Articles Nirmatrelvir/ritonavir in COVID-19 patients with haematological malignancies: a report from the EPICOVIDEHA registry Jon Salmanton-García,a,b,c,bv,∗ Francesco Marchesi,d,bv Maria Gomes da Silva,e Francesca Farina,f Julio Dávila-Valls,g Yavuz M. Bilgin,h Andreas Glenthøj,i Iker Falces-Romero,j,k Jaap Van Doesum,l Jorge Labrador,m,n Caterina Buquicchio,o Shaimaa El-Ashwah,p Verena Petzer,q Jens Van Praet,r Martin Schönlein,s Michelina Dargenio,t Gustavo-Adolfo Méndez,u Stef Meers,v Federico Itri,w Antonio Giordano,x László Imre Pinczés,y Ildefonso Espigado,z Zlate Stojanoski,aa Alberto López-García,ab Lucia Prezioso,ac Ozren Jaksic,ad Antonio Vena,ae Nicola S. Fracchiolla,af Tomás José González-López,ag Natasa Colović,ah Mario Delia,ai Barbora Weinbergerová,aj Monia Marchetti,ak Joyce Marques de Almeida,al Olimpia Finizio,am Caroline Besson,an,bu Monika M. Biernat,ao Toni Valković,ap,aq,ar Tobias Lahmer,as Annarosa Cuccaro,at Irati Ormazabal-Vélez,au Josip Batinić,av,aw Noemí Fernández,ax Nick De Jonge,ay Carlo Tascini,az Amalia N. Anastasopoulou,ba Rémy Duléry,bb Maria Ilaria Del Principe,bc Gaëtan Plantefeve,bd Mario Virgilio Papa,be Marcio Nucci,bf Moraima Jiménez,bg,bh Avinash Aujayeb,bi José-Ángel Hernández-Rivas,bj,bk Maria Merelli,az Chiara Cattaneo,bl Ola Blennow,bm Anna Nordlander,bm Alba Cabirta,bg Gina Varricchio,be Maria Vittoria Sacchi,ak Raul Cordoba,ab Elena Arellano,bn Stefanie K. Gräfe,b,bo,bp,bq Dominik Wolf,q Ziad Emarah,p Emanuele Ammatuna,l Ditte Stampe Hersby,i Sonia Martín-Pérez,g Raquel Nunes Rodrigues,e Laman Rahimli,b,bq Livio Pagano,x,br,bw and Oliver A. Cornely,a,b,c,bs,bt,bw,∗∗ on behalf of the EPICOVIDEHA registry a University of Cologne, Faculty of Medicine, and University Hospital Cologne, Chair Translational Research, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, Germany b University of Cologne, Faculty of Medicine, and University Hospital Cologne, Department I of Internal Medicine, Excellence Center for Medical Mycology (ECMM), Cologne, Germany c German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany d Hematology and Stem Cell Transplant Unit, IRCCS Regina Elena National Cancer Institute, Rome, Italy e Portuguese Institute of Oncology, Lisbon, Portugal f IRCCS Ospedale San Raffaele, Milan, Italy g Hospital Nuestra Señora de Sonsoles, Ávila, Spain h Department of Internal Medicine, ADRZ, Goes, the Netherlands i Department of Hematology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark j La Paz University Hospital, Madrid, Spain k CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain l University Medical Center Groningen, Groningen, the Netherlands m Department of Hematology, Research Unit, Hospital Universitario de Burgos, Burgos, Spain n Facultad de Ciencias de la Salud, Universidad Isabel I, Burgos, Spain o Ematologia con Trapianto, Ospedale Dimiccoli Barletta, Barletta, Italy p Oncology Center, Mansoura University, Mansoura, Egypt q Department of Hematology and Oncology, Comprehensive Cancer Center Innsbruck (CCCI), Medical University of Innsbruck (MUI), Innsbruck, Austria r Department of Nephrology and Infectious Diseases, AZ Sint-Jan Brugge-Oostende AV, Brugge, Belgium s Department of Oncology, Hematology and Bone Marrow Transplantation with Section of Pneumology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany t Hematology and Stem Cell Transplant Unit, Vito Fazzi, Lecce, Italy u Hospital Escuela de Agudos Dr. Ramón Madariaga, Posadas, Argentina v AZ KLINA, Brasschaat, Belgium w San Luigi Gonzaga Hospital - Orbassano, Orbassano, Italy x Hematology Unit, Fondazione Policlinico Universitario Agostino Gemelli - IRCCS, Rome, Italy y Division of Hematology, Department of Internal Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary z Department of Hematology, University Hospital Virgen Macarena - University Hospital Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBIS / CSIC), Universidad de Sevilla (Departamento de Medicina), Seville, Spain *Corresponding author. University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne Excellence, Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, Germany. **Corresponding author. University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne Excellence, Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, Germany. E-mail addresses: jon.salmanton-garcia@uk-koeln.de (J. Salmanton-García), oliver.cornely@uk-koeln.de (O.A. Cornely). bv Shared junior authorship. bw Shared senior authorship. www.thelancet.com Vol 58 April, 2023 1 Articles aa University Clinic of Hematology, Skopje, North Macedonia ab Fundacion Jimenez Diaz University Hospital, Health Research Institute IIS-FJD, Madrid, Spain ac Hospital University of Parma - Hematology and Bone Marrow Unit, Parma, Italy ad Department of Hematology, University Hospital Dubrava, Zagreb, Croatia ae Ospedale Policlinico San Martino, Genoa, Italy af Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy ag Department of Hematology, Hospital Universitario de Burgos, Burgos, Spain ah University Clinical Center Serbia, Medical Faculty University Belgrade, Belgrade, Serbia ai Hematology and Stem Cell Transplantation Unit, AOUC Policlinico, Bari, Italy aj Department of Internal Medicine - Hematology and Oncology, Masaryk University Hospital Brno, Brno, Czech Republic ak Azienda Ospedaliera Nazionale SS. Antonio e Biagio e Cesare Arrigo, Alessandria, Italy al Istituto Oncologico della Svizzera Italiana, Bellinzona, Switzerland am UOC Hematology, AORN Cardarelli, Naples, Italy an Centre Hospitalier de Versailles, Le Chesnay, France ao Department of Haematology, Blood Neoplasms, and Bone Marrow Transplantation, Wroclaw Medical University, Wroclaw, Poland ap University Hospital Centre Rijeka, Rijeka, Croatia aq Croatian Cooperative Group for Hematological Diseases (CROHEM), Croatia ar Faculty of Medicine and Faculty of Health Studies University of Rijeka, Rijeka, Croatia as Medizinische Klinik II, Klinikum rechts der Isar, TU München, Munich, Germany at Hematology Unit, Center for Translational Medicine, Azienda USL Toscana NordOvest, Livorno, Italy au Complejo Hospitalario de Navarra, Iruña-Pamplona, Spain av University Hospital Centre Zagreb, Zagreb, Croatia aw School of Medicine University of Zagreb, Zagreb, Croatia ax Hospital Universitario Marqués de Valdecilla, Santander, Spain ay Amsterdam UMC, Location VUmc, Amsterdam, the Netherlands az Azienda Sanitaria Universitaria del Friuli Centrale, Udine, Italy ba Laikon Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece bb Service d’Hématologie Clinique et de Thérapie Cellulaire, Hôpital Saint Antoine, Assistance Publique-Hôpitaux de Paris, Sorbonne Université, Inserm UMRs 938, Paris, France bc Hematology, Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy bd Head ICU and CRC, Centre Hospitalier Victor DUPOUY, Argenteuil, France be Azienda Ospedaliera Sant’Anna e San Sebastiano, Caserta, Italy bf Federal University of Rio de Janeiro, Rio de Janeiro, Brazil bg Department of Hematology, Vall d’Hebron Hospital Universitari, Experimental Hematology, Vall d’Hebron Institute of Oncology (VHIO), Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain bh Departament de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain bi Northumbria Healthcare, Newcastle, United Kingdom bj Hospital Universitario Infanta Leonor, Madrid, Spain bk Departmento de Medicina, Universidad Complutense de Madrid, Madrid, Spain bl Hematology Unit, ASST-Spedali Civili, Brescia, Italy bm Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden bn Department of Hematology, University Hospital Virgen Macarena, Seville, Spain bo I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany bp III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany bq University of Cologne, Faculty of Medicine, and University Hospital Cologne, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, Germany br Hematology Unit, Università Cattolica del Sacro Cuore, Rome, Italy bs University of Cologne, Faculty of Medicine, and University Hospital Cologne, Center for Molecular Medicine Cologne (CMMC), Cologne, Germany bt University of Cologne, Faculty of Medicine, and University Hospital Cologne, Clinical Trials Centre Cologne (ZKS Köln), Cologne, Germany bu Université Paris-Saclay, UVSQ, Inserm, Équipe "Exposome et Hérédité", CESP, Villejuif, France eClinicalMedicine Summary 2023;58: 101939 Background Nirmatrelvir/ritonavir treatment decreases the hospitalisation rate in immunocompetent patients with Published Online xxx COVID-19, but data on efficacy in patients with haematological malignancy are scarce. Here, we describe the https://doi.org/10. outcome of nirmatrelvir/ritonavir treatment in a large cohort of the latter patients. 