# Simultaneous Onset of Haematological Malignancy and COVID: An Epicovideha Survey

Chiara Cattaneo, Jon Salmanton-García, F. Marchesi, Shaimaa El-Ashwah, Federico Itri, Barbora Weinbergerová, Maria Gomes da Silva, Michelina Dargenio, Julio Dávila-Valls, Sonia Martín-Pérez, et al.

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Chiara Cattaneo, Jon Salmanton-García, F. Marchesi, Shaimaa El-Ashwah, Federico Itri, et al. Si-multaneous Onset of Haematological Malignancy and COVID: An Epicovideha Survey. Cancers, 2022, 14 (22), pp.5530. 10.3390/cancers14225530. hal-03888943

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Article

# Simultaneous Onset of Haematological Malignancy and COVID: An Epicovideha Survey

Chiara Cattaneo ¹,† ID, Jon Salmanton-García ²,³,*,† ID, Francesco Marchesi ⁴ ID, Shaimaa El-Ashwah ⁵ ID, Federico Itri ⁶ ID, Barbora Weinbergerová ⁷, Maria Gomes Da Silva ⁸ ID, Michelina Dargenio ⁹, Julio Dávila-Valls ¹⁰ ID, Sonia Martín-Pérez ¹⁰, Francesca Farina ¹¹ ID, Jaap Van Doesum ¹², Toni Valković ¹³,¹⁴,¹⁵, Caroline Besson ¹⁶ ID, Christian Bjørn Poulsen ¹⁷ ID, Alberto López-García ¹⁸ ID, Pavel Žák ¹⁹, Martin Schönlein ²⁰ ID, Klára Piukovics ²¹, Ozren Jaksic ²², Alba Cabirta ²³,²⁴ ID, Natasha Ali ²⁵ ID, Uluhan Sili ²⁶ ID, Nicola Fracchiolla ²⁷ ID, Giulia Dragonetti ²⁸ ID, Tatjana Adžić-Vukičević ²⁹, Monia Marchetti ³⁰ ID, Marina Machado ³¹, Andreas Glenthøj ³², Olimpia Finizio ³³, Fatih Demirkan ³⁴, Ola Blennow ³⁵, Maria Chiara Tisi ³⁶, Ali S. Omrani ³⁷ ID, Milan Navrátil ³⁸ ID, Zdeněk Ráčil ³⁹, Jan Novák ⁴⁰, Gabriele Magliano ⁴¹ ID, Moraima Jiménez ⁴²,⁴³, Carolina Garcia-Vidal ⁴⁴, Nurettin Erben ⁴⁵, Maria Ilaria Del Principe ⁴⁶, Caterina Buquicchio ⁴⁷, Rui Bergantim ⁴⁸ ID, Josip Batinić ⁴⁹,⁵⁰,⁵¹, Murtadha Al-Khabori ⁵² ID, Luisa Verga ⁵³,⁵⁴, Tomáš Szotkowski ⁵⁵, Michail Samarkos ⁵⁶ ID, Irati Ormazabal-Vélez ⁵⁷ ID, Stef Meers ⁵⁸, Johan Maertens ⁵⁹ ID, László Imre Pinczés ⁶⁰ ID, Martin Hoenigl ⁶¹,⁶²,⁶³ ID, L'uboš Drgoňa ⁶⁴, Annarosa Cuccaro ⁶⁵ ID, Yavuz M. Bilgin ⁶⁶, Avinash Aujayeb ⁶⁷ ID, Laman Rahimli ²,³, Stefanie Gräfe ²,³,⁶⁸, Mariarita Sciumè ²⁷ ID, Miloš Mladenović ²⁹,⁶⁹, Gökçe Melis Çolak ²⁶ ID, Maria Vittoria Sacchi ³⁰, Anna Nordlander ³⁵, Caroline Berg Venemyr ³², Michaela Hanáková ³⁹, Nicole García-Poutón ⁴³, Ziad Emarah ⁵ ID, Giovanni Paolo Maria Zambrotta ⁵²,⁵³ ID, Raquel Nunes Rodrigues ⁸, Raul Cordoba ¹⁸, Gustavo-Adolfo Méndez ⁷⁰, Monika M. Biernat ⁷¹, Oliver A. Cornely ²,³,⁷²,⁷³,‡ ID and Livio Pagano ²⁸,⁷⁴,‡ ID

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**Citation:** Cattaneo, C.; Salmanton-García, J.; Marchesi, F.; El-Ashwah, S.; Itri, F.; Weinbergerová, B.; Gomes Da Silva, M.; Dargenio, M.; Dávila-Valls, J.; Martín-Pérez, S.; et al. *Simultaneous Onset of Haematological Malignancy and COVID: An Epicovideha Survey.* *Cancers* **2022**, *14*, 5530. https://doi.org/10.3390/cancers14225530

Academic Editor: Mingyi Chen

Received: 11 October 2022

Accepted: 4 November 2022

Published: 10 November 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

1. Hematology Unit, ASST-Spedali Civili, 25123 Brescia, Italy

2. University of Cologne, Faculty of Medicine, University Hospital Cologne, Translational Research, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), 50931 Cologne, Germany

3. University of Cologne, Faculty of Medicine, University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD) and Excellence Center for Medical Mycology (ECMM), 50931 Cologne, Germany

4. Hematology and Stem Cell Transplant Unit, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy

5. Oncology Center, Mansoura University, Mansoura 35516, Egypt

6. San Luigi Gonzaga Hospital, 10043 Orbassano, Italy

7. Masaryk University and University Hospital Brno—Department of Internal Medicine, Hematology and Oncology, 62500 Brno, Czech Republic

8. Portuguese Institute of Oncology, 1099-023 Lisbon, Portugal

9. Hematology and Stem Cell Transplan Unit, Vito Fazzi, 73100 Lecce, Italy

10. Hospital Nuestra Señora de Sonsoles, 05004 Ávila, Spain

11. IRCCS Ospedale San Raffaele, 20132 Milan, Italy

12. University Medical Center Groningen, 9713 GZ Groningen, The Netherlands

13. University Hospital Centre Rijeka, 51000 Rijeka, Croatia

14. Croatian Cooperative Group for Hematological Diseases (CROHEM), 10000 Zagreb, Croatia

15. Faculty of Medicine, University of Rijeka, 51000 Rijeka, Croatia

16. Centre Hospitalier de Versailles, Le Chesnay, Université Paris-Saclay, UVSQ, Inserm, Équipe "Exposome et Hérédité", CESP, 94800 Villejuif, France

17. Zealand University Hospital, 4000 Roskilde, Denmark

18. Fundacion Jimenez Diaz University Hospital, Health Research Institute IIS-FJD, 28040 Madrid, Spain

19. University Hospital Hradec Králové, 50005 Hradec Králové, Czech Republic

20. Department of Oncology, Hematology and Bone Marrow Transplantation with Section of Pneumology, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany

21. Department of Internal Medicine, South Division, Faculty of Medicine University of Szeged, 6720 Szeged, Hungary

22. University Hospital Dubrava, 10000 Zagreb, Croatia

23. Department of Hematology, Vall d'Hebron Hospital Universitari, Experimental Hematology, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, 08193 Barcelona, Spain

24. Departament de Medicina, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain

25. Aga Khan University, 74000 Karachi, Pakistan
26 Department of Infectious Diseases and Clinical Microbiology, School of Medicine, Marmara University, 34854 Istanbul, Turkey

27 Hematology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy

28 Hematology Unit, Fondazione Policlinico Universitario Agostino Gemelli—IRCCS, 00168 Rome, Italy

29 COVID Hospital “Batajnica”, 11000 Belgrade, Serbia

30 Azienda Ospedaliera Nazionale SS. Antonio e Biagio e Cesare Arrigo, 15121 Alessandria, Italy

31 Clinical Microbiology and Infectious Diseases Department, Hospital General Universitario Gregorio Marañón, 28009 Madrid, Spain

