Tixagevimab-cilgavimab (AZD7442) for the treatment of patients hospitalized with COVID-19 (DisCoVeRy): A phase 3, randomized, double-blind, placebo-controlled trial
Authors: Maya Hites, Clément R. Massonnaud, Eva Larranaga Lapique, Drifa Belhadi, Simon Jamard, François Goehringer, François Danion, Jean Reignier, Nathalie de Castro, Denis Garot, Karine Lacombe, Violaine Tolsma, Emmanuel Faure, Denis Malvy, Thérèse Staub, Johan Courjon, France Cazenave-Roblot, Anne Ma Dyrhol Riise, Paul Leturnier, Guillaume Martin-Blondel, Claire Roger, Karolina Akinosoglou, Vincent Le Moing, Lionel Piroth, Pierre Sellier, Xavier Lescure, Marius Trøseid, Philippe Clevenbergh, Olav Dalgard, Sébastien Gallien, Marie Gousseff, Paul Loubet, Fanny Vardon-Bounes, Clotilde Visée, Leila Belkhir, Élisabeth Botelho-Nevers, André Cabié, Anastasia Kotanidou, Fanny Lanternier, Elisabeth Rouveix-Nordon, Susana Silva, Guillaume Thiery, Pascal Poignard, Guislaine Carcelain, Alpha Diallo, Noémie Mercier, Vida Terzic, Maude Bouscambert-Duchamp, Alexandre Gaymard, Mary-Anne Trabaud, Grégory Destras, Laurence Josset, Nicolas Billard, Thi-Hong-Lien Han, Jérémie Guedj, Sandrine Couffin-Cadiergues, Aline Dechanet, Christelle Delmas, Hélène Esperou, Claire Fougerou-Leurent, Soizic Le Mestre, Anabelle Métois, Marion Noret, Isabelle Bally, Sebastián Dergan-Dylon, Sarah Tubiana, Ouifiya Kalif, Nathalie Bergaud, Benjamin Leveau, Joe Eustace, Richard Greil, Edit Hajdu, Monika Halanova, Jose-Artur Paiva, Anna Piekarska, Jesus Rodriguez Baño, Kristian Tonby, Milan Trojánek, Sotirios Tsiodras, Serhat Unal, Charles Burdet, Dominique Costagliola, Yazdan Yazdanpanah, Nathan Peiffer-Smadja, France Mentré, Florence Ader
Journal: Journal of Infection (2024)

Dear Editor, We read with great interest the recent article by Kamboj et al., in which they described the risk of developing moderate to severe Coronavirus Disease 2019 (COVID-19) in patients with hematological malignancies receiving tixagevimab-cilgavimab (T-C) during a period in which the dominant circulating variants of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) were resistant to T-C.1Kamboj M. Laracy J.C. Usiak S. Babady N.E. Yan J. Seo S.K. Outcomes of hematologic malignancy patients with SARS-CoV-2 breakthrough infections after tixagevimab-cilgavimab during community transmission of monoclonal antibody resistant variants.J Infect. 2023 Sep; 87: 282-285Abstract Full Text Full Text PDF PubMed Google Scholar The authors highlight the ongoing need to urgently address the mAb treatment gap, particularly for immunocompromised patients. The unmet need is further highlighted by the DisCoVeRy Phase 3, adaptive, multicenter European, randomized, double-blind, superiority trial that evaluated the efficacy and safety of intravenous T-C in SARS-CoV-2 antigenic positive patients (i.e. those with a high SARS-CoV-2 viral load) hospitalized with COVID-19 and followed-up to day 90. In the ambulatory setting, and while ancestral strains were circulating, the administration of intramuscular T-C to treat SARS-CoV-2 infections significantly reduced the risk of hospitalization and death in patients at risk for disease progression, compared to placebo.2Montgomery H. Hobbs F.D.R. Padilla F. Arbetter D. Templeton A. Seegobin S. et al.Efficacy and safety of intramuscular administration of tixagevimab–cilgavimab for early outpatient treatment of COVID-19 (TACKLE): a phase 