1016/j.eclinm.2023. 101939 Methods This is a retrospective cohort study from the multicentre EPICOVIDEHA registry (NCT04733729) on pa- tients with haematological malignancy, who were diagnosed with COVID-19 between January and September 2022. 2 www.thelancet.com Vol 58 April, 2023 Articles Patients receiving nirmatrelvir/ritonavir were compared to those who did not. A logistic regression was run to determine factors associated with nirmatrelvir/ritonavir administration in our sample. Mortality between treatment groups was assessed with Kaplan–Meier survival plots after matching all the patients with a propensity score. Additionally, a Cox regression was modelled to detect factors associated with mortality in patients receiving nirmatrelvir/ritonavir. Findings A total of 1859 patients were analysed, 117 (6%) were treated with nirmatrelvir/ritonavir, 1742 (94%) were treated otherwise. Of 117 patients receiving nirmatrelvir/ritonavir, 80% had received ≥1 anti-SARS-CoV-2 vaccine dose before COVID-19 onset, 13% of which received a 2nd vaccine booster. 5% were admitted to ICU. Nirmatrelvir/ritonavir treatment was associated with the presence of extrapulmonary symptoms at COVID-19 onset, for example anosmia, fever, rhinitis, or sinusitis (aOR 2.509, 95%CI 1.448–4.347) and 2nd vaccine booster (aOR 3.624, 95%CI 1.619–8.109). Chronic pulmonary disease (aOR 0.261, 95%CI 0.093–0.732) and obesity (aOR 0.105, 95%CI 0.014–0.776) were not associated with nirmatrelvir/ritonavir use. After propensity score matching, day-30 mortality rate in patients treated with nirmatrelvir/ritonavir was 2%, significantly lower than in patients with SARS-CoV-2 directed treatment other than nirmatrelvir/ritonavir (11%, p = 0.036). No factor was observed explaining the mortality difference in patients after nirmatrelvir/ritonavir administration. Interpretation Haematological malignancy patients were more likely to receive nirmatrelvir/ritonavir when reporting extrapulmonary symptoms or 2nd vaccine booster at COVID-19 onset, as opposed to chronic pulmonary disease and obesity. The mortality rate in patients treated with nirmatrelvir/ritonavir was lower than in patients with targeted drugs other than nirmatrelvir/ritonavir. Funding EPICOVIDEHA has received funds from Optics COMMIT (COVID-19 Unmet Medical Needs and Asso- ciated Research Extension) COVID-19 RFP program by GILEAD Science, United States (Project 2020-8223). Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Keywords: Nirmatrelvir; SARS-CoV-2; Haematology; Malignancy; COVID-19 Research in context Evidence before this study results show that nirmatrelvir/ritonavir was administered Nirmatrelvir/ritonavir is a new antiviral targeting the SARS- more frequently to patients with extrapulmonary symptoms CoV-2 3Cl protease. It is widely recommended for patients and those who had received a 2nd vaccine booster dose with mild symptoms to prevent severe episodes of COVID-19. against SARS-CoV-2. On the contrary, patients with chronic A web search was performed on November 12th for articles in pulmonary disease or obesity were less likely to receive English, French, German, Italian, or Spanish using strings nirmatrelvir/ritonavir. Mortality was significantly lower than combining the terms “haemato*, “hemato*”, “nirmatrelvir*”, in patients with other directed treatments. “paxlovid” with “administration”, “mortality”, “outcome”, and Implications of all the available evidence “treatment". No studies focusing specifically on nirmatrelvir/ Clinical management of COVID-19 patients with baseline ritonavir administration in haematological patients were haematological malignancies remains challenging two years found. Single publications targeting the general population or after onset of the pandemic. Although vaccines prevent immunosuppressed patients were retrieved, but provided no hospitalization and reduce mortality rates, patients with detailed information on patients with haematological haematological malignancy may not mount protective malignancy. immune response. In this vulnerable immunosuppressed Added value of this study patient group nirmatrelvir/ritonavir treatment results in lower To the best of our knowledge, this is the first publication mortality rates as compared to other treatment approaches. describing the factors associated with nirmatrelvir/ritonavir Still not all patients qualifying for nirmatrelvir/ritonavir administration and investigating factors associated with received that treatment. Reasons for underuse remain unclear mortality in patients with haematological malignancy. Our at this point. Introduction efforts by all stakeholders led to effective treatment Since the coronavirus disease 2019 (COVID-19) options that can ameliorate the disease. Vaccines have pandemic was declared in March 2020,1 unprecedented proved to be a most effective method preventing www.thelancet.com Vol 58 April, 2023 3 Articles hospitalisation and mortality.2,3 Immunocompromised polymerase chain reaction (PCR) or antigen test; and patients, for instance those with haematological ma- SARS-CoV-2 diagnosis between January 1st and lignancy, have been at increased risk for severe courses September 30th, 2022. of COVID-19 and fatal outcome. Because of impaired Selected patients were grouped according to treat- immune response to vaccination, they are still at high- ment specifically received for COVID-19. Thus, we risk and need other approaches than current formed the following categories: patients treated with vaccines.4–6 nirmatrelvir/ritonavir ± other directed or non-directed Such approaches have been implemented with the treatments, patients receiving other SARS-CoV-2 antivirals molnupiravir,7 nirmatrelvir/ritonavir,8 and directed antivirals or monoclonal antibodies ± other remdesivir,9 and with the monoclonal antibodies tar- non-directed treatments, and finally patients receiving geting viral antigens.10–14 The common goal of these neither directed antivirals or monoclonal antibodies, nor drugs is reducing rates of hospitalisation, severe dis- corticosteroids or convalescent plasma. ease, and death. Approved for administration in 2022,15,16 during the initial moments of the omicron Statistical analysis wave, nirmatrelvir/ritonavir is an oral protease inhibitor Consecutive data from participating institutions were administered in high-risk patients with mild symptoms summarised with frequencies and percentages for cat- early in the course of COVID-19.15,16 Although the phase egorical variables and with median, interquartile range 3 development programme addressed high-risk pa- (IQR) and absolute range for continuous variables. tients, only few patients with cancer were enrolled.8 Proportion comparisons were performed using Fisher’s Current consensus guidelines recommend nirma- exact or Pearson’s chi (X) squared tests, respectively. trelvir/ritonavir in patients with haematological malig- Logistic regression was utilised to determine which in- nancy,17 although there is a lack of available data on this dependent variables were associated with subsequent patient group.18 nirmatrelvir/ritonavir administration. For comparison This EPICOVIDEHA study compares epidemiology analyses, patients were matched with a propensity score and outcome of patients with haematological malig- based on a logistic regression. The model included the nancy receiving nirmatrelvir/ritonavir treatment versus variables sex, age (±10 years), baseline haematological those who did not. malignancy, haematological malignancy status