32 Department of Hematology, Copenhagen University Hospital—Rigshospitalet, DK-2100 Copenhagen, Denmark

33 UOC Hematology, AORN Cardarelli, 80131 Naples, Italy

34 Dokuz Eylül University, Division of Hematology, 35340 Izmir, Turkey

35 Department of Infectious Diseases, Karolinska University Hospital, 17176 Stockholm, Sweden

36 Ospedale San Bortolo, 36100 Vicenza, Italy

37 Communicable Disease Center, Hamad Medical Corporation, Doha 3050, Qatar

38 University Hospital Ostrava, 70852 Ostrava, Czech Republic

39 Institute of Hematology and Blood Transfusion, 12800 Prague, Czech Republic

40 Department of Hematology, University Hospital Kralovske Vinohrady and Third Faculty of Medicine, Charles University, 12808 Prague, Czech Republic

41 ASST Grande Ospedale Metropolitano Niguarda, 20162 Milan, Italy

42 Department of Hematology, University Hospital Vall d'Hebron, Experimental Hematology, 08035 Barcelona, Spain

43 Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, 08035 Barcelona, Spain

44 Department of Infectious Diseases, Hospital Clinic de Barcelona, University of Barcelona, IDIBAPS, 08035 Barcelona, Spain

45 Department of Infectious Diseases and Clinical Microbiology, Faculty of Medicine Eskisehir Osmangazi University, 26040 Eskisehir, Turkey

46 Hematology, Department of Biomedicine and Prevention, University of Rome Tor Vergata, 00133 Rome, Italy

47 Ematologia Con Trapianto, Ospedale Dimiccoli Barletta, 70051 Barletta, Italy

48 Centro Hospitalar e Universitário São João, 4200-319 Porto, Portugal

49 University Hospital Centre Zagreb, 10000 Zagreb, Croatia

50 Croatian Cooperative Group for Hematological Diseases (KROHEM), 10000 Zagreb, Croatia

51 School of Medicine University of Zagreb, 10000 Zagreb, Croatia

52 Sultan Qaboos University Hospital, Muscat 123, Oman

53 Azienda Ospedaliera San Gerardo—Monza, 20900 Monza, Italy

54 Università Milano-Bicocca, 20126 Milan, Italy

55 University Hospital Olomouc, 77900 Olomouc, Czech Republic

56 Laikon Hospital, 11527 Athens, Greece

57 Hospital Universitario de Navarra, 31008 Iruña-Pamplona, Spain

58 AZ KLINA, 2930 Brasschaat, Belgium

59 KU Leuven, 3000 Leuven, Belgium

60 Division of Hematology, Department of Internal Medicine, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary

61 Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California San Diego, San Diego, CA 92093, USA

62 Clinical and Translational Fungal-Working Group, University of California San Diego, La Jolla, CA 92093, USA

63 Division of Infectious Diseases, Department of Internal Medicine, Medical University of Graz, A-8036 Graz, Austria

64 Department of Oncohematology, Comenius University and National Cancer Institute, 81499 Bratislava, Slovakia

65 Hematology Unit, Center for Translational Medicine, Azienda USL Toscana NordOvest, 55100 Livorno, Italy

66 Department of Internal Medicine, ADRZ, 4462 RA Goes, The Netherlands

67 Northumbria Healthcare, Newcastle NE29 8NH, UK

68 Universitätsklinikum Hamburg Eppendorf, 20251 Hamburg, Germany

69 Clinic for Orthopedic Surgery and Traumatology, University Clinical Center of Serbia, 11000 Belgrade, Serbia

70 Hospital Escuela de Agudos Dr. Ramón Madariaga, Posadas 3736, Argentina

71 Department of Haematology, Blood Neoplasms, and Bone Marrow Transplantation, Wroclaw Medical University, 50-425 Wroclaw, Poland

72 University of Cologne, Faculty of Medicine, University Hospital Cologne, Clinical Trials Centre Cologne (ZKS Köln), 50931 Cologne, Germany

73 German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, 50931 Cologne, Germany
74 Hematology Unit, Università Cattolica del Sacro Cuore, 86100 Rome, Italy

* Correspondence: jon.salmanton-garcia@uk-koeln.de; Tel.: +49-(0)221-478-32290

† These authors contributed equally to this work.

‡ These authors contributed equally to this work.

**Simple Summary:** Patients with simultaneous diagnosis of haematological malignancies (HM) and COVID-19 are an even greater challenge for hematologists. To better clarify their outcome, we describe the clinical features and outcome of a cohort of 450 patients with simultaneous diagnosis of HM and COVID-19 registered in the EPICOVIDEHA registry between March 2020 to February 2022. Overall, 343 (76.2%) patients received treatment for HM, and an overall response rate was observed in 140 (40.8%) patients after the first line of treatment. Thirty-day mortality was significantly higher in patients not receiving HM treatment (42.1%) than in those receiving treatment (27.4%, *p* = 0.004). Statistical analysis showed that, together with age, severe/critical COVID-19, ≥2 comorbidities, lack of HM treatment was an independent risk factors for mortality. These observations suggest the importance of HM treatment in these patients; therefore, it should be delivered as soon as possible for patients requiring immediate therapy.

**Abstract:** Background: The outcome of patients with simultaneous diagnosis of haematological malignancies (HM) and COVID-19 is unknown and there are no specific treatment guidelines. Methods: We describe the clinical features and outcome of a cohort of 450 patients with simultaneous diagnosis of HM and COVID-19 registered in the EPICOVIDEHA registry between March 2020 to February 2022. Results: Acute leukaemia and lymphoma were the most frequent HM (35.8% and 35.1%, respectively). Overall, 343 (76.2%) patients received treatment for HM, which was delayed for longer than one month since diagnosis in 57 (16.6%). An overall response rate was observed in 140 (40.8%) patients after the first line of treatment. After a median follow-up of 35 days, overall mortality was 177/450 (39.3%); 30-day mortality was significantly higher in patients not receiving HM treatment (42.1%) than in those receiving treatment (27.4%, *p* = 0.004), either before and/or after COVID-19, or compared to patients receiving HM treatment at least after COVID-19 (15.2%, *p* < 0.001). Age, severe/critical COVID-19, ≥2 comorbidities, and lack of HM treatment were independent risk factors for mortality, whereas a lymphocyte count >500/mcl at COVID-19 onset was protective. Conclusions: HM treatment should be delivered as soon as possible for patients with simultaneous diagnosis of COVID-19 and HM requiring immediate therapy.

**Keywords:** haematological malignancy onset; COVID-19; treatment; outcome; prognostic factors

# 1. Introduction

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was declared a global pandemic by the World Health Organization (WHO) in March 2020. Since then, many reports demonstrated high morbidity and mortality in haematological patients with coronavirus disease 2019 (COVID-19), partly driven by uncontrolled haematological malignancy (HM), which can affect the severity of COVID-19 [1–3].

However, to date, few data are available about the impact of starting early versus delayed specific HM treatment as well as the outcome of patients with simultaneous onset of HM and COVID-19. Some recommendations from expert panels have raised concern regarding the management of specific HM, including acute leukaemia (AL), multiple myeloma (MM) and hairy cell leukaemia (HCL), during the pandemic [4–8]. In these recommendations, few suggestions apply to patients with simultaneous HM and COVID-19 diagnosis, and the advice is usually to delay, when possible, the start of HM therapy. Indeed, the severity of the COVID-19 clinical picture might make any HM specific therapeutic approach impossible, but some cases of simultaneous diagnosis of COVID-19 and AL requiring immediate treatment have been reported, suggesting that the HM therapeutic approach may be possible even with an active infection [9,10]. Other researchers have indi-
cated that an intensity-reduced approach may be helpful, particularly in the management
of specific HM, such as acute myeloid leukaemia (AML) [11].

Specific data on a large cohort of patients with simultaneous onset of HM and COVID-19 with long-term follow-up are still lacking, and there are no evidence-based algorithms to guide clinicians in the selection of the best therapeutic approach and timing, particularly for patients requiring urgent antineoplastic treatment.