3, randomised, double-blind, placebo-controlled trial.Lancet Respir Med. 2022; 10: 985-996Abstract Full Text Full Text PDF PubMed Scopus (129) Google Scholar In the hospital setting, the double-blinded, placebo-controlled ACTIV-3-TICO trial evaluating T-C in 1417 patients with COVID-19, with >50% of participants infected with the Delta variant, demonstrated that treatment with T-C was associated with a 30% relative risk reduction in mortality (9% vs. 12%; hazard ratio [HR] 0.70 [95% confidence interval (CI) 0.50–0.97]; p = 0.032) through day 90.3Holland T.L. Ginde A.A. Paredes R. Murray T.A. Engen N. Grandits G. et al.Tixagevimab–cilgavimab for treatment of patients hospitalised with COVID-19: a randomised, doubleblind, phase 3 trial.Lancet Respir Med. 2022; 10: 972-984Abstract Full Text Full Text PDF PubMed Scopus (67) Google Scholar The EU DisCoVeRy placebo-controlled trial (NCT04315948) began enrolling on April 28, 2021, after these trials were initiated (January 28, 2021, and February 10, 2021, respectively) and aimed to confirm efficacy and safety data in hospitalized COVID-19 patients during a later stage of the pandemic when the natural evolution of SARS-CoV-2 strains had led to the emergence of variants of concern (VOC), and mass vaccination campaigns had been ramped up worldwide.4Carabelli A.M. Peacock T.P. Thorne L.G. Harvey W.T. Hughes J. COVID-19 Genomics UK Consortium et al.SARS-CoV-2 variant biology: immune escape, transmission and fitness.Nat Rev Microbiol. 2023; ([cited November 3, 2023]; Available from: 〈https://www.nature.com/articles/s41579-022-00841-7〉)Crossref Scopus (326) Google Scholar In DisCoVeRy, participants were randomly assigned (1:1) to receive placebo or T-C in addition to standard of care (SoC), not including remdesivir. The primary outcome was the clinical status at day 15 measured by the WHO seven-point ordinal scale. Clinical, virological, immunological and safety endpoints were also assessed. In the context of in-vitro evidence showing loss of neutralization activity against emerging VOC,5Touret F. Giraud E. Bourret J. Donati F. Tran-Rajau J. Chiaravalli J. et al.Enhanced neutralization escape to therapeutic monoclonal antibodies by SARS-CoV-2 omicron sublineages.iScience. 2023; 26106413Abstract Full Text Full Text PDF PubMed Scopus (14) Google Scholar, 6Takashita E. Yamayoshi S. Simon V. Van Bakel H. Sordillo E.M. Pekosz A. et al.Efficacy of antibodies and antiviral drugs against Omicron BA.2.12.1, BA.4, and BA.5 subvariants.N Engl J Med. 2022; 387: 468-470Crossref PubMed Scopus (187) Google Scholar enrollment slowed down until recruitment was stopped on July 1, 2022, before reaching the pre-determined targeted sample size of 1240 patients. As shown in Table 1, the antigen positive modified intention-to-treat population (mITT) included 173 participants randomized to T-C (n = 91) or placebo (n = 82), among whom 91.9% (159/173) needed supplementary oxygen, 19.6% (24/173) were immunocompromised, and 47.4% (82/173) were previously vaccinated against SARS-CoV-2 at inclusion. There was no difference in the distribution of the WHO ordinal scale at day 15 between the two groups (odds ratio (OR) 0.93, 95%CI [0.54–1.61]; p = 0.81) nor in any clinical, virological or safety secondary endpoints (Fig. 1). In the global mITT population (n = 226), neutralization antibody titers were significantly higher in the T-C recipients compared to placebo at day 3 (least-square mean differences (LSMD) 1.44, 95%CI [1.20–1.68]; p < 10−23) and day 8 (LSMD 0.91, 95%CI [0.64–1.18]; p < 10−8) and it was greatest for patients infected with a pre-Omicron variant, both at day 3 (LSMD 1.94, 95% CI [1.67–2.20], p < 10−25) and day 8 (LSMD 1.17, 95% CI [0.87–1.47], p < 10−9), with a significant interaction (p < 10−7 and p = 0.01 at days 3 and 8, respectively). A total of 178 adverse events (AEs), including 90 serious AEs (SAEs) were reported, of which 28 (31.1%) were considered related to the investigational medicinal product. In the T-C group, 51/123 (41.5%) patients had at least one AE, 30/123 (24.4%) had at least one grade 3 or 4 AE, and 28/123 (22.8%) had at least one SAE, against 45/103 (43.7%), 33 (32.0%), and 32 (31.1%) in the control group (p = 0.70, 0.18, and 0.13), respectively. Among 19 fatal SAEs, none were of cardiac origin. Complete results and all supporting documents are available on medRxiv (doi: 10.1101/2024.02.23.24302586).Table 1Baseline characteristics, clinical endpoints, and safety of participants in the antigen positive and global modified intention-to-treat populations, overall and according to the treatment group.Antigen positive (N = 173)Global (N = 226)OverallTixagevimab-cilgavimabPlaceboEffect measureOverallTixagevimab-cilgavimabPlaceboEffect measure(N = 173)(N = 91)(N = 82)(95% CI)(N = 226)(N = 123)(N = 103)(95% CI)Baseline characteristicsMedian age, years66.0 [55.0–79.0]65.0 [56.0–80.0]66.5 [55.0–78.0]66.0 [53.0–76.0]64.0 [53.0–76.0]68.0 [52.0–76.0]Sex male,117 (67.6%)56 (61.5%)61 (74.4%)155 (68.6%)78 (63.4%)77 (74.8%)Number of comorbidities*Denotes variables with missing data. The number of missing data is presented for the antigen positive/the global mITT for each variable, respectively. Data on smoking status (current) were missing in 3/3 participants; data on delay between first laboratory-confirmed SARS-CoV-2 infection and admission date at facility were missing in 1/1 participant; data on delay between first laboratory-confirmed SARS-CoV-2 infection and randomization were missing in 1/1 participant; data on serology test were missing on 2/5 participants; data on variant sequencing were missing in 35/71 participants; data on body weight were missing on 10/11 participants; data on NEWS2 score were missing on 16/20 participants. 038 (22.0%)17 (18.7%)21 (25.6%)52 (23.0%)28 (22.8%)24 (23.3%) 149 (28.3%)26 (28.6%)23 (28.0%)71 (31.4%)38 (30.9%)33 (32.0%) 243 (24.9%)23 (25.3%)20 (24.4%)50 (22.1%)27 (22.0%)23 (22.3%) 325 (14.5%)14 (15.4%)11 (13.4%)32 (14.2%)18 (14.6%)14 (13.6%) >318 (10.4%)11 (12.1%)7 (8.5%)21 (9.3%)12 (9.8%)9 (8.7%)Coexisting condition Chronic cardiac disease62 (35.8%)39 (42.9%)23 (28.0%)72 (31.9%)43 (35.0%)29 (28.2%) Obesity (BMI ≥ 30)46 (26.6%)27 (29.7%)19 (23.2%)63 (27.9%)38 (30.9%)25 (24.3%) Diabetes46 (26.6%)30 (33.0%)16 (19.5%)58 (25.7%)37 (30.1%)21 (20.4%) Current smoker13 (48.1%)6 (42.9%)7 (53.8%)15 (48.4%)7 (46.7%)8 (50.0%) Chronic pulmonary disease (including asthma)43 (24.9%)22 (24.2%)21 (25.6%)53 (23.5%)27 (22.0%)26 (25.2%) Active cancer (including hematological malignancy)23 (13.3%)9 (9.9%)14 (17.1%)30 (13.3%)12 (9.8%)18 (17.5%)Median days from symptoms onset and random assignment*Denotes variables with missing data. The number of missing data is presented for the antigen positive/the global mITT for each variable, respectively. Data on smoking status (current) were missing in 3/3 participants; data on delay between first