at COVID-19 onset, and origin continent (Europe). In or- der to determine the power and robustness of the per- Methods formed propensity score, variables used for the All data included in this analysis were exported from the matching were confronted with a median difference EPICOVIDEHA registry. EPICOVIDEHA (NCT04733729) (age), Phi coefficient (sex and origin continent [Europe]), is an online registry open for patients with haematologic or Cramér’s V (baseline haematological malignancy and malignancy and SARS-CoV-2 infection. Cases from haematological malignancy status at COVID-19 onset), various regions of the world are documented in an elec- as appropriate (Supplementary Table S1). A log-rank test tronic case report form (eCRF) accessible via www. was used to compare the survival probability of the pa- clinicalsurveys.net (EFS Summer 2021, TIVIAN, Co- tients based on the treatment received for COVID-19, logne, Germany). The eCRF comprises epidemiological which was graphically represented with a Kaplan– data, such as baseline pre-COVID-19 conditions, previous Meier survival plot. Additionally, Cox regression was clinical management of the haematologic malignancy, used to analyse which factor could be associated with anti-SARS-CoV-2 vaccination history, COVID-19 diagnosis mortality both in every patient and in nirmatrelvir/ri- and management, and outcome. All patients are included tonavir recipients who had data on duration of follow in a validation process for data coherence and complete- up. Variables with a p value < 0.1 in the univariable ness performed by experts in haematologic malignancy models were considered for the respective multivariable and infectious diseases.19 In this validation process, data model. P value < 0.05 was considered statistically missing completely at random were reduced as possible, significant. contacting contributors were to solve pending queries. Exclusions from the database only happened if a patient Ethics statement was not fulfilling all the inclusion criteria (no haemato- The central ethics committee is at Fondazione Policli- logical malignancy, not active within the last 5 years prior nico Universitario Agostino Gemelli - IRCCS, Uni- to COVID-19, no adult, no laboratory-based COVID-19 versità Cattolica del Sacro Cuore of Rome, Italy (Study diagnosis). ID: 3226). Additionally, each participating institution For the present analysis, patients needed to fulfil all may also have a local approval for the research initiative inclusion criteria to be eligible: active haematologic as appropriate. The anonymized data that do not malignancy within the last five years prior to COVID-19, contain any personally identifiable information from including patients at onset or watch and wait; age ≥18 any sources implies that the informed consent is not years; SARS-CoV-2 infection confirmed by either applicable. 4 www.thelancet.com Vol 58 April, 2023 Articles Role of the funding source malignancy, haematological malignancy status at The funders had no role in the study design, the COVID-19 onset, and origin continent (Europe), the collection, analysis, and interpretation of data, writing of day-30 mortality rate was 2.0% (n = 2/102) after nir- the report and the decision to submit for publication. matrelvir/ritonavir administration, 10.8% (n = 11/102) JSG, FM, LP, and OAC had access to and verified all raw after the administration of directed treatment options data sets and made the decision to submit the other than nirmatrelvir/ritonavir, and 5.9% (n = 6/102) manuscript. in patients without treatment administration (p = 0.036, Table 4, Supplementary Table S2). Survival probability was significantly higher in patients treated with nirma- Results trelvir/ritonavir as compared to those with directed This EPICOVIDEHA data set comprises 1859 patients treatment options other than nirmatrelvir/ritonavir with haematological malignancy from 84 centres in 28 (p = 0.008, Fig. 2A and B). countries, who were diagnosed with COVID-19 between Sensitivity analyses we performed to determine which January and September 2022 (Fig. 1A). factors were associated to mortality in all the matched patients. Thus, we could observe how, in the univariable Overall cohort analyses, administration of directed drugs other than Almost 60% of the patients were male (n = 1070, nirmatrelvir/ritonavir was associated with an increased 57.6%), and often with no other comorbidities (n = 766, mortality (p = 0.046), as compared to nirmatrelvir/rito- 41.2%) besides haematological malignancy. Non- navir. Nevertheless, the factor more greatly associated Hodgkin lymphoma (n = 602, 32.5%) was the most with mortality in the analysed patients, either in the frequent haematological malignancy, followed by mul- univariable or in multivariable analyses was the hospital, tiple myeloma (n = 337, 18.1%). Only one in four especially to ICU (Supplementary Tables S3 and S4). documented patients (n = 501, 26.9%) had active ma- Nirmatrelvir/ritonavir administration remained as a lignancy when COVID-19 was diagnosed. Overall, protective factor in the coupled multivariable analyses 69.0% (n = 1282) had received antineoplastic treatment performed considering the COVID-19 treatment and the within the preceding three months, or hematopoietic variables observed to have a p < 0.1 in the univariable stem-cell transplantation or chimeric antigen receptor T models when including in couples COVID-19 treatment cell administration within the last six months before and age, comorbidities, neutrophils, status of the malig- COVID-19 diagnosis. The overall vaccination rate was nancy at COVID-19 onset and symptoms at COVID-19 76.9% (n = 1430). Of 1118/1859 (60.1%) patients onset, respectively (Supplementary Tables S5 and S6). receiving directed treatment for COVID-19, 117/1118 (10.5%) received nirmatrelvir/ritonavir, either as mon- Nirmatrelvir/ritonavir recipients otherapy (n = 93/117, 79.5%) or in combination with The majority of the 117 patients receiving nirmatrelvir/ other recommended drugs (n = 24/117, 20.5%), while ritonavir was male (n = 61, 51.7%). Non-Hodgkin lym- 1001/1118 (89.5%) patients received treatment schemes phoma (n = 37/117, 31.6%) and multiple myeloma without nirmatrelvir/ritonavir. A total of 741/1859 (n = 25/117, 21.4%) were the baseline haematological (39.9%) patients did not receive SARS-CoV-2 directed malignancy in more than half of the patients, 24.8% treatment. In total, intensive care was delivered to 148 (n = 29/117) of which had active malignancy at COVID- (8.0%) patients (Table 1, Table 2). 19 onset. Immuno-chemotherapy (n = 49/117, 41.9%), In univariable logistic regression, nirmatrelvir/rito- targeted therapy (n = 23/117, 19.7%) and conventional navir treatment was associated with a patient without chemotherapy (n = 16/117, 13.7%) were the most history of chronic pulmonary disease (odds ratio [OR] common HM treatment strategies administered 0.341, 95% confidence interval [CI] 0.136–0.852), immediately before infection diagnosis. Only 3.4% without obesity (OR 0.110, 95% CI 0.015–0.796), with (n = 4/117) of the patients received no haematological extrapulmonary (i.e., anosmia, fever, rhinitis, or sinus- malignancy treatment any time before COVID-19, all itis) symptoms at COVID-19 onset (OR 2.102, 95% CI due to a contemporaneous diagnosis of malignancy and 1.278–3.457), and receipt of a second booster/4th dose infection (Table 1). (OR 3.434, 95% CI 1.674–7.045). In the multivariable In the unmatched populations, the proportion of model, patients with extrapulmonary symptoms (aOR patients without any additional comorbidity at COVID- 2.509, 95% CI 1.448–4.347) and those having received a 19 onset was higher in patients with nirmatrelvir/rito- 4th vaccine dose (aOR 3.624, 95% CI 1.619–8.109) were navir (n = 53/117, 45.3%) than in those receiving other more likely to be treated with nirmatrelvir/ritonavir, directed drugs (n = 371/1001, 37.1%, p = 0.007), with no while patients with chronic pulmonary disease (adjusted difference between nirmatrelvir/ritonavir patients and OR [aOR] 0.261, 95% CI 0.093–0.732) and obesity (aOR