Hereby, we aimed to assess the overall survival (OS) of patients with simultaneous onset of HM and COVID-19 as primary endpoint of the study. In addition, we intended to determine: (1) the HM response rate of patients with simultaneous onset of HM and COVID-19; (2) the rate of patients receiving specific treatment for HM during the acute phase of COVID-19; (3) the prognostic factors in patients with simultaneous onset of HM and COVID-19; (4) the time interval between HM diagnosis and initiation of therapy; (5) the safety of specific haematological treatments during COVID-19.

## 2. Materials and Methods

We have conducted an observational multicentre analysis of patients with HM who developed COVID-19 between March 2020 and February 2022. Data were collected from the EPICOVIDEHA registry. EPICOVIDEHA (www.clinicaltrials.gov; NCT04733729) is an international open web-based registry for patients with HM infected with SARS-CoV-2. This registry was centrally approved by the local ethics committee of the Fondazione Policlinico Universitario Agostino Gemelli-IRCCS, Università Cattolica del Sacro Cuore of Rome, Italy (Study ID: 3226). Additionally, if applicable, the respective local ethics committee of each participating institution might have approved the EPICOVIDEHA. EPICOVIDEHA's methods have been described elsewhere [12]. The electronic case report form (eCRF) is accessible online at www.clinicalsurveys.net (EFS Summer 2021, TIVIAN, Cologne, Germany, Accessed on 23 February 2022). Each documented patient was reviewed and validated by experts in infectious diseases and haematology. Inclusion criteria were described as follows: (a) new diagnosis of HM within 33 days before or 3 days after SARS-CoV-2 infection diagnosis, (b) adult patients ≥ 18 years old, and (c) laboratory-based diagnosis of SARS-CoV-2 infection.

Data on patient baseline conditions pre-COVID-19 (i.e., age, sex, factors predisposing for COVID-19, COVID-19 vaccination status), HM clinical management (i.e., type of treatment received and any delay), COVID-19 severity, and outcome (i.e., mortality, attributable mortality [assessed by the medical team in charge of the patient], last day of follow-up) were collected. COVID-19 severity was graded according to international standards as previously described (asymptomatic: no clinical signs or symptoms; mild: non-pneumonia and mild pneumonia; severe: dyspnoea, respiratory frequency ≥ 30 breaths per min, $SpO_2 \le 93\%$, $PaO_2/FiO_2 < 300$, or lung infiltrates > 50%); critical: patients admitted to intensive care for respiratory failure, septic shock, or multiple organ dysfunction or failure) [1] HM treatment was considered delayed if delivered more than one month after the HM diagnosis. Overall response rate for HM included complete remission and partial remission [13]. Neutropenia and lymphopenia were reported based on grade 3 and 4 values according to Common Terminology Criteria for Adverse Events (CTCAE) v6.0 [14]. The observation period was split into four intervals (1st: March 2020–September 2020; 2nd: October 2020–February 2021; 3rd: March 2021–November 2021; 4th: December 2021–February 2022), according to pandemic waves and to vaccine availability.

No a priori sample size calculation was performed for this analysis. Categorical variables are described using frequencies and percentages, whereas continuous variables using median, interquartile range (IQR) and absolute range. A Cox regression hazard model was designed and run with variables suspected to play a role in the mortality of patients with COVID-19, as previously described [11]. A multivariable Cox regression model was calculated with the Wald backward method, including only the variables statistically significant in the univariable model. Mortality was analysed using Kaplan-Meier survival plots. Log-rank test was used to compare the survival probability of the patients included
in the different plots. A *p*-value ≤ 0.05 was found statistically significant. SPSSv27.0 was employed for statistical analyses (SPSS, IBM Corp., Chicago, IL, USA).

## 3. Results

### 3.1. Characteristics of Patients

From March 2020 to February 2022, 450 patients with simultaneous onset of HM and COVID-19 have been reported in the EPICOVIDEHA registry. Of these, 118 (26.2%) patients were diagnosed with COVID-19 between March and September 2020, 167 (37.1%) between October 2020 and February 2021, 71 (15.8%) between March and November 2021, and 94 (20.9%) between December 2021 and February 2022.

Patient characteristics are summarized in Table 1. Males were predominant (n = 264, 58.7%), with a median age of 65 years (IQR: 53 to 68). At least one comorbidity was reported in 140 (62.7%) patients, and two in 142 (31.6%). AL, particularly AML, were the most common HM (AL n = 161, 35.8%; AML n = 129, 28.7%), together with non-Hodgkin Lymphoma (NHL), mainly aggressive (NHL n = 142, 31.6%; aggressive NHL n = 91, 20.2%). The median time between HM and COVID-19 diagnosis was 11 days (IQR: −22 to −2) before COVID-19. At COVID-19 diagnosis, neutropenia was present in 97 (21.5%) patients (grade 4 in n = 69, 15.5% with less than 500 neutrophils/mm³), and lymphopenia in 101 (22.4%) patients. Secondary infections were reported in 63 (14%) of patients; of these, 6 (9.5%) were invasive possible or probable mould diseases. One fifth of the patients (n = 89, 19.8%) received at least one vaccine dose before COVID-19 diagnosis, with 29 (6.4%) being fully vaccinated; they were recorded all in the 3rd and 4th intervals. In 70 cases patients were vaccinated with mRNA based vaccines. COVID-19 was severe or critical in 286 (63.6%) patients. Most of the patients were admitted to hospital (n = 380, 84.4%); a specific treatment for COVID-19 was delivered in 173 (38.4%) patients, as reported in Table 1. In Table S1 COVID-19 directed antivirals and monoclonal antibodies are reported.