laboratory-confirmed SARS-CoV-2 infection and admission date at facility were missing in 1/1 participant; data on delay between first laboratory-confirmed SARS-CoV-2 infection and randomization were missing in 1/1 participant; data on serology test were missing on 2/5 participants; data on variant sequencing were missing in 35/71 participants; data on body weight were missing on 10/11 participants; data on NEWS2 score were missing on 16/20 participants., +Only conditions with a relative frequency greater than 10% are displayed in the table.*Denotes variables with missing data. The number of missing data is presented for the antigen positive/the global mITT for each variable, respectively. Data on smoking status (current) were missing in 3/3 participants; data on delay between first laboratory-confirmed SARS-CoV-2 infection and admission date at facility were missing in 1/1 participant; data on delay between first laboratory-confirmed SARS-CoV-2 infection and randomization were missing in 1/1 participant; data on serology test were missing on 2/5 participants; data on variant sequencing were missing in 35/71 participants; data on body weight were missing on 10/11 participants; data on NEWS2 score were missing on 16/20 participants.7.0 [5.0–9.0]7.0 [6.0–9.0]7.0 [5.0–9.0]7.0 [6.0–9.0]8.0 [6.0–9.0]7.0 [5.0–9.0]NEWS2 score*Denotes variables with missing data. The number of missing data is presented for the antigen positive/the global mITT for each variable, respectively. Data on smoking status (current) were missing in 3/3 participants; data on delay between first laboratory-confirmed SARS-CoV-2 infection and admission date at facility were missing in 1/1 participant; data on delay between first laboratory-confirmed SARS-CoV-2 infection and randomization were missing in 1/1 participant; data on serology test were missing on 2/5 participants; data on variant sequencing were missing in 35/71 participants; data on body weight were missing on 10/11 participants; data on NEWS2 score were missing on 16/20 participants.7.0 [5.0–9.0]7.0 [5.0–8.0]7.0 [5.0–9.0]7.0 [5.0–9.0]7.0 [5.0–8.0]6.0 [5.0–9.0]Clinical status 3. Hospitalized, not requiring supplemental oxygen7 (4.0%)5 (5.5%)2 (2.4%)9 (4.0%)6 (4.9%)3 (2.9%) 4. Hospitalized, requiring supplemental oxygen141 (81.5%)71 (78.0%)70 (85.4%)179 (79.2%)93 (75.6%)86 (83.5%) 5. Hospitalized, on non-invasive ventilation or high flow oxygen devices25 (14.5%)15 (16.5%)10 (12.2%)38 (16.8%)24 (19.5%)14 (13.6%)Randomization site Intensive care unit21 (12.1%)15 (16.5%)6 (7.3%)32 (14.2%)21 (17.1%)11 (10.7%) Conventional unit152 (87.9%)76 (83.5%)76 (92.7%)194 (85.8%)102 (82.9%)92 (89.3%)Vaccination initiation (partly or fully)82 (47.4%)43 (47.3%)39 (47.6%)102 (45.1%)56 (45.5%)46 (44.7%)Serology*Denotes variables with missing data. The number of missing data is presented for the antigen positive/the global mITT for each variable, respectively. Data on smoking status (current) were missing in 3/3 participants; data on delay between first laboratory-confirmed SARS-CoV-2 infection and admission date at facility were missing in 1/1 participant; data on delay between first laboratory-confirmed SARS-CoV-2 infection and randomization were missing in 1/1 participant; data on serology test were missing on 2/5 participants; data on variant sequencing were missing in 35/71 participants; data on body weight were missing on 10/11 participants; data on NEWS2 score were missing