those with no treatment/non-SARS-CoV-2 directed 0.105, 95% CI 0.014–0.776) were not (Table 3). treatment (n = 342/741, 46.2%, p = 0.618). Among the After matching the patients from the three treatment patients with at least one comorbidity, chronic cardiop- groups by sex, age (±10 years), baseline haematological athy was the most frequent (n = 48/117, 41.0%), similar www.thelancet.com Vol 58 April, 2023 5 Articles Fig. 1: Geographical distribution of patients documented in 2022 in EPICOVIDEHA according to the treatment received for COVID-19. A) Overall sample. This figure includes patients from institutions worldwide. Countries with patterns of more than one colour indicate that more than one type of treatment has been administered in the respective country. Blue indicates patients with nirmatrelvir/ritonavir ± other treatments: Italy (n = 59), Spain (n = 31), Belgium (n = 13), Germany (n = 7), France (n = 5), and Austria and Serbia (n = 1, each). Orange indicates patients with other SARS-CoV-2-directed drugs ± other treatments: Italy (n = 284), Spain (n = 162), Denmark (n = 73), Netherlands (n = 59), Germany (n = 51), Croatia (n = 36), Egypt (n = 33), Hungary (n = 32), Austria (n = 31); Belgium and France (n = 29, each), North Macedonia (n = 23), Serbia (n = 20), Czech Republic (n = 19), Greece (n = 18), Argentina, Poland, and Portugal (n = 16, each), Switzerland (n = 13), United Kingdom (n = 11), Sweden (n = 8), Turkey (n = 7), Brazil and Saudi Arabia (n = 6, each), and Bangladesh, Chile, and Hong Kong SAR (n = 1, each). Brown indicates patients with non-SARS-CoV-2-directed drugs: Spain (n = 192), Italy (n = 166), Netherlands (n = 105), Portugal (n = 80), Belgium (n = 35), Croatia (n = 26), France (n = 23), Argentina (n = 20), Austria (n = 15), Egypt (n = 14), Hungary (n = 11), Germany (n = 10), North Macedonia (n = 9), Switzerland (n = 7), Brazil (n = 6), Greece (n = 5), Turkey (n = 4), Serbia (n = 3), Denmark, Poland, and Sweden (n = 2, each), and Czech Republic, Saudi Arabia, Singapore, and United Kingdom (n = 1, each). B) Proportional ambulatory administration of nirmatrelvir/ritonavir. This figure includes patients from European institutions. The darker the blue, the higher proportion of patients receiving ambulatory nirmatrelvir/ritonavir: France (5/5) 100.0%, Italy (48/59) 81.4%, Spain (5/29) 17.2%, Belgium (1/13) 7.7%, and Austria (0/1), Germany (0/7), and Serbia (0/1) 0.0%, each. 6 www.thelancet.com Vol 58 April, 2023 Articles Directed treatment p value N/R p value No treatment/non-SARS- Overall other than N/R N/R vs other N/R vs no/other CoV-2 directed treatment non-directed tx directed treatment n % n % n % n % Sex 0.112 0.618 Female 400 40.0 56 47.9 333 44.9 789 42.4 Male 601 60.0 61 51.7 408 55.1 1070 57.6 Age 66 (53–75) 0.858 66 (55–75) 0.165 63 (51–74) 65 (52–75) [18–95] [22–88] [19–97] [18–97] Comorbidities at COVID-19 onset No comorbidities 371 37.1 0.007 53 45.3 0.618 342 46.2 766 41.2 1 comorbidity 320 32.0 40 34.2 248 33.5 608 32.7 2 comorbidities 192 19.2 22 18.8 102 13.8 316 17.0 3 or more comorbidities 118 11.8 2 1.7 49 6.6 169 9.1 Chronic cardiopathy 405 40.5 0.921 48 41.0 0.176 255 34.4 708 38.1 Chronic pulmonary disease 116 11.6 0.017 5 4.3 0.077 70 9.4 191 10.3 Diabetes mellitus 130 13.0 0.187 10 8.5 0.623 77 10.4 217 11.7 Liver disease 44 4.4 0.469 3 2.6 0.789 28 3.8 75 4.0 Obesity 73 7.3 0.005 1 0.9 0.072 33 4.5 107 5.8 Renal impairment 67 6.7 0.039 2 1.7 0.298 31 4.2 100 5.4 Smoking history 136 13.6 0.387 12 10.3 0.472 60 8.1 208 11.2 Baseline malignancy at COVID-19 0.432 0.635 onset Leukemia 393 39.3 49 41.9 282 38.1 724 38.9 Acute myeloid leukemia 152 15.2 17 14.5 62 8.4 231 12.4 Chronic myeloid leukemia 15 1.5 4 3.4 36 4.9 55 3.0 Acute lymphoid leukemia 58 5.8 8 6.8 35 4.7 101 5.4 Chronic lymphoid leukemia 107 10.7 5 4.3 97 13.1 209 11.2 Myelodisplastic syndrome 58 5.8 14 12.0 50 6.7 122 6.6 Hairy cell leukemia 3 0.3 1 0.9 2 0.3 6 0.3 Lymphoma 392 39.2 38 32.5 257 34.7 687 37.0 Hodgkin lymphoma 39 3.9 1 0.9 45 6.1 85 4.6 Non-Hodgkin lymphoma 353 35.3 37 31.6 212 28.6 602 32.4 PH negative myeloproliferative 28 2.8 5 4.3 51 6.9 84 4.5 diseases Essential thrombocythemia 2 0.2 0 0.0 19 2.6 21 1.1 Myelofibrosis 20 2.0 3 2.6 15 2.0 38 2.0 Polycythemia vera 4 0.4 1 0.9 14 1.9 19 1.0 Systemic mastocytosis 2 0.2 1 0.9 3 0.4 6 0.3 Plasma cell disorders 179 17.9 25 21.4 143 19.3 347 18.7 Multiple myeloma 175 17.5 25 21.4 137 18.5 337 18.1 Amyloid light-chain amyloidosis 4 0.4 0 0.0 6 0.8 10 0.5 Other hematological malignancies 9 0.9 0 0.0 10 1.3 19 1.0 Aplastic anemia 9 0.9 0 0.0 10 1.3 19 1.0 Status malignancy at COVID-19 0.234 0.065 onset Controlled disease 473 47.3 64 54.7 397 53.6 934 50.2 Stable disease 188 18.8 19 16.2 175 23.6 382 20.5 Active disease 314 31.4 29 24.8 158 21.3 501 26.9 Unknown 26 2.6 5 4.3 11 1.5 42 2.3 Last haematological malignancy treatment immediately before COVID-19 onset No treatment 85 8.5 4 3.4 95 12.8 184 9.9 alloHSCT 65 6.5 6 5.1 32 4.3 103 5.5 In the last 6 months 32 3.2 1 0.9 14 1.9 47 2.5 >6 months 32 3.2 5 4.3 18 2.4 55 3.0 Unknown 1 0.1 0 0.0 0 0.0 1 0.1 (Table 1 continues on next page) www.thelancet.com Vol 58 April, 2023 7 Articles Directed treatment p value N/R p value No treatment/non-SARS- Overall other than N/R N/R vs other N/R vs no/other CoV-2 directed treatment non-directed tx directed treatment n % n % n % n % (Continued from previous page) autoHSCT 16 1.6 5 4.3 5 0.7 26 1.4 In the last 6 months 13 1.3 3 2.6 4 0.5 20 1.1 >6 months 3 0.3 2 1.7 1 0.1 6 0.3 CAR-T 11 1.1 1 0.9 3 0.4 15 0.8 In the last 6 months 4 0.4 0 0.0 2 0.3 6 0.3 >6 months 7 0.7 1 0.9 1 0.1 9 0.5 Conventional chemotherapy 300 30.0 26 22.2 209 28.2 535 28.8 In the last month 129 12.9 10 8.5 82 11.1 221 11.9 In the last 3 months 146 14.6 13 11.1 92 12.4 251 13.5 >3 months 20 2.0 3 2.6 35 4.7 58 3.1 Unknown 5 0.5 0 0.0 0 0.0 5 0.3 Demethylating agents 57 5.7 7 6.0 41 5.5 105 5.6 In the last month 43 4.3 5 4.3 34 4.6 82 4.4 In the last 3 months 11 1.1 0 0.0 6 0.8 17 0.9 >3 months 3 0.3 0 0.0 1 0.1 4 0.2 Unknown 0 0.0 2 1.7 0 0.0 2 0.1 Immuno-chemotherapy 351 35.1 49 41.9 238 32.1 638 34.3 In the last month 229 22.9 34 29.1 156 21.1 419 22.5 In the last 3 months 42 4.2 5 4.3 24 3.2 71 3.8 >3 months 79 7.9 10 8.5 57 7.7 146 7.9 Unknown 1 0.1 0 0.0 1 0.1 2 0.1 Immunotherapy 46 4.6 1 0.9 34 4.6 81 4.4 In the last month 25 2.5 1 0.9 17 2.3 43 2.3 In the last 3 months 10 1.0 0 0.0 6 0.8 16 0.9 >3 months 9 0.9 0 0.0 11 1.5 20 1.1 Unknown 2 0.2 0 0.0 0 0.0 2 0.1 Supportive measures 16 1.6 5 4.3 19 2.6 40 2.2 In the last month 3 0.3 1 0.9 1 0.1 5 0.3 In the last 3 months 2 0.2 0 0.0 0 0.0 2 0.1 >3 months 1 0.1 0 0.0 0 0.0 1 0.1 Unknown 10 1.0 4 3.4 18 2.4 32 1.7 Targeted therapy 183 18.3 23 19.7 147 19.8 353 19.0 In the last month 138 13.8 21 17.9 116 15.7 275 14.8 In the last 3 months 19 1.9 0 0.0 9 1.2 28 1.5 >3 months 17 1.7 0 0.0 16 2.2 33 1.8 Unknown 9 0.9 2 1.7 6 0.8 17 0.9 Neutrophils at COVID-19 onset 0.704 0.708 <501 91 9.1 8 6.8 29 3.9 128 6.9 501–999 58 5.8 6 5.1 33 4.5 97 5.2 >999 758 75.7 91 77.8 459 61.9 1308 70.4 Lymphocytes at COVID-19 onset 0.044 0.180 <201 124 12.4 9 7.7 22 3.0 155 8.3 201–499 166 16.6 12 10.3 57 7.7 235 12.6 >499 618 61.7 84 71.8 436 58.8 1138 61.2 SARS-CoV-2 vaccination status at COVID-19 onset Overall days from last dose 127 (73–203) <0.001 174 (121–235) <0.001 116 (70–191) 126 (75–201) administration to COVID-19 onset [2–532] [14–482] [3–372] [2–532] Number of doses 0.003 0.040 Not vaccinated 258 25.8 23 19.7 148 20.0 429 23.1 One dose 32 3.2 3 2.6 27 3.6 62 3.3 Days from last dose 231 (123–275) 110 (23–394) 163 (108–247) 195.5 (110–258) administration to COVID-19 [5–461] [23–394] [6–368] [5–461] onset (Table 1 continues on next page) 8 www.thelancet.com Vol 58 April, 2023 Articles Directed treatment p value N/R p value No treatment/non-SARS- Overall other than N/R N/R vs other N/R vs no/other CoV-2 directed treatment non-directed tx directed treatment n % n % n % n % (Continued from previous page) Two doses 208 20.8 15 12.8 165 22.3 388 20.9 Days from last dose 233 (161–276) 305 (166–365) 198 (141–244) 212 (153–267) administration