<table><caption>**Table 1.** Characteristics of patients with simultaneous onset of haematological malignancy and COVID-19.</caption><thead><tr><th></th><th>n</th><th>%</th></tr></thead><tbody><tr><td>Sex</td><td></td><td></td></tr><tr><td>Female</td><td>186</td><td>41.3%</td></tr><tr><td>Male</td><td>264</td><td>58.7%</td></tr><tr><td>Age, median (IQR) [absolute range]</td><td>65 (53 to 75) [18 to 95]</td><td></td></tr><tr><td>18–25 years old</td><td>15</td><td>3.3%</td></tr><tr><td>26–50 years old</td><td>84</td><td>18.7%</td></tr><tr><td>51–69 years old</td><td>174</td><td>38.7%</td></tr><tr><td>≥70 years old</td><td>177</td><td>39.3%</td></tr><tr><td>Comorbidities before COVID-19</td><td></td><td></td></tr><tr><td>No comorbidities</td><td>168</td><td>37.3%</td></tr><tr><td>1 comorbidity</td><td>140</td><td>31.1%</td></tr><tr><td>2 comorbidities</td><td>81</td><td>18%</td></tr><tr><td>3 or more comorbidities</td><td>61</td><td>13.6%</td></tr><tr><td>Chronic cardiopathy</td><td>156</td><td>34.7%</td></tr><tr><td>Chronic pulmonary disease</td><td>61</td><td>13.6%</td></tr><tr><td>Diabetes mellitus</td><td>77</td><td>17.1%</td></tr><tr><td>Liver disease</td><td>18</td><td>4%</td></tr><tr><td>Obesity</td><td>43</td><td>9.6%</td></tr><tr><td>Renal impairment</td><td>43</td><td>9.6%</td></tr><tr><td>Smoking history</td><td>52</td><td>11.6%</td></tr><tr><td>No risk factor identified</td><td>168</td><td>37.3%</td></tr><tr><td>Baseline malignancy</td><td></td><td></td></tr><tr><td>Days between malignancy diagnosis and COVID-19 diagnosis, median (IQR) [absolute range]</td><td>−11 (−21 to −2) [−33 to 3]</td><td></td></tr></tbody></table>
<table><caption>**Table 1.** *Cont.*</caption><thead><tr><th></th><th>n</th><th>%</th></tr></thead><tbody><tr><td>Acute lymphoid leukaemia</td><td>32</td><td>7.1%</td></tr><tr><td>Chronic lymphoid leukaemia</td><td>27</td><td>6%</td></tr><tr><td>Acute myeloid leukaemia</td><td>129</td><td>28.7%</td></tr><tr><td>Chronic myeloid leukaemia</td><td>9</td><td>2%</td></tr><tr><td>Hodgkin lymphoma</td><td>16</td><td>3.6%</td></tr><tr><td>Non-Hodgkin lymphoma</td><td>142</td><td>31.6%</td></tr><tr><td>Indolent</td><td>42</td><td>9.3%</td></tr><tr><td>Aggressive</td><td>91</td><td>20.2%</td></tr><tr><td>Unknown</td><td>7</td><td>1.6%</td></tr><tr><td>Essential thrombocythemia</td><td>2</td><td>0.4%</td></tr><tr><td>Multiple myeloma</td><td>55</td><td>12.2%</td></tr><tr><td>Myelodysplastic syndrome</td><td>25</td><td>5.6%</td></tr><tr><td>Myelofibrosis</td><td>3</td><td>0.7%</td></tr><tr><td>Hairy cell leukaemia</td><td>10</td><td>2.2%</td></tr><tr><td>Neutrophils at COVID-19 diagnosis</td><td></td><td></td></tr><tr><td>≤500</td><td>69</td><td>15.3%</td></tr><tr><td>501–999</td><td>28</td><td>6.2%</td></tr><tr><td>≥1000</td><td>307</td><td>68.2%</td></tr><tr><td>Lymphocytes at COVID-19 diagnosis</td><td></td><td></td></tr><tr><td>≤200</td><td>47</td><td>10.4%</td></tr><tr><td>201–499</td><td>54</td><td>12%</td></tr><tr><td>≥500</td><td>315</td><td>70%</td></tr><tr><td>COVID-19 infection</td><td></td><td></td></tr><tr><td>Asymptomatic</td><td>106</td><td>23.6%</td></tr><tr><td>Mild infection</td><td>58</td><td>12.9%</td></tr><tr><td>Severe infection</td><td>170</td><td>37.8%</td></tr><tr><td>Critical infection</td><td>116</td><td>25.8%</td></tr><tr><td>COVID-19 symptoms at infection onset</td><td></td><td></td></tr><tr><td>Pulmonary</td><td>151</td><td>33.6%</td></tr><tr><td>Pulmonary + extrapulmonary</td><td>106</td><td>23.6%</td></tr><tr><td>Extrapulmonary</td><td>66</td><td>14.7%</td></tr><tr><td>Screening</td><td>127</td><td>28.2%</td></tr><tr><td>COVID-19 vaccination</td><td></td><td></td></tr><tr><td>Not vaccinated</td><td>360</td><td>80%</td></tr><tr><td>One dose</td><td>15</td><td>3.3%</td></tr><tr><td>Two doses</td><td>46</td><td>10.2%</td></tr><tr><td>Three doses</td><td>29</td><td>6.4%</td></tr><tr><td>COVID-19 treatment</td><td></td><td></td></tr><tr><td>No specific treatment reported</td><td>277</td><td>61.6%</td></tr><tr><td>Antivirals + monoclonal antibodies ± corticosteroids ± plasma</td><td>8</td><td>1.8%</td></tr><tr><td>Antivirals ± corticosteroids ± plasma</td><td>52</td><td>11.6%</td></tr><tr><td>Corticosteroids</td><td>72</td><td>16%</td></tr><tr><td>Monoclonal antibodies ± plasma ± corticosteroids</td><td>31</td><td>6.9%</td></tr><tr><td>Plasma ± corticosteroids</td><td>10</td><td>2.2%</td></tr><tr><td>Stay during COVID-19 episode</td><td></td><td></td></tr><tr><td>Hospital</td><td>380</td><td>84.4%</td></tr><tr><td>Days of the stay in ICU, median (IQR) [absolute range]</td><td>15 (7 to 28) [1 to 150]</td><td></td></tr><tr><td>ICU</td><td>116</td><td>25.8%</td></tr><tr><td>Days of the stay in ICU, median (IQR) [absolute range]</td><td>8 (4 to 20) [1 to 56]</td><td></td></tr><tr><td>Invasive mechanical ventilation</td><td>74</td><td>16.4%</td></tr><tr><td>Non-invasive mechanical ventilation</td><td>42</td><td>9.3%</td></tr><tr><td>Home</td><td>93</td><td>20.7%</td></tr></tbody></table>

Negative days indicate days before COVID-19 diagnosis. Positive days indicate days after COVID-19 diagnosis. Day of COVID-19 diagnosis is set as day 0. Asymptomatic: no clinical signs or symptoms; mild: non-pneumonia and mild pneumonia; severe: dyspnea, respiratory frequency ≥ 30 breaths per min, SpO₂ ≤ 93%, PaO₂/FiO₂ < 300, or lung infiltrates > 50%; critical: patients admitted in intensive care for respiratory failure, septic shock, or multiple organ dysfunction or failure. COVID-19, coronavirus disease 2019; ICU, intensive care unit; IQR, interquartile range.
## 3.2. HM Treatment

Overall, at least 343 (76.2%) patients with simultaneous COVID-19 and HM received treatment for HM, either before and/or after COVID-19 diagnosis. HM treatment was delivered at least before COVID-19 diagnosis in 227/343 (66.2%) patients, with a median time between HM diagnosis and start of HM treatment of 7 days (IQR: 3 to 19). HM treatment was started only after COVID-19 in 116 (33.8%) patients. Only 41 (5.6%) patients were treated from day 32 of COVID-19 onwards. Forty-five (10.0%) patients were treated only with palliative care, before or after COVID-19. One-hundred and seven (23.7%) patients did not receive any treatment until the last day of follow-up. In seven (1.5%) cases no information about HM treatment was provided.

HM treatment was delayed beyond one month since HM diagnosis in 57 (17.2%) patients. Treatment delay was rarer for AL (AML: 9/103, 8.7%, acute lymphoblastic leukaemia, ALL: 2/27, 9.1%) and MM (5/41, 12.2%) and more frequent in NHL (27/112, 21.7%), both aggressive (21.9%) and indolent (20.8%), myelodysplastic/myeloproliferative syndromes (MDS/MPS) (5/22, 22.7%), chronic lymphoproliferative disorders (CLD) (4/11, 36.4%) and Hodgkin lymphoma (HL) (7/14, 50%). In Supplementary Table S2 all the treatments for HM delivered before and after COVID-19 diagnosis are detailed.

Table 2 summarizes the clinical characteristics of patients by HM treatment. Patients receiving HM treatment (either before or after COVID-19) were more often female. AML or lymphoma patients were more frequently treated than those with CLD or MDS/MPS. The number of comorbidities and COVID-19 severity, as well as vaccination status and specific treatment for COVID-19 did not differ significantly in treated and untreated patients. The largest number of HM treated patients was observed in the second period (October 2020–February 2021). Thirty-day mortality was significantly lower in treated patients for HM as compared to those receiving no HM treatment.

