI) % (95%CI) p OR (95% CI) p Patient age > 70 years old 2.5 (1.4–4.3) 0.001 2.54 (1.2–5.2) 0.011 Patient age ns 0–20 1 21–70 0.15 (0.017–1.4) 0.11 > 70 0.45 (0.04–3.9) 0.4 Sex male 1.2 (0.43–1.3) 0.3 Baseline disease ns AML 1 ALL 0.5 (0.13–1.9) 0.31 MDS 0.48 (0.11–1.4) 0.15 CMPD 0.25 (0.08–0.76) 0.014 NHL 0.3 (0.12–0.73) 0.008 CLL 0.11 (0.03–0.41) 0.001 Plasmatic cell disorder 0.5 (0.2–1.3) 0.18 AA or auto-immune disorders 0.09 (0.09–0.89) 0.04 Disease status CR/PR/not requiring therapy 1 Rel/Ref/Prog 4.3 (2.388–7.8) < 0.0001 3.5 (1.6–7.5) 0.001 Procedure Allo-SCT 1 ASCT 1.08 (0.38–3) 0.8 Non-SCT 1.58 (0.74–3.3) 0.23 Chemotherapy 40 days before COVID-19 1.56 (0.9–2.7) 0.11 Disease Dx within 40 days of COVID-19 3.5 (1.56–7.8) 0.002 ns ECOG 3–4 3.1 (1.7–5.76) < 0.0001 ns Active smoking 0.88 (0.37–2.1) 0.8 Arterial hypertension 1.97 (1.14–.4) 0.014 2 (1.3–3.2) 0.002 Cardiomyopathy 1.21 (0.6–2.36) 0.56 Dyslipidemia 1.4 (0.8.–2.6) 0.2 ALC < 0.5 × 109/L 1.7 (1–3) 0.05 ns ANC < 0.5 × 109/L 3.7 (1.58–8.7) 0.002 ns Specific therapy HCQ 0.64 (0.37–1.1) 0.1 ns AZT 0.49 (0.28–0.84) 0.01 0.42 (0.2–0.89) 0.02 HCQ +AZT 0.6 (0.3–1.2) 0.14 lop/rit 0.7 (0.4–1.2) 0.2 Remdesivir 0.18 (0.02–1.6) 0.12 Corticosteroid therapy 0.54 (0.31–0.93) 0.028 ns Corticosteroid doses No 1 1 ≤0.5 mg/kg/dayb 0.44 (0.23–0.83) 0.014 0.31 (0.11–0.87) 0.02 >0.5 mg/kg/dayb 0.54 (0.27–1.06) 0.075 0.75 (0.34–1.6) 0.4 Cytokine inhibitors 0.6 (0.34–1.1) 0.16 Tocilizumab 0.54 (0.28–1.05) 0.073 ns Platelet count (× ­109/L) ≤ 20 × ­109/L 6.4 (2–19) 0.001 5.66 (1.44–22) 0.013 Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 13 of 16 Table 4 (continued) Variables Log. Regr. COVID-19 Mortality in patients with COVID-19 > stage IIA (n = 216) Univariate analysis Multivariate analysis OR (95% CI) % (95%CI) p OR (95% CI) p 21–50 × ­109/L 4.1 (1.7–9.7) 0.001 3.3 (1.2–9.2) 0.021 > 50 × ­109/L 1 1 CRP > 20 mg/dL 2.1 (1.08–4.1) 0.027 2.7 (1.1–6.5) 0.029 IL-6 > 50 pg/mLa 1.8 (0.69–4.7) 0.2 NT Ferritin ­levelsa NT <500 µg/mL 1 501–1000 µg/mL 0.9 (0.2–4.3) 0.9 >1001 µg/mL 2.2 (0.72–7) 0.15 D dimer > 500 ng/mLa 1.39 (0.76–2.6) 0.2 NT SCT: stem cell transplantation; ASCT: autologous stem cell transplantation; allo-SCT: allogeneic hematopoietic stem cell transplantation; AML: acute myeloid leukemia; ALL: acute lymphoblastic leukemia; MDS; myelodysplastic syndrome; cMPD: chronic myeloproliferative disease; NHL: non-Hodgkin lymphoma; CLL: chronic lymphocytic leukemia; AA: aplastic anemia; CR: complete remission; PR: partial remission; Rel: relapse; Ref: refractory; Prog: progression; Dx: diagnostic; ANC: absolute neutrophil count; ALC: absolute lymphocyte count; HCQ: hydroxi-cloroquine; AZT: azithromycin; lop/rit: lopinavir/ritonavir; CRP: C-reactive protein; IL: interleukin; ns: not significant; NT: not tested a These variables were not included in the multivariate analyses due to the low number of patients with complete data b Refers to dose of IV methylprednisolone or an equivalent dose of another corticosteroid many comorbidities who are far from being candidates results; both favorable [40–43] and detrimental effects to the standard-of-care for their AML, MDS, lymphoma, [44, 45] have been found. A preliminary, unpublished myeloma and other diseases, and patient-specific treat- analysis from a large, multicenter, randomized, open- ment decisions must commonly be made. In such real- label trial (RECOVERY study) showed that dexametha- life setting, COVID-19 mortality was mainly driven by sone at 6 mg/day for 10 days reduced the mortality in advanced age, poor performance status, uncontrolled patients with severe COVID-19 (defined as those who disease status (not being at least in a partial remission), required supplemental oxygen) [46]. Our findings are presence of marrow or immune failure (severe neutro- in line with results from this trial, since 6 mg of dexa- penia, and lymphopenia in the univariate analysis) and methasone is equivalent to 40 mgr of oral prednisone having a high baseline and/or COVID-19 induced sys- or 32 mgr of IV methylprednisolone, and the latter is temic inflammatory state (identified in the multivariate within our definition of low-dose steroids (≤ 0.5 mg/kg/ analysis by high CRP, although high levels of IL-6 and day methylprednisolone). However, our results should ferritin showed a strong trend in univariate analysis). In be interpreted with great caution and should not be used contrast, the