to COVID-19 [8–425] [39–482] [7–355] [7–482] onset Three doses 454 45.4 61 52.1 351 47.4 866 46.6 Days from last dose 97 (57–134) 155 (111–190) 90 (56–123) 98 (59–135) administration to COVID-19 [2–532] [14–286] [3–372] [2–532] onset Four doses 49 4.9 15 12.8 50 6.7 114 6.1 Days from last dose 188 (155–216) 234 (197–260) 197 (164.5–234) 193 (161–234) administration to COVID-19 [94–297] [104–295] [84–293] [84–297] onset Type of last vaccine mRNA 683 68.2 92 78.6 547 73.8 1322 71.1 BioNTech/Pfizer 548 54.7 75 64.1 408 55.1 1031 55.5 Moderna COVE 135 13.5 17 14.5 139 18.8 291 15.7 Vector-based 38 3.8 1 0.9 39 5.3 78 4.2 AstraZeneca Oxford 29 2.9 1 0.9 18 2.4 48 2.6 Sputnik 5 0.5 0 0.0 6 0.8 11 0.6 J&J - Janssen 4 0.4 0 0.0 15 2.0 19 1.0 Inactivated 18 1.8 1 0.9 5 0.7 24 1.3 CoronaVac | Sinovac 5 0.5 0 0.0 1 0.1 6 0.3 Sinopharm 13 1.3 1 0.9 4 0.5 18 1.0 This table includes patients from institutions worldwide. alloHSCT, allogeneic hematopoietic stem-cell transplantation; autoHSCT, autologous hematopoietic stem-cell transplantation; CAR-T, chimeric antigen receptor T cells; COVE, coronavirus efficacy; COVID-19, coronavirus 2019 disease; J&J, Johnson and Johnson; mRNA, messenger ribonucleic acid; N/R, nirmatrelvir/ritonavir; PH, Philadelphia; tx, treatment. Reasons for no vaccination in nirmatrelvir/ritonavir: unknown (n = 23, 100.0%). Reasons for no vaccination in other SARS-CoV-2-directed drugs: unknown (n = 216, 83.7%), patient refusal (n = 24, 9.3%), ongoing malignancy treatment (n = 14, 5.4%), and other reasons (n = 4, 1.6%). Reasons for no vaccination in non-SARS-CoV-2-directed drugs: unknown (n = 129, 87.2%), patient refusal (n = 14, 9.5%), ongoing malignancy treatment (n = 4, 2.7%), and other reasons (n = 1, 0.7%). Table 1: Baseline characteristics of EPICOVIDEHA patients after licensing of nirmatrelvir/ritonavir. proportion to other patients (other directed drugs levels at COVID-19 onset (p < 0.001), number of vaccine n = 405/1001, p = 0.921; no targeted drugs n = 255/741, doses (p = 0.047), and symptoms at COVID-19 onset p = 0.176). As compared to patients receiving other (p = 0.001, Table 4, Supplementary Table S2). directed drugs against SARS-CoV-2, patients receiving COVID-19 was diagnosed after a median of 174 days nirmatrelvir/ritonavir had a lower proportion of chronic (IQR 121–235) since last vaccination. Thirteen (11.1%) pulmonary diseases (n = 5/117, 4.3% versus n = 116/ patients out of 117 remained asymptomatic during the 1001, 11.6%, p = 0.017), obesity (n = 1/117, 0.9% versus entire COVID-19 episode, whereas 38/117 (32.5%) had n = 73/1001, 7.3%, p = 0.005) and renal impairment mild symptoms, 60/117 (51.3%) progressed to severe (n = 2/117, 1.7% versus n = 67/1001, 6.7%, p = 0.039). disease, and 6/117 (5.1%) to a critical condition No significant differences were observed between pa- (Table 2). tients with nirmatrelvir/ritonavir and those with no In unmatched patients with directed drugs other treatment/non-SARS-CoV-2 directed treatment. Up to than nirmatrelvir/ritonavir, there were similar percent- 80.3% (n = 94/117) had received at least one anti-SARS- ages of asymptomatic (n = 145/1001, 14.5%) and CoV-2 vaccine dose preceding infection onset, a higher severely sick patients (556/1001, 55.5%), but fewer mild frequency than the 74.2% (n = 743/1001) in patients infections (176/1001, 17.6%) and more critical evolu- with other directed drugs (p = 0.003). Compared to pa- tions (124/1001, 12.4%) (p < 0.001). Patients with no tients with no treatment/non-SARS-CoV-2 directed treatment or no SARS-CoV-2 directed drugs, had a treatment, patients with nirmatrelvir/ritonavir had higher rate of asymptomatic courses (n = 211/741, received more frequently four vaccine doses (n = 15/ 28.5%), and lower rates of mild (n = 185/741, 25.0%), 117, 12.8% versus n = 50/741, 6.7%, p = 0.040, Tables 1 severe (n = 327/741, 44.1%) and critical infections and 2). After matching, statistically significant differ- (n = 18/741, 2.4%) than patients with nirmatrelvir/ri- ences were observed between patients in lymphocyte tonavir (p < 0.001). After matching the patients by sex, www.thelancet.com Vol 58 April, 2023 9 Articles Directed treatment p value N/R p value No treatment/non-SARS-CoV-2 Overall other than N/R N/R vs N/R vs no/other directed treatment other non-directed tx n % n % n % % n directed treatment SARS-CoV-2 variant of concern 0.139 1.000 Wild type 1 0.1 0 0.0 1 0.1 2 0.1 Delta 7 0.7 0 0.0 1 0.1 8 0.4 Omicron 479 47.9 44 37.6 281 37.9 804 43.2 Not tested 514 51.3 73 62.4 458 61.8 1045 56.2 Symptoms at COVID-19 onset 0.001 <0.001 Pulmonary 145 14.5 34 29.1 220 29.7 399 21.5 Pulmonary + extrapulmonary 176 17.6 32 27.4 121 16.3 329 17.7 Extrapulmonary 556 55.5 38 32.5 178 24.0 772 41.5 Screening 124 12.4 13 11.1 222 30.0 359 19.3 COVID-19 infection <0.001 <0.001 Asymptomatic 145 14.5 13 11.1 211 28.5 369 19.8 Mild infection 176 17.6 38 32.5 185 25.0 399 21.5 Severe infection 556 55.5 60 51.3 327 44.1 943 50.7 Critical infection 124 12.4 6 5.1 18 2.4 148 8.0 Stay during COVID-19 episode <0.001 <0.001 Home 264 26.4 59 50.4 554 74.8 877 47.2 Hospital 736 73.5 56 47.9 182 24.6 974 52.4 Overall days of hospital stay 12 (7–21) [1–135] <0.001 8 (1–15) [1–57] 0.975 7 (2–15) [1–118] 11 (6–20) [1–135] ICU admission 124 12.4 0.021 6 5.1 0.124 18 2.4 148 8.0 Overall days in ICU 9 (5–14) [1–68] 0.609 7 (3–11) [2–32] 0.323 3 (2–11) [1–24] 9 (4–14) [1–68] COVID-19 treatment Days under COVID-19 treatment 2 (1–4) [1–34] 4 (4–5) [1–24] 4 (1–4) [1–34] Days under nirmatrelvir/ritonavir 4 (4–5) [1–10] 4 (4–5) [1–10] treatment Days from COVID-19 onset to 1 (0–3) [0–151] 1 (0–3) [0–151] nirmatrelvir/ritonavir treatment Type of treatment No treatment administered 0 0.0 0 0.0 741 100.0 741 39.9 Antiviral + monoclonal antibody ± corticosteroids ± plasma 141 14.1 0 0.0 0 0.0 141 7.6 Antiviral ± corticosteroids ± plasma 293 29.3 0 0.0 0 0.0 293 15.8 Corticosteroids 242 24.2 0 0.0 0 0.0 242 13.0 Monoclonal antibodies ± plasma ± corticosteroids 305 30.5 0 0.0 0 0.0 305 16.4 Nirmatrelvir combination therapy ± corticosteroids ± plasma 0 0.0 24 20.5 0 0.0 24 1.3 1st line 0 0.0 7 6.0 0 0.0 7 0.4 Other line 0 0.0 17 14.5 0 0.0 17 0.9 Nirmatrelvir monotherapy ± corticosteroids ± plasma 0 0.0 93 79.5 0 0.0 93 5.0 1st line 0 0.0 93 79.5 0 0.0 93 5.0 Plasma ± corticosteroids 20 2.0 0 0.0 0 0.0 20 1.1 Outcome 0.027 0.016 Days from COVID-19 onset to 26 (12–47) [0–219] 35 (16–64) 27 (12–46) [0–214] 27 (13–48) [0–219] final day of follow up/death [0–191] Alive 853 85.2 0.023 109 93.2 0.666 701 94.6 1663 89.5 Dead 148 14.8 8 6.8 40 5.4 196 10.5 Days from COVID-19 onset to 29 (14–51) [0–219] 35 (15–63) 28 (13–46) [0–214] 29 (14–50) [0–219] final day of follow up [0–191] Days from COVID-19 onset to 16 (8–28) [0–109] 48.5 (28.5–83) 12 (4–25) [0–127] 16 (7–30) [0–156] death [14–156] (Table 2 continues on next page) 10 www.thelancet.com Vol 58 April, 2023 Articles Directed treatment p value N/R p value No treatment/non-SARS-CoV-2 Overall other than N/R N/R vs N/R vs no/other directed treatment other non-directed tx n % n % n % % n directed treatment (Continued from previous page) Reason for death 0.177 0.588 COVID-19 84 8.4 2 1.7 17 2.3 103 5.5 COVID-19 + hematological malignancy 46 4.6 4 3.4 11 1.5 61 3.3 Hematological maligancies +/− other reasons 14 1.4 2 1.7 9 1.2 25 1.3 Other reasons 4 0.4 0 0.0 3 0.4 7 0.4 This table includes patients from institutions worldwide. COVID-19, coronavirus 2019 disease; ICU, intensive care unit; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2. Table 2: Characteristics of COVID-19 episodes. age (±10 years), baseline haematological malignancy, Discussion haematological malignancy status at COVID-19 onset, Of 1859 patients with haematological malignancy and origin continent (Europe), those with directed drugs registered in EPICOVIDEHA since the licensing of other than nirmatrelvir/ritonavir remained with a nirmatrelvir/ritonavir, 117 (6.3%) received the drug to higher prevalence of critical COVID-19 episodes prevent complicated courses of COVID-19.8 Patients (p < 0.001, Table 1, Table 2, Table 4, Supplementary