<table><caption>**Table 2.** Clinical characteristics of treated and not treated patients.</caption><thead><tr><th rowspan="2"></th><th colspan="2">No HM Tx at All</th><th colspan="2">HM Tx at Least after COVID-19 dx</th><th rowspan="2">p Value</th><th colspan="2">No HM Tx at All</th><th colspan="2">HM Tx</th><th rowspan="2">p Value</th></tr><tr><th>n</th><th>%</th><th>n</th><th>%</th><th>n</th><th>%</th><th>n</th><th>%</th></tr></thead><tbody><tr><td>Sex</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Female</td><td>34</td><td>31.8%</td><td>96</td><td>44.2%</td><td>0.031</td><td>34</td><td>31.8%</td><td>152</td><td>44.3%</td><td>0.021</td></tr><tr><td>Male</td><td>73</td><td>68.2%</td><td>121</td><td>55.8%</td><td></td><td>73</td><td>68.2%</td><td>191</td><td>55.7%</td><td></td></tr><tr><td>Age, median (IQR) [absolute range]</td><td>68 (56–79) [24–92]</td><td></td><td>61 (47–72) [18–95]</td><td></td><td>&lt;0.001</td><td>68 (56–79) [24–92]</td><td></td><td>64 (50–74) [18–95]</td><td></td><td>0.003</td></tr><tr><td>Comorbidities Before COVID-19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No comorbidities</td><td>37</td><td>34.6%</td><td>86</td><td>39.6%</td><td>0.031</td><td>37</td><td>34.6%</td><td>131</td><td>38.2%</td><td>0.093</td></tr><tr><td>1 comorbidity</td><td>29</td><td>27.1%</td><td>71</td><td>32.7%</td><td></td><td>29</td><td>27.1%</td><td>111</td><td>32.4%</td><td></td></tr><tr><td>2 comorbidities</td><td>28</td><td>26.2%</td><td>28</td><td>12.9%</td><td></td><td>28</td><td>26.2%</td><td>53</td><td>15.5%</td><td></td></tr><tr><td>3 or more comorbidities</td><td>13</td><td>12.1%</td><td>32</td><td>14.7%</td><td></td><td>13</td><td>12.1%</td><td>48</td><td>14.0%</td><td></td></tr><tr><td>Baseline malignancy</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>ALL</td><td>4</td><td>3.7%</td><td>19</td><td>8.8%</td><td></td><td>4</td><td>3.7%</td><td>28</td><td>8.2%</td><td></td></tr><tr><td>AML</td><td>17</td><td>15.9%</td><td>62</td><td>28.6%</td><td></td><td>17</td><td>15.9%</td><td>112</td><td>32.7%</td><td></td></tr><tr><td>Lymphoma</td><td>32</td><td>29.9%</td><td>82</td><td>37.8%</td><td>&lt;0.001</td><td>32</td><td>29.9%</td><td>124</td><td>36.2%</td><td>&lt;0.001</td></tr><tr><td>CLD</td><td>26</td><td>24.3%</td><td>9</td><td>4.1%</td><td></td><td>26</td><td>24.3%</td><td>13</td><td>3.8%</td><td></td></tr><tr><td>MM</td><td>12</td><td>11.2%</td><td>29</td><td>13.4%</td><td></td><td>12</td><td>11.2%</td><td>43</td><td>12.5%</td><td></td></tr><tr><td>MDS/MPS</td><td>16</td><td>15.0%</td><td>16</td><td>7.4%</td><td></td><td>16</td><td>15.0%</td><td>23</td><td>6.7%</td><td></td></tr><tr><td>Anti-SARS-CoV-2 vaccination</td><td>26</td><td>24.3%</td><td>38</td><td>17.5%</td><td>0.149</td><td>26</td><td>24.3%</td><td>64</td><td>18.7%</td><td>0.203</td></tr><tr><td>COVID-19 severity</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Asymptomatic</td><td>20</td><td>18.7%</td><td>64</td><td>29.5%</td><td></td><td>20</td><td>18.7%</td><td>86</td><td>25.1%</td><td></td></tr><tr><td>Mild infection</td><td>11</td><td>10.3%</td><td>27</td><td>12.4%</td><td>0.019</td><td>11</td><td>10.3%</td><td>47</td><td>13.7%</td><td>0.092</td></tr><tr><td>Severe infection</td><td>39</td><td>36.4%</td><td>83</td><td>38.2%</td><td></td><td>39</td><td>36.4%</td><td>131</td><td>38.2%</td><td></td></tr><tr><td>Critical infection</td><td>37</td><td>34.6%</td><td>43</td><td>19.8%</td><td></td><td>37</td><td>34.6%</td><td>79</td><td>23.0%</td><td></td></tr><tr><td>COVID-19 diagnostic period</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>March 2020–September 2020</td><td>27</td><td>25.2%</td><td>56</td><td>25.8%</td><td></td><td>27</td><td>25.2%</td><td>91</td><td>26.5%</td><td></td></tr><tr><td>October 2020–February 2021</td><td>25</td><td>23.4%</td><td>99</td><td>45.6%</td><td>&lt;0.001</td><td>25</td><td>23.4%</td><td>142</td><td>41.4%</td><td>0.001</td></tr><tr><td>March 2021–November 2021</td><td>24</td><td>22.4%</td><td>29</td><td>13.4%</td><td></td><td>24</td><td>22.4%</td><td>47</td><td>13.7%</td><td></td></tr><tr><td>December 2021–February 2022</td><td>31</td><td>29.0%</td><td>33</td><td>15.2%</td><td></td><td>31</td><td>29.0%</td><td>63</td><td>18.4%</td><td></td></tr></tbody></table>
<table><caption>**Table 2.** *Cont.*</caption><thead><tr><th rowspan="2"></th><th colspan="2">No HM Tx at All</th><th colspan="2">HM Tx at Least after COVID-19 dx</th><th rowspan="2">p Value</th><th colspan="2">No HM Tx at All</th><th colspan="2">HM Tx</th><th rowspan="2">p Value</th></tr><tr><th>n</th><th>%</th><th>n</th><th>%</th><th>n</th><th>%</th><th>n</th><th>%</th></tr></thead><tbody><tr><td>Any COVID-19 treatment</td><td>46</td><td>43.0%</td><td>66</td><td>30.4%</td><td>0.025</td><td>46</td><td>43.0%</td><td>127</td><td>37.0%</td><td>0.268</td></tr><tr><td>Day-30 mortality</td><td>45</td><td>42.1%</td><td>33</td><td>15.2%</td><td>&lt;0.001</td><td>45</td><td>42.1%</td><td>94</td><td>27.4%</td><td>0.004</td></tr></tbody></table>

ALL, acute lymphoid leukaemia; AML, acute myeloid leukaemia; CLD, chronic lymphoproliferative disorder; COVID-19, coronavirus disease 2019; Dx, diagnosis; HM, haematological malignancy; IQR, interquartile range; MDS, myelodysplastic syndrome; MM, multiple myeloma; MPS, myeloproliferative syndrome; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; Tx, treatment.

### 3.3. *Patient Outcome*

Among the 343 treated patients, HM treatment overall response rate was 40.8% (140/343 patients) after the first line of treatment; 100 (29.2%) patients had complete remission. Chemotherapy-induced neutropenia occurred in 155 (45.2%) patients and secondary infections were reported in 85 (24.8%).

After a median follow-up of 35 days (IQR: 12-168) since COVID-19 diagnosis, 177/450 (39.3%) had died. Thirty-day mortality was 139/450 (30.9%) for the whole cohort. It was higher in AML (57/129, 44.2%) and in MM patients (21/55, 38.2%) and lower in lymphoma (39/156, 25%), in MDS/MPS (9/39, 23.1%), in ALL (6/32, 18.7%) and in CLD (7/39, 17.9%) patients (overall survival probability reported in Figure 1a,b). Thirty-day mortality was similar in indolent and aggressive NHL (respectively: 12/42, 28.6% and 26/91, 28.6%), regardless of different proportions of HM treatment received (24/42, 57.1% and 81/91, 90.1%, respectively). In 151 (85.3%) patients COVID-19 was responsible for death; however, in 78 (44%) patients the main reason for death was COVID-19, in 73 (41.2%) COVID-19 and HM and in 26 (5.8%) HM. Thirty-day mortality was significantly higher in patients not receiving HM treatment (42.1%) than in those receiving treatment (27.4%, *p* = 0.004), either before and/or after COVID-19, or compared to patients receiving HM treatment at least after COVID-19 (15.2%, *p* < 0.001). The lowest mortality (12.1%) was observed in patients receiving treatment only after COVID-19. Mortality rates by timing of HM treatment are showed in Table S3.

<figure><img src="image_6.png" /><figcaption>**Figure 1.** *Cont.*</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>**Figure 1.** Overall survival probability. (a) Cohort. (b) Patients by malignancy.</figcaption></figure>

Overall, patients treated for HM showed a higher survival probability at 30 days follow-up as compared to those untreated (*p* < 0.001) (Figure 2). Higher survival probability in those who were treated was also found in patients with AML (*p* < 0.001), lymphoma (*p* < 0.001), MDS/MPS (*p* = 0.01), and MM (*p* = 0.052) (Figure S1).