broad range of hematological malignan- to support the use of either azithromycin or low-dose cies included did not allow us to study the impact of this steroids in patients with hematological malignancies. infection in different diagnoses. Management of COVID-19 is a worldwide research pri- We decided to evaluate the effect of several treatments ority, and the optimal treatment of our patients must be on mortality only in patients who developed very severe guided by the results of these international randomized COVID-19 and found that having received azithromycin clinical trials. (AZT) or low-dose corticosteroids were independently We acknowledge several limitations of this study such associated with lower mortality. Obviously, many clini- as its retrospective nature, the use of different PCR assays cians have been using macrolides to treat COVID-19 and the lack of complete inflammatory markers data in off-label, without any robust evidence of safety or effec- most cases. However, the large number of patients and tiveness. Our results suggest that the use of azithromy- the comparison between non-SCT and SCT recipients cin at least did not have a deleterious impact on survival. should be considered as its strengths, and a starting point In contrast, we found no impact of using hydroxychlo- for future larger and more disease-specific or treatment- roquine (HCQ). To what extend the lack of its benefit specific observational studies. Additionally, our hemato- could be related to potential severe toxicities or insuf- logical COVID-19 database (see Fig. 1) mirrored national ficient antiviral activity remains to be determined [39]. epidemiological data in SARS-CoV-2 during each week Regarding the use of short courses of corticosteroids [47]. This fact suggests a low probability of bias in report- for COVID-19, prior reports have yielded conflicting ing hematological COVID-19 cases in our study. Piñana et al. Exp Hematol Oncol (2020) 9:21 Page 14 of 16 Conclusions División, ICO-Hospital Germans Trias i Pujol, Josep Carreras Research Institute, Badalona, Spain. 31 Pediatric División, Hospital de la Santa Creu i Sant Pau, COVID-19 was severe in patients with hematological Barcelona, Spain. 32 Pediatric División, Hospital niño Jesús, Madrid, Spain. malignancies, and their survival was strongly correlated 33 Hematology División, Hospital Marqués de Valdecilla, Santander, Spain. 34 with the COVID-19 stage and patient and disease-related Hematology División, Hospital Joan XXIII, Tarragona, Spain. 35 Hematopoi‑ etic Stem Cell Transplantation and Cell Therapy Group (GETH), Madrid, Spain. factors [older age, disease status, performance status, 36 Division of Clinical Hematology, Hospital Universitario la Fe de Valencia, immune (neutropenia) status and systemic inflammation Avda Fernando Abril Martorell, 106 CP 46026 Valencia, Spain. (high CRP)]. However, recipients of a SCT did not have a Received: 16 July 2020 Accepted: 18 August 2020 higher mortality. Acknowledgements REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research. We thank the Spanish Society of Hematology (SEHH) References for its support on patients’ recruitment. 1. Guan W, Ni Z, Yu Hu, Liang W, Ou C, He J, Liu L, Shan H, Lei C, Hui DSC, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Authors’ contributions Med. 2020;382:1708–20. JLP, and RM designed the study and drafted the manuscript. All authors 2. Yang X, Yu Y, Xu J, Shu H, Liu H, Wu Y, Zhang L, Yu Z, Fang M, Yu T, Wang participated in the revision of the manuscript. All authors read and approved Y, et al. Clinical course and outcomes of critically ill patients with SARS- the final manuscript. CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. 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Enfermedad por el coronavirus (COVID-19). lished maps and institutional affiliations. 08.06.2020. https​://www.mscbs​.gob.es/profe​siona​les/salud​Publi​ca/ccaye​s/ alert​asAct​ual/nCov-China​/docum​entos​/Actua​lizac​ion_130_COVID​-19.pdf. Ready to submit your research ? Choose BMC and benefit from: • fast, convenient online submission • thorough peer review by experienced researchers in your field • rapid publication on acceptance • support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations • maximum visibility for your research: over 100M website views per year At BMC, research is always in progress. Learn more biomedcentral.com/submissions