with extrapulmonary symptoms at COVID-19 onset and Table S2). those who had received a 2nd booster dose of an mRNA Overall, nirmatrelvir/ritonavir was administered with vaccine were more likely to receive nirmatrelvir/ritona- similar frequencies to hospital in-patients (n = 59/117, vir. Recipients of nirmatrelvir/ritonavir had a signifi- 50.4%) and out-patients (n = 56/117, 47.9%). However, cantly lower mortality rate than patients with other when analysing results by country, this significantly treatment approaches. Additionally, we aimed to differed, being more common for outpatients in Italy discover factors associated with mortality in patients (n = 48/59, 81.4%) versus (n = 11/59, 18.6%) in-patients receiving nirmatrelvir/ritonavir for the COVID-19 rather than in Spain (24/29, 82.8% hospital versus n = 5/ treatment, although none was observed as significant, 29, 17.2% home, p < 0.001, Fig. 1B). Of the 56/117 potentially linked to the reduced sample size and overall (47.9%) patients admitted to hospital, 6/117 (10.7%) mortality rate. required intensive care. In patients with other directed Patients with chronic pulmonary diseases and drugs, both hospitalization (n = 736/1001, 73.5%, obesity were less likely to receive nirmatrelvir/ritonavir, p < 0.001) and intensive care (n = 124/1001, 12.4%, although precisely these are patients at risk of devel- p = 0.02) were significantly more frequent. On the con- oping more severe COVID-19,20 and therefore being the trary, patients with no treatment/non-SARS-CoV-2 most appropriate candidates for nirmatrelvir/ritonavir directed treatment were less frequently in-hospital administration even in the absence of haematological (n = 182/741, 24.6%, p < 0.001), although similarly malignancy.15–17 This apparent underuse of nirmatrelvir/ treated in intensive care (n = 18/741, 2.4%, p = 0.12, ritonavir may have multiple reasons explaining such Table 2, Table 4, Supplementary Table S2). results: lack of stock in hospital pharmacies and clinical Nirmatrelvir/ritonavir treatment commenced the day practices,21 unawareness on when and how to admin- after COVID-19 diagnosis (median 1, IQR 0–3) and ister it, unidentified obstacles in prescription, or already lasted a median of 4 days (IQR 4–5). Among the 24/117 described adverse events, such us dysgeusia, diarrhoea (20.5%) patients receiving nirmatrelvir/ritonavir in or emboli, or drug–drug interactions.8,22 The perfor- combination with other drugs (9/24 with other antivi- mance of a similar analyses once the drug has been rals, 7/24 with monoclonal antibodies and 8/24 with longer available may show broader use and may provide both) only 17/24 received it as salvage treatment results more in line with the drug recommendations. In (Table 2). parallel, the presence of only extrapulmonary symptoms The overall mortality rate in nirmatrelvir/ritonavir at COVID-19 was associated with nirmatrelvir/ritonavir recipients was 6.8% (n = 8/117), death was attributed to use, following the prescription recommendations COVID-19 in 5.1% (n = 6/8) cases. In the Cox regres- regarding target patients: mild COVID-19 episodes with sion models, no factor stood out to be associated with high-risk for SARS-CoV-2 progression.15–17 Those fully mortality after administration of nirmatrelvir/ritonavir vaccinated including a 2nd booster dose were more (Table 2, Table 5). likely to receive nirmatrelvir/ritonavir. Interpretations www.thelancet.com Vol 58 April, 2023 11 Articles Univariable analysis Multivariable analysis p value OR 95% CI p value OR 95% CI Lower limit Upper limit Lower limit Upper limit Sex Female – – – – Male 0.101 0.725 0.494 1.065 Age 0.521 1.004 0.992 1.016 Comorbidities at COVID-19 onset Chronic cardiopathy 0.906 1.024 0.694 1.511 Chronic pulmonary disease 0.021 0.341 0.136 0.852 0.011 0.261 0.093 0.732 Diabetes mellitus 0.173 0.626 0.319 1.228 Liver disease 0.356 0.572 0.175 1.873 Obesity 0.029 0.110 0.015 0.796 0.027 0.105 0.014 0.776 Renal failure 0.050 0.242 0.059 1.003 0.071 0.265 0.063 1.120 Smoking history 0.316 0.727 0.389 1.357 No comorbidity 0.261 1.250 0.847 1.845 Neutrophils at COVID-19 onset <501 – – – – 501–999 0.774 1.177 0.388 3.565 >999 0.418 1.366 0.642 2.905 Lymphocytes at COVID-19 onset <201 – – – – – – – – 201–499 0.993 0.996 0.407 2.438 0.672 1.219 0.487 3.052 >499 0.085 1.873 0.917 3.824 0.050 2.080 1.000 4.329 Status malignancy at COVID-19 onset Controlled disease – – – – Stable disease 0.289 0.747 0.436 1.281 Active disease 0.105 0.683 0.430 1.083 Unknown 0.487 1.421 0.527 3.833 Baseline malignancy at COVID-19 onset Leukaemia – – – – Lymphoma 0.269 0.777 0.498 1.215 PH negative myeloproliferative diseases 0.480 1.432 0.529 3.881 Plasma cell disorders 0.665 1.120 0.671 1.871 Other haematological malignancies 0.999 0.000 0.000 – Symptoms at COVID-19 onset Pulmonary – – – – – – – – Pulmonary + extrapulmonary 0.908 0.970 0.585 1.611 0.995 1.002 0.570 1.762 Extrapulmonary 0.003 2.102 1.278 3.457 0.001 2.509 1.448 4.347 Screening 0.357 0.732 0.376 1.423 0.740 0.888 0.441 1.789 SARS-CoV-2 vaccination status at COVID-19 onset Not vaccinated – – – – – – – – One dose 0.937 1.052 0.299 3.700 0.654 0.706 0.154 3.233 Two doses 0.539 0.809 0.412 1.590 0.292 0.673 0.322 1.406 Three doses 0.110 1.507 0.911 2.493 0.081 1.618 0.942 2.780 Four doses <0.001 3.434 1.674 7.045 0.002 3.624 1.619 8.109 This table includes patients from institutions worldwide. CI, confidence interval; COVID-19, coronavirus 2019 disease; OR, odds ratio; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2. Table 3: Factors associated with a potential nirmatrelvir/ritonavir administration. range from pockets of patients with access to all man- different vaccination schemes alleviating COVID-19 agement options being very well taken care of (patients course.4,6,23 receiving nirmatrelvir/ritonavir were concentrated in We observed an overall vaccination rate of 76.9%; Western Europe, as opposed to a wider geographical 80.3% in patients receiving nirmatrelvir/ritonavir, spread of patients in the other groups), to effects of 80.0% in those with no treatment/non-SARS-CoV-2 12 www.thelancet.com Vol 58 April, 2023 Articles Directed treatment other than N/R No treatment/non-SARS-CoV-2 p value N/R directed treatment n % n % n % Sex 1.000 Female 44 43.1% 44 43.1% 44 43.1% Male 58 56.9% 58 56.9% 58 56.9% Age 66 (57–74) [21–89] 67 (56–75) [22–88] 67 (58–75) [22–89] 0.913 Comorbidities at COVID-19 onset No comorbidities 39 38.2% 46 45.1% 36 35.3% 0.429 1 comorbidity 32 31.4% 33 32.4% 35 34.3% 2 comorbidities 22 21.6% 21 20.6% 24 23.5% 3 or more comorbidities 9 8.8% 2 2.0% 7 6.9% Chronic cardiopathy 41 40.2% 42 41.2% 38 37.3% 0.874 Chronic pulmonary disease 15 14.7% 5 4.9% 12 11.8% 0.062 Diabetes mellitus 9 8.8% 10 9.8% 9 8.8% 1.000 Liver disease 8 7.8% 3 2.9% 7 6.9% 0.397 Obesity 5 4.9% 1 1.0% 5 4.9% 0.245 Renal impairment 9 8.8% 2 2.0% 5 4.9% 0.097 Smoking history 9 8.8% 10 9.8% 16 15.7% 0.281 Baseline malignancy at COVID-19 onset 1.000 Leukemia 43 42.2% 43 42.2% 43 42.2% Acute myeloid leukemia 12 11.8% 15 14.7% 11 10.8% Chronic myeloid leukemia 3 2.9% 3 2.9% 8 7.8% Acute lymphoid leukemia 9 8.8% 8 7.8% 5 4.9% Chronic lymphoid leukemia 9 8.8% 4 3.9% 9 8.8% Myelodisplastic syndrome 10 9.8% 13 12.7% 10 9.8% Hairy cell leukemia 0 0.0% 0 0.0% 0 0.0% Lymphoma 34 33.3% 34 33.3% 34 33.3% Hodgkin lymphoma 2 2.0% 1 1.0% 4 3.9% Non-Hodgkin lymphoma 32 31.4% 33 32.4% 30 29.4% PH negative myeloproliferative diseases 3 2.9% 2 2.0% 7 6.9% Essential thrombocythemia 0 0.0% 0 0.0% 0 0.0% Myelofibrosis 2 2.0% 2 2.0% 3 2.9% Polycythemia vera 1 1.0% 0 0.0% 1 1.0% Systemic mastocytosis 0 0.0% 0 0.0% 3 2.9% Plasma cell disorders 21 20.6% 21 20.6% 21 20.6% Multiple myeloma 19 18.6% 21 20.6% 19 18.6% Amyloid light-chain amyloidosis 2 2.0% 0 0.0% 2 2.0% Other hematological malignancies 0 0.0% 0 0.0% 0 0.0% Aplastic anemia 0 0.0% 0 0.0% 0 0.0% Status malignancy at COVID-19 onset 1.000 Controlled disease 62 60.8% 62 60.8% 62 60.8% Stable disease 13 12.7% 13 12.7% 13 12.7% Active disease 27 26.5% 27 26.5% 27 26.5% Last hematological malignancy treatment immediately before COVID-19 onset