### 3.4. Risk Factors for Mortality

Increasing age, AML diagnosis, pre-existing comorbidities, critical COVID-19, and no HM treatment were observed as risk factors for mortality in the univariable analysis, whereas simultaneous HM and COVID-19 diagnosis in the 2nd and 4th period, a lymphocyte count > 500/mcl at COVID-19 onset, administration of at least conventional chemotherapy, administration of at least immunotherapy before COVID-19, HM treatment after COVID-19, and anti-SARS-CoV-2 monoclonal antibody administration were protective. At multivariable analysis, age, report of at least two comorbidities, severe/critical COVID-19, and no treatment were independently associated with an increased mortality, whereas a lymphocyte count >500/mcl at COVID-19 onset was protective. Chemotherapy induced neutropenia during the acute phase of COVID-19 did not show any impact on mortality (Table 3).
<figure><img src="image_8.png" /></figure>

<table><caption>Figure 2. 30-day survival probability of treated vs. untreated patients.</caption><thead><tr><th>Number of patients at risk</th><th colspan="4">Days from COVID-19 diagnosis</th></tr></thead><tbody><tr><td>No HM treatment</td><td>107</td><td>68</td><td>49</td><td>42</td></tr><tr><td>HM treatment</td><td>341</td><td>291</td><td>247</td><td>201</td></tr></tbody></table>

<table><caption>Table 3. Univariable and multivariable analysis for risk factors for mortality (whole cohort).</caption><thead><tr><th rowspan="2"></th><th colspan="4">Univariable</th><th colspan="4">Multivariable</th></tr><tr><th>p Value</th><th>HR</th><th>95% CI<br>Lower</th><th>95% CI<br>Upper</th><th>p Value</th><th>HR</th><th>95% CI<br>Lower</th><th>95% CI<br>Upper</th></tr></thead><tbody><tr><td>Sex</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Female</td><td>-</td><td>-</td><td>-</td><td>-</td><td></td><td></td><td></td><td></td></tr><tr><td>Male</td><td>0.965</td><td>0.993</td><td>0.735</td><td>1.342</td><td></td><td></td><td></td><td></td></tr><tr><td>Age</td><td>&lt;0.001</td><td>1.035</td><td>1.024</td><td>1.046</td><td>&lt;0.001</td><td>1.033</td><td>1.019</td><td>1.047</td></tr><tr><td>Baseline malignancy</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>ALL</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>AML</td><td>0.015</td><td>2.632</td><td>1.210</td><td>5.726</td><td>0.080</td><td>2.307</td><td>0.906</td><td>5.873</td></tr><tr><td>Lymphoma</td><td>0.656</td><td>1.198</td><td>0.541</td><td>2.650</td><td>0.957</td><td>0.974</td><td>0.369</td><td>2.567</td></tr><tr><td>CLD</td><td>0.832</td><td>1.108</td><td>0.430</td><td>2.860</td><td>0.082</td><td>0.365</td><td>0.117</td><td>1.137</td></tr><tr><td>MM</td><td>0.085</td><td>2.090</td><td>0.904</td><td>4.833</td><td>0.941</td><td>1.040</td><td>0.374</td><td>2.889</td></tr><tr><td>MDS/MPS</td><td>0.245</td><td>1.704</td><td>0.694</td><td>4.180</td><td>0.752</td><td>0.838</td><td>0.282</td><td>2.495</td></tr><tr><td>COVID-19 infection severity</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Asymptomatic</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Mild infection</td><td>0.919</td><td>1.036</td><td>0.525</td><td>2.045</td><td>0.862</td><td>1.068</td><td>0.509</td><td>2.239</td></tr><tr><td>Severe infection</td><td>0.080</td><td>1.545</td><td>0.949</td><td>2.515</td><td>0.026</td><td>1.804</td><td>1.074</td><td>3.032</td></tr><tr><td>Critical infection</td><td>&lt;0.001</td><td>4.598</td><td>2.896</td><td>7.299</td><td>&lt;0.001</td><td>5.523</td><td>3.328</td><td>9.166</td></tr><tr><td>Comorbidities at COVID-19 onset</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>**Table 3. Cont.**</caption><thead><tr><th rowspan="2"></th><th rowspan="2">p Value</th><th colspan="4">Univariable</th><th colspan="4">Multivariable</th></tr><tr><th>HR</th><th colspan="2">95% CI</th><th>p Value</th><th>HR</th><th colspan="2">95% CI</th></tr><tr><th></th><th></th><th></th><th>Lower</th><th>Upper</th><th></th><th></th><th>Lower</th><th>Upper</th></tr></thead><tbody><tr><td>No comorbidities</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>1 comorbidity</td><td>0.033</td><td>1.527</td><td>1.034</td><td>2.256</td><td>0.618</td><td>1.113</td><td>0.732</td><td>1.692</td></tr><tr><td>2 comorbidities</td><td>&lt;0.001</td><td>2.630</td><td>1.746</td><td>3.960</td><td>0.015</td><td>1.767</td><td>1.119</td><td>2.793</td></tr><tr><td>3 or more comorbidities</td><td>0.014</td><td>1.817</td><td>1.129</td><td>2.924</td><td>0.066</td><td>1.680</td><td>0.967</td><td>2.918</td></tr><tr><td>Season COVID-19 diagnosis</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>March 2020–September 2020</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>October 2020–February 2021</td><td>0.003</td><td>0.603</td><td>0.430</td><td>0.845</td><td>0.699</td><td>1.084</td><td>0.720</td><td>1.634</td></tr><tr><td>March 2021–November 2021</td><td>0.060</td><td>0.639</td><td>0.400</td><td>1.019</td><td>0.402</td><td>1.280</td><td>0.719</td><td>2.279</td></tr><tr><td>December 2021–February 2022</td><td>&lt;0.001</td><td>0.384</td><td>0.222</td><td>0.666</td><td>0.728</td><td>0.880</td><td>0.428</td><td>1.810</td></tr><tr><td>Malignancy treatment?</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Before COVID-19 diagnosis</td><td>0.053</td><td>0.717</td><td>0.512</td><td>1.004</td><td></td><td></td><td></td><td></td></tr><tr><td>After COVID-19 diagnosis</td><td>&lt;0.001</td><td>0.251</td><td>0.154</td><td>0.408</td><td></td><td></td><td></td><td></td></tr><tr><td>Neutrophils at COVID-19 onset</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>≤500</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>501–999</td><td>0.650</td><td>0.858</td><td>0.442</td><td>1.665</td><td></td><td></td><td></td><td></td></tr><tr><td>≥1000</td><td>0.082</td><td>0.706</td><td>0.475</td><td>1.045</td><td></td><td></td><td></td><td></td></tr><tr><td>Lymphocytes at COVID-19 onset</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>≤200</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>201–499</td><td>0.058</td><td>0.582</td><td>0.333</td><td>1.018</td><td>0.210</td><td>0.683</td><td>0.377</td><td>1.239</td></tr><tr><td>≥500</td><td>0.005</td><td>0.553</td><td>0.366</td><td>0.836</td><td>0.024</td><td>0.573</td><td>0.352</td><td>0.931</td></tr><tr><td>Chemotherapy induced neutropenia</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Yes</td><td>0.071</td><td>0.722</td><td>0.506</td><td>1.029</td><td>0.239</td><td>1.285</td><td>0.846</td><td>1.950</td></tr><tr><td>No treatment administered</td><td>0.011</td><td>1.602</td><td>1.112</td><td>2.308</td><td>&lt;0.001</td><td>3.449</td><td>2.224</td><td>5.349</td></tr><tr><td>Secondary infection after COVID-19</td><td>0.125</td><td>0.740</td><td>0.503</td><td>1.087</td><td></td><td></td><td></td><td></td></tr><tr><td>COVID-19 treatment</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No specific treatment reported</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Antivirals + monoclonal antibodies ± corticosteroids ± plasma</td><td>0.213</td><td>0.286</td><td>0.040</td><td>2.049</td><td>0.105</td><td>0.190</td><td>0.025</td><td>1.414</td></tr><tr><td>Antivirals ± corticosteroids ± plasma</td><td>0.793</td><td>1.064</td><td>0.668</td><td>1.695</td><td>0.395</td><td>0.798</td><td>0.476</td><td>1.341</td></tr><tr><td>Corticosteroids</td><td>0.791</td><td>0.944</td><td>0.617</td><td>1.444</td><td>0.033</td><td>0.605</td><td>0.381</td><td>0.961</td></tr><tr><td>Monoclonal antibodies ± plasma ± corticosteroids</td><td>0.026</td><td>0.360</td><td>0.147</td><td>0.882</td><td>0.081</td><td>0.442</td><td>0.177</td><td>1.107</td></tr><tr><td>Plasma ± corticosteroids</td><td>0.905</td><td>1.063</td><td>0.392</td><td>2.880</td><td>0.269</td><td>0.557</td><td>0.198</td><td>1.571</td></tr></tbody></table>