on 16/20 participants. Negative (anti-N antibodies -and anti-S RBD antibodies -)69 (40.4%)40 (44.4%)29 (35.8%)76 (34.4%)44 (36.4%)32 (32.0%) Positive (anti-N antibodies + or anti-S RBD antibodies +)102 (59.6%)50 (55.6%)52 (64.2%)145 (65.6%)77 (63.6%)68 (68.0%)Variant Omicron on day 1 (imputed)*Denotes variables with missing data. The number of missing data is presented for the antigen positive/the global mITT for each variable, respectively. Data on smoking status (current) were missing in 3/3 participants; data on delay between first laboratory-confirmed SARS-CoV-2 infection and admission date at facility were missing in 1/1 participant; data on delay between first laboratory-confirmed SARS-CoV-2 infection and randomization were missing in 1/1 participant; data on serology test were missing on 2/5 participants; data on variant sequencing were missing in 35/71 participants; data on body weight were missing on 10/11 participants; data on NEWS2 score were missing on 16/20 participants. Pre-Omicron99 (57.2%)52 (57.1%)47 (57.3%)133 (58.8%)70 (56.9%)63 (61.2%) Omicron BA144 (25.4%)25 (27.5%)19 (23.2%)53 (23.5%)32 (26.0%)21 (20.4%) Omicron BA2/520 (11.6%)10 (11.0%)10 (12.2%)22 (9.7%)11 (8.9%)11 (10.7%) Unknown10 (5.8%)4 (4.4%)6 (7.3%)18 (8.0%)10 (8.1%)8 (7.8%)Median normalized viral load in nasopharyngeal swabs at baseline, log10 copies per 10,000 cells‡Undetectable viral load values (i.e. values < 1 log10 copies/10 000 cells) were imputed to 0.7 log10 copies/10 000 cells.4.4 [3.3–5.4]4.4 [3.4–5.3]4.4 [3.3–5.6]4.0 [2.5–5.2]3.9 [2.4–5.1]4.1 [2.7–5.3]Clinical endpoints7-point ordinal scale at day 15 1. Not hospitalized, no limitations on activities35 (20.2%)15 (16.5%)20 (24.4%)OR = 0.93 (0.54–1.61) [p = 0.81]48 (21.2%)20 (16.3%)28 (27.2%)OR = 0.85 (0.52–1.37) [p = 0.50] 2. Not hospitalized, limitation on activities77 (44.5%)45 (49.5%)32 (39.0%)104 (46.0%)63 (51.2%)41 (39.8%) 3. Hospitalized, not requiring supplemental oxygen18 (10.4%)9 (9.9%)9 (11.0%)24 (10.6%)14 (11.4%)10 (9.7%) 4. Hospitalized, requiring supplemental oxygen9 (5.2%)7 (7.7%)2 (2.4%)13 (5.8%)10 (8.1%)3 (2.9%) 5. Hospitalized, on non-invasive ventilation or high flow oxygen devices6 (3.5%)2 (2.2%)4 (4.9%)7 (3.1%)2 (1.6%)5 (4.9%) 6. Hospitalized, on invasive mechanical ventilation or ECMO11 (6.4%)5 (5.5%)6 (7.3%)12 (5.3%)6 (4.9%)6 (5.8%) 7. Death17 (9.8%)8 (8.8%)9 (11.0%)18 (8.0%)8 (6.5%)10 (9.7%)Time to sustained recovery through day 90 (days)22.0 [19.0–27.0]22.0 [19.0–27.5]21.0 [18.0–27.0]HR = 0.98 (0.71–1.36) [p = 0.92]21.0 [18.0–27.0]22.0 [19.0–27.5]21.0 [18.0–27.0]HR = 1.01 (0.77–1.34) [p = 0.93]Days to hospital discharge before day 908.0 [6.0–13.0]8.0 [6.0–11.0]9.0 [5.0–13.0]HR = 1.06 (0.78–1.45) [p = 0.70]8.0 [5.0–13.0]8.0 [5.0–12.0]8.0 [5.0–13.0]HR = 1.10 (0.84–1.43) [p = 0.49]Mortality rate at day 9026 (15.0%)12 (13.2%)14 (17.1%)OR = 0.73 (0.31–1.72) [p = 0.47]28 (12.4%)12 (9.8%)16 (15.5%)OR = 0.56 (0.25–1.28) [p = 0.17]SafetyNumber of patients with at least one adverse event Any adverse events96 (42.5%)51 (41.5%)45 (43.7%)OR = 0.90 (0.53–1.54) [p = 0.70] Any grade 1 adverse events20 (8.8%)12 (9.8%)8 (7.8%) Any grade 2 adverse events29 (12.8%)18 (14.6%)11 (10.7%) Any grade 3 adverse events34 (15.0%)18 (14.6%)16 (15.5%) Any grade 4 adverse events35 (15.5%)14 (11.4%)21 (20.4%) Any grade 1 and 2 adverse events43 (19.0%)25 (20.3%)18 (17.5%) Any grade 3 and 4 adverse events63 (27.9%)30 (24.4%)33 (32.0%)OR = 0.67 (0.37–1.20) [p = 0.18]Number of patients with at least one serious adverse event Any serious adverse events60 (26.5%)28 (22.8%)32 (31.1%)OR = 0.63 (0.35–1.15) [p = 0.13] Any serious adverse events leading to outcome of death19 (8.4%)9 (7.3%)10 (9.7%)Data are median [IQR] or n (%).Analyses were stratified on the vaccination status at randomization and adjusted effect measures are reported in the table. For the ordinal scale results, an odds ratio above 1 is in the direction of tixagevimab-cilgavimab being better than placebo. For time to event analyses, a hazard ratio above 1 is in the direction of tixagevimab-cilgavimab being better than placebo. Estimates are reported with their 95% confidence interval. As per the definition in the protocol, adverse events and serious adverse events do not include disease-related events. CI: confidence interval; OR: odds ratio; HR: hazard ratio; BMI: body mass index; ECMO: extracorporeal membrane oxygenation.* Denotes variables with missing data. The number of missing data is presented for the antigen positive/the global mITT for each variable, respectively. Data on smoking status (current) were missing in 3/3 participants; data on delay between first laboratory-confirmed SARS-CoV-2 infection and admission date at facility were missing in 1/1 participant; data on delay between first laboratory-confirmed SARS-CoV-2 infection and randomization were missing in 1/1 participant; data on serology test were missing on 2/5 participants; data on variant sequencing were missing in 35/71 participants; data on body weight were missing on 10/11 participants; data on NEWS2 score were missing on 16/20 participants.+ Only conditions with a relative frequency greater than 10% are displayed in the table.‡ Undetectable viral load values (i.e. values < 1 log10 copies/10 000 cells) were imputed to 0.7 log10 copies/10 000 cells. Open table in a new tab Data are median [IQR] or n (%). Analyses were stratified on the vaccination status at randomization and adjusted effect measures are reported in the table. For the ordinal scale results, an odds ratio above 1 is in the direction of tixagevimab-cilgavimab being better than placebo. For time to event analyses, a hazard ratio above 1 is in the direction of tixagevimab-cilgavimab being better than placebo. Estimates are reported with their 95% confidence interval. As per the definition in the protocol, adverse events and serious adverse events do not include disease-related events. CI: confidence interval; OR: odds ratio; HR: hazard ratio; BMI: body mass index; ECMO: extracorporeal membrane oxygenation. Although T-C combination was safe and well-tolerated, showing no excess cardiac events, it did not significantly improve patients' clinical status in the DisCoVeRy study, nor accelerate viral clearance, despite a significant increase in neutralizing antibodies against SARS-CoV-2 at days 3 and 8 compared to placebo. The difference with the ACTIV-3-TICO trial concerning mortality is due to the underpowered nature of the DisCoVeRy trial, and possibly amongst other reasons, the changes in infecting SARS-CoV-2 variants. The Delta variant was the predominant one in both trials, but the DisCoVeRy trial enrolled 40% of patients infected with the Omicron variant compared to none in the ACTIV-3-TICO trial.3Holland T.L. Ginde A.A. Paredes R. Murray T.A. Engen N. Grandits G. et al.Tixagevimab–cilgavimab for treatment of patients hospitalised