No treatment 12 11.8% 4 3.9% 11 10.8% alloHSCT 10 9.8% 5 4.9% 5 4.9% In the last 6 months 5 4.9% 1 1.0% 3 2.9% >6 months 5 4.9% 4 3.9% 2 2.0% Unknown 0 0.0% 0 0.0% 0 0.0% autoHSCT 2 2.0% 5 4.9% 1 1.0% In the last 6 months 2 2.0% 3 2.9% 0 0.0% >6 months 0 0.0% 2 2.0% 1 1.0% (Table 4 continues on next page) www.thelancet.com Vol 58 April, 2023 13 Articles Directed treatment other than N/R No treatment/non-SARS-CoV-2 p value N/R directed treatment n % n % n % (Continued from previous page) CAR-T 0 0.0% 1 1.0% 0 0.0% In the last 6 months 0 0.0% 0 0.0% 0 0.0% >6 months 0 0.0% 1 1.0% 0 0.0% Conventional chemotherapy 12 11.8% 14 13.7% 16 15.7% In the last month 10 9.8% 8 7.8% 10 9.8% In the last 3 months 2 2.0% 3 2.9% 0 0.0% >3 months 0 0.0% 3 2.9% 6 5.9% Unknown 0 0.0% 0 0.0% 0 0.0% Demethylating agents 10 9.8% 6 5.9% 6 5.9% In the last month 8 7.8% 4 3.9% 6 5.9% In the last 3 months 2 2.0% 0 0.0% 0 0.0% >3 months 0 0.0% 0 0.0% 0 0.0% Unknown 0 0.0% 2 2.0% 0 0.0% Immuno-chemotherapy 38 37.3% 43 42.2% 37 36.3% In the last month 27 26.5% 29 28.4% 27 26.5% In the last 3 months 5 4.9% 4 3.9% 5 4.9% >3 months 6 5.9% 10 9.8% 5 4.9% Unknown 0 0.0% 0 0.0% 0 0.0% Immunotherapy 0 0.0% 1 1.0% 4 3.9% In the last month 0 0.0% 1 1.0% 3 2.9% In the last 3 months 0 0.0% 0 0.0% 1 1.0% >3 months 0 0.0% 0 0.0% 0 0.0% Unknown 0 0.0% 0 0.0% 0 0.0% Supportive measures 0 0.0% 5 4.9% 0 0.0% In the last month 0 0.0% 1 1.0% 0 0.0% In the last 3 months 0 0.0% 0 0.0% 0 0.0% >3 months 0 0.0% 0 0.0% 0 0.0% Unknown 0 0.0% 4 3.9% 0 0.0% Targeted therapy 17 16.7% 18 17.6% 24 23.5% In the last month 15 14.7% 17 16.7% 22 21.6% In the last 3 months 2 2.0% 0 0.0% 1 1.0% >3 months 0 0.0% 0 0.0% 1 1.0% Unknown 0 0.0% 1 1.0% 0 0.0% Neutrophils at COVID-19 onset 0.866 <501 4 3.9% 6 5.9% 3 2.9% 501–999 4 3.9% 5 4.9% 3 2.9% >999 88 86.3% 80 78.4% 76 74.5% Lymphocytes at COVID-19 onset <0.001 <201 15 14.7% 8 7.8% 0 0.0% 201–499 21 20.6% 11 10.8% 9 8.8% >499 60 58.8% 72 70.6% 73 71.6% SARS-CoV-2 vaccination status at COVID-19 onset Overall days from last dose administration to COVID-19 onset 112 (47–173) [2–425] 173 (121–235) [14–482] 104 (57–170) [6–368] <0.001 Number of doses 0.003 Not vaccinated 27 26.5% 20 19.6% 15 14.7% 0.047 § One dose 2 2.0% 2 2.0% 4 3.9% Days from last dose administration to COVID-19 onset 175 (112–237) [112–237] 67 (23–110) [23–110] 191 (55–323) [6–368] Two doses 21 20.6% 14 13.7% 20 19.6% Days from last dose administration to COVID-19 onset 235 (83–276) [20–425] –482 304 (166–364) [39] 208 (135–238) [7–272] Three doses 49 48.0% 52 51.0% 58 56.9% Days from last dose administration to COVID-19 onset 81 (37–125) [2–250] 154 (110–189) [14–286] 84 (51–113) [10–260] (Table 4 continues on next page) 14 www.thelancet.com Vol 58 April, 2023 Articles Directed treatment other than N/R No treatment/non-SARS-CoV-2 p value N/R directed treatment n % n % n % (Continued from previous page) Four doses 3 2.9% 14 13.7% 5 4.9% Days from last dose administration to COVID-19 onset 152 (125–161) [125–161] 231 (197–260) [104–295] 189 (158–193) [127–196] Type of last vaccine mRNA 74 72.5% 80 78.4% 81 79.4% BioNTech/Pfizer 58 56.9% 65 63.7% 59 57.8% Moderna COVE 16 15.7% 15 14.7% 22 21.6% Vector-based 0 0.0% 1 1.0% 5 4.9% AstraZeneca Oxford 0 0.0% 1 1.0% 4 3.9% Sputnik 0 0.0% 0 0.0% 0 0.0% J&J - Janssen 0 0.0% 0 0.0% 1 1.0% Inactivated 1 1.0% 1 1.0% 0 0.0% CoronaVac | Sinovac 0 0.0% 0 0.0% 0 0.0% Sinopharm 1 1.0% 1 1.0% 0 0.0% SARS-CoV-2 variant of concern 0.147 Wild type 1 1.0% 0 0.0% 0 0.0% Delta 1 1.0% 0 0.0% 0 0.0% Omicron 50 49.0% 38 37.3% 40 39.2% Not tested 50 49.0% 64 62.7% 62 60.8% Symptoms at COVID-19 onset 0.001 Pulmonary 35 34.3% 28 27.5% 25 24.5% Pulmonary + extrapulmonary 21 20.6% 30 29.4% 15 14.7% Extrapulmonary 21 20.6% 34 33.3% 30 29.4% Screening 25 24.5% 10 9.8% 32 31.4% COVID-19 infection <0.001 Asymptomatic 20 19.6% 10 9.8% 29 28.4% Mild infection 22 21.6% 34 33.3% 32 31.4% Severe infection 41 40.2% 52 51.0% 40 39.2% Critical infection 19 18.6% 6 5.9% 1 1.0% Stay during COVID-19 episode <0.001 Home 29 28.4% 53 52.0% 72 70.6% Hospital 73 71.6% 48 47.1% 29 28.4% Overall days of hospital stay 14 (7–28) [1–135] 8 (1–15) [1–57] 6 (1–11) [1–52] <0.001 ICU admission 19 18.6% 6 5.9% 1 1.0% <0.001 Overall days in ICU 14 (9–20) [3–54] 7 (3–11) [2–32] (−) [-] 0.160 COVID-19 treatment Days under COVID-19 treatment 2 (1–4) [1–10] 4 (4–5) [1–24] Days under nirmatrelvir/lopinavir treatment 4 (4–5) [1–10] Days from COVID-19 onset to nirmatrelvir/lopinavir 1 (0–3) [0–151] treatment Type of treatment No treatment administered 0 0.0% 0 0.0% 102 100.0% Antiviral + monoclonal antibody ± corticosteroids ± plasma 20 19.6% 0 0.0% 0 0.0% Antiviral ± corticosteroids ± plasma 31 30.4% 0 0.0% 0 0.0% Corticosteroids 21 20.6% 0 0.0% 0 0.0% Monoclonal antibodies ± plasma ± corticosteroids 27 26.5% 0 0.0% 0 0.0% Nirmatrelvir combination therapy ± corticosteroids ± plasma 0 0.0% 23 22.5% 0 0.0% 1st line 0 0.0% 6 5.9% 0 0.0% Other line 0 0.0% 17 16.7% 0 0.0% Nirmatrelvir monotherapy ± corticosteroids ± plasma 0 0.0% 79 77.5% 0 0.0% 1st line 0 0.0% 79 77.5% 0 0.0% Plasma ± corticosteroids 3 2.9% 0 0.0% 0 0.0% (Table 4 continues on next page) www.thelancet.com Vol 58 April, 2023 15 Articles Directed treatment other than N/R No treatment/non-SARS-CoV-2 p value N/R directed treatment n % n % n % (Continued from previous page) Outcome Days from COVID-19 onset to final day of follow up/death 28 (10–30) [1–30] 30 (16–30) [0–30] 28 (12–30) [0–30] 0.197 Day 30 mortality rate 11 10.8% 2 2.0% 6 5.9% 0.036 Days from COVID-19 onset to alive 30 (14–30) [1–30] 30 (16–30) [0–30] 30 (13–30) [0–30] Days from COVID-19 onset to death 10 (6–16) [1–28] 18 (14–22) [14–22] 13 (10–19) [7–21] This table includes patients from European institutions. § Sensitivity analyses on vaccination coverage proportions after propensity score-based matched paired analyses are depicted in Supplementary Table S2. alloHSCT, allogeneic hematopoietic stem-cell transplantation; autoHSCT, autologous hematopoietic stem-cell transplantation; CAR-T, chimeric antigen receptor T cells; COVE, coronavirus efficacy; COVID-19, coronavirus 2019 disease; ICU, intensive care unit; J&J, Johnson and Johnson; mRNA, messenger ribonucleic acid; N/R, nirmatrelvir/ritonavir; PH, Philadelphia; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; tx, treatment. Table 4: Characteristics of patients and COVID-19 episodes after matching by propensity score. directed treatment, and 74.2% in patients with directed A retrospective study from Israel analysed factors drugs other than nirmatrelvir/ritonavir. These vaccina- associated with mortality in patients with high-risk of tion rates are similar to those in the general popula- COVID-19 progression after receiving nirmatrelvir/ tion.24 In line with previous experiences in ritonavir.29 Immunosuppressed patients showed immunosuppressed settings,25 the absence of vaccina- increased mortality, adjusted by different comorbid- tion in our patients was related to an ongoing haema- ities (i.e., cardiovascular disease, chronic kidney dis- tological malignancy treatment or to patient refusal. ease, chronic lung disease, diabetes mellitus, However, in the majority of them it was unknown the malignancy in the prior year, or neurological disease), rationale. Specific studies analysing the vaccination but the authors did not differentiate haematologic coverage in patients with an increased risk for COVID- malignancy from other causes of immunosuppression. 