ALL, acute lymphoid leukaemia; AML, acute myeloid leukaemia; CI, confidence interval; CLD, chronic lymphoproliferative disorder; COVID-19, coronavirus disease 2019; HR, hazard ratio; MDS, myelodysplastic syndrome; MM, multiple myeloma; MPS, myeloproliferative syndrome asymptomatic: no clinical signs or symptoms; mild: non-pneumonia and mild pneumonia; severe: dyspnoea, respiratory frequency ≥ 30 breaths per min, SpO₂ ≤ 93%, PaO₂/FiO₂ < 300, or lung infiltrates > 50%; critical: patients admitted in intensive care for respiratory failure, septic shock, or multiple organ dysfunction or failure.

Age, critical COVID-19, and no HM treatment were risk factors for mortality at univariable and multivariable analyses for both AML and lymphoma patients. Chemotherapy induced neutropenia during the acute phase of COVID-19 was not a mortality risk factor in AML cases, whereas it was for lymphoma patients; immunotherapy before COVID-19 was protective at univariable analysis for lymphoma patients. Moreover, the diagnosis of COVID-19 in consecutive waves to the initial one was associated with a reduced risk for mortality as compared to the first in lymphoma patients at multivariable analysis, while this was not significant for AML (Tables S4 and S5).

## 4. Discussion

The COVID-19 pandemic has impacted the algorithms for treating HM. While there is some consensus on when to avoid or delay HM treatment during the pandemic [4], no guidelines are available yet for treatment of patients with simultaneous COVID-19 and HM
diagnosis. Here we present results of a dataset of 450 patients with simultaneous diagnosis of HM and COVID-19, derived from the EPICOVIDEHA registry. In this analysis, AL and lymphoma were predominant, and about three quarters of these patients received treatment for HM. An overall response rate was observed in about 40% of patients after first-line treatment, and overall survival was 60.7%. Age, critical COVID-19, ≥2 comorbidities and lack of HM treatment were independent predictors of mortality.

The demographic characteristics of patients were similar to those observed in the overall population of the EPICOVIDEHA registry [1] and in other series [2,3]. Most patients were admitted to hospital, with a very high proportion of AL patients, particularly AML, which could be justified by the clinical complexity of these patients who cannot be managed at home since the onset of HM. Indeed, more than half of patients showed a severe or critical COVID-19, which is the subset more difficult to treat for the haematologists.

Among patients receiving HM treatment, 66.2% initiated their treatment before COVID-19 diagnosis and only 33.8% after. As compared to non-treated patients, treated patients were more often female and younger, which could be explained by a relative lower severity of COVID-19. Treated patients were more often affected by AL and, although to a lesser extent, lymphoma, probably because of the urgent need of treatment for these patients. Severity of COVID-19 did not differ significantly in treated and untreated patients, whereas the degree of severity was less pronounced when considering patients treated at least after COVID-19. Thirty-day mortality was significantly lower in patients treated either before and/or after COVID-19 or only after COVID-19 compared to patients with no treatment at all, suggesting that early HM treatment contributes to a better control of SARS-CoV-2 infection.

Overall, the response rate to HM treatment was relatively low (40.8%), probably also for the proportion of deceased patients during treatment, and after a median follow-up of 35 days 60.7% of patients remained alive. COVID-19 alone or in association with HM was the main cause of death. As expected, AML was the HM with the highest 30-day mortality (44.2%), confirming data already reported in the pre-vaccination era [1,5,15]. Mortality was markedly lower (18.7%) in ALL. Causes of this difference may be found in the usually younger age of ALL patients as compared to AML and in the less intensive induction regimen required for ALL treatment than AML, in addition to the fact that also steroid alone can control the disease, at least for a limited period. A Spanish study [16] reported a mortality of 29% in an ALL cohort including patients on salvage treatment during the first two COVID-19-waves. A lower mortality (11.1%) in ALL has also been reported by Chiaretti et al. [17] in a series of 63 ALL COVID-19 patients in a recent observational study, where only a minority (22.2%) of patients became infected with SARS-CoV-2 at diagnosis.

Considering lymphoproliferative disorders, a wide range of mortality rates has been observed among MM, lymphoma and CLD patients in previous EPICOVIDEHA studies [1], with the worst prognosis for MM. As reported in other series enrolling patients during different phases of HM [2,3], it is interesting to notice that no difference in mortality has been recorded between aggressive and indolent NHL COVID-19 patients neither at HM onset, probably reflecting an intrinsic immune response impairment of NHL patients.

Lack of HM treatment was an independent risk factor for mortality, in addition to well-established risks such as age, COVID-19 severity and presence of comorbidities. This association was quite evident in some HM patients, particularly AML, lymphoma, MDS/MPS and MM; it highlights the crucial role of early HM treatment and, therefore, of disease control, for a favourable outcome. In our series, chemotherapy induced neutropenia during the acute phases of COVID-19 did not affect the outcome of AML patients, as opposed to lymphoma patients, where it did. The role of neutropenia as negative impact on AML patients is still a matter of debate. Although some series report a negative impact of neutropenia [18–21], in the AML EPICOVIDEHA study [5] neutropenia at onset of COVID-19 was not a risk factor for mortality. Indeed, neutropenia is an intrinsic feature of AML, and it is present in AML patients regardless of treatment received. This is not true for lymphoma patients, where chemotherapy induced neutropenia had a negative
impact on survival, confirming that less intensive treatment should be preferred during the acute phase of COVID-19, as also suggested by the recent ECIL recommendations [22]. The incidence of secondary infections was relatively low (14%), and invasive fungal diseases were even rarer. These findings are in line with other reports on ICU patients [23,24] or HM patients [25].

In our cohort, less than ten percent of patients were fully vaccinated against COVID-19. Therefore, our study was not able to appropriately evaluate the impact of vaccination on outcome. We also analysed the outcome according to the pandemic period and we observed a relationship only for lymphoma patients, where any period after the first was independently associated to a better outcome. The mortality risk reduction across pandemic periods could be explained by multiple factors, such as an increased number of asymptomatic or mild infections registered while the pandemic was progressing and maybe also a lower virulence of SARS-CoV-2 infection detected over time [26], while in this study COVID-19 specific treatments did not have a relevant impact. Interestingly, in contrast to some of the largest epidemiologic studies published so far [1,5], no impact of pandemic period was observed for AML and simultaneous COVID-19 diagnosis patients, probably because of the burden of active HM disease.

The study is subject to several limitations. First, the absence of a comparison group of HM patients without COVID-19 makes it difficult to assess the real impact of covid on the prognosis of haematological disease and vice versa. Moreover, the choice of the time frame (−33 days to +3 days from COVID-19) for the simultaneous diagnosis of HM and COVID-19 was chosen based on the enrolment criteria of the protocol, which planned to record only patients who had a history of HM. We decided to not go beyond 33 days before COVID-19 to avoid enrolling patients who have already undergone more than one course of HM treatment. Another limitation of the study is the heterogeneity of the HM population and the different algorithms of HM treatment adopted in different countries during the COVID-19 pandemic, which makes interpretation of the results more difficult. Indeed, the concept of treatment delay is not the same for aggressive and indolent HM diseases. Another limitation is that we do not know exactly how many patients went from curative intent to palliation after COVID-19. Moreover, the inclusion of patients in the registry was potentially influenced by the impact of the pandemic waves, and results may not be applicable to the current omicron wave. Finally, the low percentage of vaccinated cases as well as those receiving COVID-19 treatment with monoclonal antibodies limit the applicability to the current and potentially also future phases of the pandemic.