with COVID-19: a randomised, doubleblind, phase 3 trial.Lancet Respir Med. 2022; 10: 972-984Abstract Full Text Full Text PDF PubMed Scopus (67) Google Scholar Indeed, the SARS-CoV-2 Omicron variant and its multiple sub-lineages have proven to be more evasive than the ancestral strain or Delta variant to vaccines and therapeutic mABs, including T-C, as assessed by in-vitro live-virus neutralization assays.5Touret F. Giraud E. Bourret J. Donati F. Tran-Rajau J. Chiaravalli J. et al.Enhanced neutralization escape to therapeutic monoclonal antibodies by SARS-CoV-2 omicron sublineages.iScience. 2023; 26106413Abstract Full Text Full Text PDF PubMed Scopus (14) Google Scholar, 6Takashita E. Yamayoshi S. Simon V. Van Bakel H. Sordillo E.M. Pekosz A. et al.Efficacy of antibodies and antiviral drugs against Omicron BA.2.12.1, BA.4, and BA.5 subvariants.N Engl J Med. 2022; 387: 468-470Crossref PubMed Scopus (187) Google Scholar Infections due to the Omicron variant have overall proven to be less virulent than prior variants, including Delta,7Fan Y. Li X. Zhang L. Wan S. Zhang L. Zhou F. SARS-CoV-2 Omicron variant: recent progress and future perspectives.Signal Transduct Target Ther. 2022; 7: 141Crossref PubMed Scopus (278) Google Scholar however, many patients who did require hospitalization were still at risk of dying, as illustrated by the mortality rate of 15% at day 90 in our trial and the important morbidity described by Kamboj et al.1Kamboj M. Laracy J.C. Usiak S. Babady N.E. Yan J. Seo S.K. Outcomes of hematologic malignancy patients with SARS-CoV-2 breakthrough infections after tixagevimab-cilgavimab during community transmission of monoclonal antibody resistant variants.J Infect. 2023 Sep; 87: 282-285Abstract Full Text Full Text PDF PubMed Google Scholar The early termination of this DisCoVeRy trial, with only 19% of the planned enrollment, is an example of the difficulties to evaluate mAbs in the changing variant landscape of the COVID-19 pandemic. Due to the evolving genomics4Carabelli A.M. Peacock T.P. Thorne L.G. Harvey W.T. Hughes J. COVID-19 Genomics UK Consortium et al.SARS-CoV-2 variant biology: immune escape, transmission and fitness.Nat Rev Microbiol. 2023; ([cited November 3, 2023]; Available from: 〈https://www.nature.com/articles/s41579-022-00841-7〉)Crossref Scopus (326) Google Scholar as well as the increased capacity of the virus for immune escape, vulnerable individuals unable to mount an adequate immune response (e.g. the immunocompromised), remain at risk for severe COVID-19. Consequently, further reflections are needed on how best to evaluate mAbs in the clinical setting to rapidly address this urgent unmet need by bringing new therapeutic options to patients, particularly immunocompromised, while ensuring their safety. Novel approaches for evaluating mAbs include immuno-bridging trials, where humoral and/or cellular immune parameters are evaluated in a controlled trial to establish whether an intervention is effective8European Medical Agency. Summary report of the Joint EMA-FDA workshop on the efficacy of monoclonal antibodies in the context of rapidly evolving SARS-CoV-2 variants [Internet]. [cited November 3, 2023]. Available from: 〈https://www.ema.europa.eu/en/documents/report/summary-report-joint-ema-fdaworkshop-efficacy-monoclonal-antibodies-context-rapidly-evolving-sars_en.pdf〉.Google Scholar and the adoption of a global surveillance system with criteria for