19-associated mortality could help to understand and Interestingly we did not identify factors associated with overcome this situation, facilitating a close-to-full mortality. The high rate of vaccinated patients may vaccination in haematological malignancy patients. have reduced death rates even in our immunosup- With these data, one could elucidate that the variables pressed population. The 6.8% mortality rate in nir- included in the propensity score-based matching per- matrelvir/ritonavir recipients, much lower than in formed in our analysis (sex, age (±10 years), baseline previously reported populations without vaccination haematological malignancy, haematological malignancy (31.2%)5 or including pre-nirmatrelvir/ritonavir cases4 status at COVID-19 onset, and origin continent (9.2%), jeopardises the performance of further mor- [Europe]) has made the treatment groups very homo- tality analyses. geneous and comparable, not only in the matching Our study has some limitations. The retrospective variables, but also in the vaccination coverage. Addi- design may intrinsically yield lower data quality, and tionally, the fact that all the patients were diagnosed in the sample size is large by comparison to published 2022 has facilitated a higher coverage. In order to see studies, but still too small to allow additional sub- more detailed reasons, we may need to look patient to group comparisons. We do not capture the actual patient and thus, the heterogenicity of the results to be antineoplastic treatment days and doses limiting an- potentially obtained could have a very poor significance. alyses of drug–drug interactions with ritonavir.26 Further analysis may need to focus on this aspect and Finally, we have been unable to detect which factors we will definitely keep in mind in our prospective are associated with mortality. Further analyses with a research. larger sample size collecting more variables, Surprisingly, the patients in our sample received nir- including laboratory values, might overcome these matrelvir/ritonavir for a median of only four days, one limitations. day less than the manufacturer recommendations, which In conclusion, patients with extrapulmonary symp- may hint towards general shortage of the drug.15,16 Other toms at COVID-19 onset and a 2nd vaccine dose are potential reasons may be drug–drug interactions,26,27 more prone to receive nirmatrelvir/ritonavir as opposed adverse effects22 or prompt recovery of symptoms. Addi- to those with chronic pulmonary disease and obesity. tionally, storage and supply restrictions,21 which can Despite mortality in patients with nirmatrelvir/ritonavir potentially end in a distribution of available doses among is lower as compared to that in other treatment more patients than recommended, and difficulties in the schemes, no statistical significance was observed. Thus, access to the compound,28 might have interfered with the further analyses are needed to depict the factors asso- correct number of administration days. ciated to this observation. 16 www.thelancet.com Vol 58 April, 2023 Articles Fig. 2: Survival probability by COVID-19 treatment strategy. A) Summarised treatment strategies. This table includes patients from European institutions. B) Detailed treatment strategies. This table includes patients from European institutions. www.thelancet.com Vol 58 April, 2023 17 Articles Univariable analysis Multivariable analysis p value HR 95% CI p value HR 95% CI Lower limit Upper limit Lower limit Upper limit Sex Female – – – – Male 0.234 2.644 0.533 13.116 Age 0.332 1.029 0.972 1.089 Comorbidities at COVID-19 onset Chronic cardiopathy 0.063 7.479 0.900 62.169 0.092 6.761 0.731 62.532 Chronic pulmonary disease 0.619 0.044 0.000 . Diabetes mellitus 0.056 5.001 0.957 26.126 0.167 4.229 0.547 32.698 Liver disease 0.720 0.046 0.000 . Obesity . . . . Renal failure 0.799 0.048 0.000 . Smoking history 0.626 0.044 0.000 . No comorbidity 0.122 0.191 0.023 1.555 Neutrophils at COVID-19 onset <501 – – – – 501–999 0.642 0.512 0.030 8.614 >999 0.172 0.210 0.022 1.970 Lymphocytes at COVID-19 onset <201 – – – – 201–499 0.640 0.563 0.051 6.249 >499 0.149 0.266 0.044 1.607 Status malignancy at COVID-19 onset Controlled disease – – – – – – – – Stable disease 0.980 0.000 0.000 . 0.950 0.000 0.000 . Active disease 0.064 4.721 0.915 24.354 0.311 2.462 0.431 14.060 Unknown 0.993 0.000 0.000 . 0.995 0.000 0.000 . Baseline malignancy at COVID-19 onset Leukaemia – – – – Lymphoma 0.837 0.863 0.213 3.492 PH negative myeloproliferative diseases 0.989 0.000 0.000 . Plasma cell disorders 0.971 0.000 0.000 . Symptoms at COVID-19 onset Pulmonary – – – – Pulmonary + extrapulmonary 0.966 0.968 0.212 4.419 Extrapulmonary 0.305 0.299 0.030 3.001 Screening 0.988 0.000 0.000 . SARS-CoV-2 vaccination status at COVID-19 onset Not vaccinated – – – – One dose 0.940 . 0.000 . Two doses 0.920 . 0.000 . Three doses 0.924 . 0.000 . Four doses 0.980 1735.991 0.000 . ICU admission 0.106 3.614 0.760 17.178 Nirmatrelvir/ritonavir line Other line – – – – First line 0.997 1.003 0.188 5.349 Days from COVID-19 onset to nirmatrelvir/ritonavir treatment 0.771 1.003 0.980 1.027 Stay during COVID-19 episode Home – – – – Hospital 0.171 4.387 0.528 36.477 This table includes patients from European institutions. CI, confidence interval; COVID-19, coronavirus 2019 disease; HR, hazard ratio; ICU, intensive care unit; PH, Philadelphia; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2. Table 5: Factors associated with mortality in patients with nirmatrelvir/ritonavir administration. 18 www.thelancet.com Vol 58 April, 2023 Articles Contributors 10 Gottlieb RL, Nirula A, Chen P, et al. Effect of bamlanivimab as JSG, FM, LP and OAC contributed to study design and study supervi- monotherapy or in combination with etesevimab on viral load in sion. JSG did the statistical plan and analysis. JSG and OAC interpreted patients with mild to moderate COVID-19: a randomized clinical the data and wrote the paper. All the authors recruited, and documented trial. JAMA. 2021;325(7):632–644. 11 O’Brien MP, Forleo-Neto E, Sarkar N, et al. Effect of subcutaneous participants, critically read, reviewed, and agreed to publish the Casirivimab and imdevimab antibody combination vs placebo on manuscript. development of symptomatic COVID-19 in early asymptomatic SARS-CoV-2 infection: a randomized clinical trial. JAMA. Data sharing statement 2022;327(5):432–441. Data are available upon reasonable request to the corresponding authors 12 Kim JY, Sandulescu O, Preotescu LL, et al. A randomized clinical trial of regdanvimab in high-risk patients with mild-to-moderate Dr. Jon Salmanton-García (jon.salmanton-garcia@uk-koeln.de) or Prof. coronavirus disease 2019. Open Forum Infect Dis. 2022;9(8):ofac406. Dr. Oliver A. Cornely (oliver.cornely@uk-koeln.de). 13 Group AC-TfIwC-S. Efficacy and safety of two neutralising mono- clonal antibody therapies, sotrovimab and BRII-196 plus BRII-198, Declaration of interests for adults hospitalised with COVID-19 (TICO): a randomised The authors do not declare conflicts of interest related to the submitted controlled trial. Lancet Infect Dis. 2022;22(5):622–635. manuscript. The funder of the study had no role in study design, data 14 Group AC–TfIwC- S. Tixagevimab-cilgavimab for treatment of pa- analysis, interpretation, or writing of the report. All authors had full tients hospitalised with COVID-19: a randomised, double-blind, access to the data and had final responsibility for the decision to submit phase 3 trial. Lancet Respir Med. 2022;10(10):972–984. 15 U.S. Food and Drug Administration. Fact sheet for healthcare for publication. providers: emergency use authorization for paxlovid. https://www. fda.gov/media/155050/download; 2022. Accessed October 8, 2022. Acknowledgments 16 European Medicine Agency. Paxlovid. https://www.ema.europa.eu/ The authors thank all participating institutions for their utmost contri- en/medicines/human/EPAR/paxlovid; 2022. Accessed October 8, butions and support to the project during a pandemic situation. In 2022. 17 Cesaro S, Ljungman P, Mikulska M, et al. Recommendations for addition, we would like to express our gratitude to Professor Francisco the management of COVID-19 in patients with haematological Javier Martín-Vallejo (Department of Statistics, Faculty of Medicine, malignancies or haematopoietic cell transplantation, from the 2021 University of Salamanca, Salamanca, Spain) for his guidance in per- European Conference on Infections in Leukaemia (ECIL 9). Leu- forming the statistical analyses of this manuscript. EPICOVIDEHA has kemia. 2022;36(6):1467–1480. received funds from Optics COMMIT (COVID-19 Unmet Medical 18 Sun F, Lin Y, Wang X, Gao Y, Ye S. 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