**5. Conclusions**

Patients with simultaneous COVID-19 and HM still represent a challenge for haematologists, particularly in elderly patients with AML. Our results outline the importance of HM treatment delivered as soon as possible for patients requiring immediate HM therapy. Indeed, Haematologists may fear initiating treatment that may cause more immunosuppression or lead to other side effects in a patient with active COVID-19; however, the consequences of delayed or suspended treatment may be worse. Any supportive measure should be provided for those patients with chemotherapy-induced neutropenia. Whenever possible, a less-intensive approach should be considered, particularly for lymphoma patients, where chemotherapy-induced neutropenia was found as risk factor for mortality. Future studies should evaluate the impact of large-scale COVID-19 vaccination on outcome of patients with simultaneous HM and COVID-19 diagnosis.

**Supplementary Materials:** The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers14225530/s1, Table S1: COVID-19 directed antivirals; Table S2: HM treatments before and after COVID-19 diagnosis; Table S3: 30-day mortality according to HM treatment start; Table S4: Univariable and multivariable analysis for risk factors for mortality (AML patients); Table S5: Univariable and multivariable analysis for risk factors for mortality (Lymphoma patients); Figure S1: 30-day survival probability of treated vs. untreated patients according to HM.
**Author Contributions:** C.C., J.S.-G., O.A.C. and L.P. contributed to study design, study supervision, and data interpretation and wrote the paper C.C., J.S.-G. and L.P. did the statistical plan. J.S.-G. performed the analysis and C.C., J.S.-G. and L.P. interpreted the data. C.C., J.S.-G., F.M., S.E.-A., F.I., B.W., M.G.D.S., M.D., J.D.-V., S.M.-P., F.F., J.V.D., T.V., C.B. (Caroline Besson), C.B.P., A.L.-G., P.Ž., M.S. (Martin Schönlein), K.P., O.J., A.C. (Alba Cabirta), N.A., U.S., N.F., G.D., T.A.-V., M.M. (Monia Marchetti), M.M. (Marina Machado), A.G., O.F., F.D., O.B., M.C.T., A.S.O., M.N., Z.R., J.N., G.M., M.J., C.G.-V., N.E., M.I.D.P., C.B. (Caterina Buquicchio), R.B., J.B., M.A.-K., L.V., T.S., M.S. (Michail Samarkos), I.O.-V., S.M., J.M., L.I.P., M.H. (Martin Hoenigl), L'D., A.C. (Annarosa Cuccaro), Y.M.B., A.A., L.R., S.G., M.S. (Mariarita Sciumè), M.M. (Miloš Mladenović), G.M.Ç., M.V.S., A.N., C.B.V., M.H. (Michaela Hanáková), N.G.-P., Z.E., G.P.M.Z., R.N.R., R.C., G.-A.M., M.M.B., O.A.C. and L.P. recruited participants and collected and interpreted data. C.C., J.S.-G., F.M., S.E.-A., F.I., B.W., M.G.D.S., M.D., J.D.-V., S.M.-P., F.F., J.V.D., T.V., C.B. (Caroline Besson), C.B.P., A.L.-G., P.Ž., M.S. (Martin Schönlein), K.P., O.J., A.C. (Alba Cabirta), N.A., U.S., N.F., G.D., T.A.-V., M.M. (Monia Marchetti), M.M. (Marina Machado), A.G., O.F., F.D., O.B., M.C.T., A.S.O., M.N., Z.R., J.N., G.M., M.J., C.G.-V., N.E., M.I.D.P., C.B. (Caterina Buquicchio), R.B., J.B., M.A.-K., L.V., T.S., M.S. (Michail Samarkos), I.O.-V., S.M., J.M., L.I.P., M.H. (Martin Hoenigl), L'D., A.C. (Annarosa Cuccaro), Y.M.B., A.A., L.R., S.G., M.S. (Mariarita Sciumè), M.M. (Miloš Mladenović), G.M.Ç., M.V.S., A.N., C.B.V., M.H. (Michaela Hanáková), N.G.-P., Z.E., G.P.M.Z., R.N.R., R.C., G.-A.M., M.M.B., O.A.C. and L.P. contributed to manuscript writing and review of the manuscript. C.C., J.S.-G., F.M., S.E.-A., F.I., B.W., M.G.D.S., M.D., J.D.-V., S.M.-P., F.F., J.V.D., T.V., C.B. (Caroline Besson), C.B.P., A.L.-G., P.Ž., M.S. (Martin Schönlein), K.P., O.J., A.C. (Alba Cabirta), N.A., U.S., N.F., G.D., T.A.-V., M.M. (Monia Marchetti), M.M. (Marina Machado), A.G., O.F., F.D., O.B., M.C.T., A.S.O., M.N., Z.R., J.N., G.M., M.J., C.G.-V., N.E., M.I.D.P., C.B. (Caterina Buquicchio), R.B., J.B., M.A.-K., L.V., T.S., M.S. (Michail Samarkos), I.O.-V., S.M., J.M., L.I.P., M.H. (Martin Hoenigl), L'D., A.C. (Annarosa Cuccaro), Y.M.B., A.A., L.R., S.G., M.S. (Mariarita Sciumè), M.M. (Miloš Mladenović), G.M.Ç., M.V.S., A.N., C.B.V., M.H. (Michaela Hanáková), N.G.-P., Z.E., G.P.M.Z., R.N.R., R.C., G.-A.M., M.M.B., O.A.C. and L.P. agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. C.C., J.S.-G., F.M., S.E.-A., F.I., B.W., M.G.D.S., M.D., J.D.-V., S.M.-P., F.F., J.V.D., T.V., C.B. (Caroline Besson), C.B.P., A.L.-G., P.Ž., M.S. (Martin Schönlein), K.P., O.J., A.C. (Alba Cabirta), N.A., U.S., N.F., G.D., T.A.-V., M.M. (Monia Marchetti), M.M. (Marina Machado), A.G., O.F., F.D., O.B., M.C.T., A.S.O., M.N., Z.R., J.N., G.M., M.J., C.G.-V., N.E., M.I.D.P., C.B. (Caterina Buquicchio), R.B., J.B., M.A.-K., L.V., T.S., M.S. (Michail Samarkos), I.O.-V., S.M., J.M., L.I.P., M.H. (Martin Hoenigl), L'D., A.C. (Annarosa Cuccaro), Y.M.B., A.A., L.R., S.G., M.S. (Mariarita Sciumè), M.M. (Miloš Mladenović), G.M.Ç., M.V.S., A.N., C.B.V., M.H. (Michaela Hanáková), N.G.-P., Z.E., G.P.M.Z., R.N.R., R.C., G.-A.M., M.M.B., O.A.C. and L.P. have read and agreed to the published version of the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** EPICOVIDEHA has received funds from Optics COMMITTM (COVID-19 Unmet Medical Needs and Associated Research Extension) COVID-19 RFP program by GILEAD Science, United States (Project 2020-8223).

**Institutional Review Board Statement:** The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of Fondazione Policlinico Universitario Agostino Gemelli-IRCCS, Università Cattolica del Sacro Cuore of Rome, Italy (Study ID: 3226). Additionally, if applicable, the respective local ethics committee of each participating institution might have approved the EPICOVIDEHA.

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study when required by the respective Ethics Committee.

**Data Availability Statement:** The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

**Conflicts of Interest:** The funder of the study had no role in study design, data analysis, interpretation, or writing of the report. All authors had full access to the data and had final responsibility for the decision to submit for publication.
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