in-vitro evaluation of antiviral susceptibility correlated to clinical data.9European Centre for Disease Prevention and Control. SARS-CoV-2 variant mutations conferring reduced susceptibility to antiviral drugs and monoclonal antibodies: a non systematic literature review for surveillance purposes. [Internet]. LU: Publications Office; 2023 [cited November 3, 2023]. Available from: 〈https://data.europa.eu/doi/10.2900/192733〉.Google Scholar Modeling antiviral effects while accounting for vaccination status, SARS-CoV-2 antibody levels, infecting viral strains, and other parameters, may provide better insight into antiviral efficacy of mAbs, as we have previously shown with remdesivir.10Lingas G. Néant N. Gaymard A. Belhadi D. Peytavin G. Hites M. et al.Effect of remdesivir on viral dynamics in COVID-19 hospitalized patients: a modelling analysis of the randomized, controlled, open-label DisCoVeRy trial.J Antimicrob Chemother. 2022; 77: 1404-1412Crossref PubMed Scopus (22) Google Scholar M.H. reports grants from The Belgian Center for Knowledge (KCE), the Fonds Erasme-COVID-Université Libre de Bruxelles and the EU-Horizon program, for the submitted work; and has received support for attending meetings from Pfizer; support for participation on an advisory board for therapeutics on COVID-19; and support for leadership for the Belgian guidelines on therapeutics for COVID-19 and acting as a treasurer for the Belgian Society of Clinical Microbiology and Infectious Diseases. R.G. reports consulting fees from Celgene, Novartis, Roche, Bristol Myers Squibb, Takeda, Abbvie, AstraZeneca, Janssen, Merck Sharp & Dohme, Merck, Gilead, and Daiichi Sankvo; lecture fees from Celgene, Roche, Merck, Takeda, AstraZeneca, Novartis, Amgen, Bristol Myers Squibb, Merck Sharp & Dohme, Sandoz, Abbvie, Gilead, and Daiichi Sankvo; support for attending meetings from Roche, Amgen, Janssen, AstraZeneca, Novartis, Merck Sharp & Dohme, Celgene, Gilead, Bristol Myers Squibb, Abbvie, and Daiichi Sankvo; participation in a Data Safety and Monitoring Board for Celgene, Novartis, Roche, Bristol Myers Squibb, Takeda, Abbvie, AstraZeneca, Janssen, Merck Sharp & Dohme, Merck, Gilead, and Daiichi Sankyo; research grants from Celgene, Roche, Merck, Takeda, AstraZeneca, Novartis, Amgen, Bristol Myers Squibb, Merck Sharp & Dohme, Sandoz, Abbvie, Gilead, and Daiichi Sankyo. J.-A.P. reports consulting fees from Pfizer, Merck Sharp & Dohme, and Janssen-Cilag; lecture fees from Pfizer; and support for attending meetings from Pfizer. D.C. reports grants and lecture fees from Janssen and lecture fees from Gilead, outside the submitted work. C.B. reports participation in a Data Safety and Monitoring Board for 4Living Biotech; and consulting fees from Da Volterra and Mylan Pharmaceuticals, outside the submitted work. F.M. reports grants and consulting fees from Da Volterra, grants from Sanofi, and consulting fees from Ipsen, outside the submitted work. All other authors declare no competing interests. This work received funding from several sources: the European Commission (EU-Response, Grant 101015736), the DIM One Health Île-de-France (R20117HD) and Astra-Zeneca. We thank all participants who consented to enroll in the trial, as well as all study and site staff whose indispensable assistance made the conduct of the DisCoVeRy trial possible (all listed in the appendix, pp 27–36, available on medRxiv, doi: 10.1101/2024.02.23.24302586).