SARS-COV-2 nasopharyngeal viral load change in a multicenter randomized clinical trial comparing early therapies for COVID-19 in non-hospitalized adults with high risk of severe COVID-19 (the MONET TRIAL)

SARS-COV-2 nasopharyngeal viral load change in a multicenter randomized clinical trial comparing early therapies for COVID-19 in non-hospitalized adults with high risk of severe COVID-19 (the MONET TRIAL) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article SARS-COV-2 nasopharyngeal viral load change in a multicenter randomized clinical trial comparing early therapies for COVID-19 in non-hospitalized adults with high risk of severe COVID-19 (the MONET TRIAL) Ilaria Mastrorosa, Alessandro Cozzi-Lepri, Giulia Matusali, Francesca Colavita, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5715907/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Although in vitro studies suggest that neutralization by monoclonal antibodies (mAbs) against SARS CoV2 Omicron sub lineages is reduced, in vivo virological response data are lacking. MONET (EudraCT: 2021-004188-28) was multi-centric phase 4 open-label parallel randomized clinical trial, conducted in Italy over 2022-2023, to assess the efficacy of sotrovimab (SOT), tixagevimab/cilgavimab (TIX/CIL) and Nirmatrelvir/ritonavir (NMV/r), in outpatients at high risk for severe COVID-19. The outcome (secondary in the trial protocol) was SARS-CoV-2 variation in cycle threshold (CT) values over the first 7 days (D1-D7) of the trial. CT variation was compared by trial arms using unadjusted linear regression and after controlling for age. We included 346 individuals: 116 (34%) received SOT, 113 (33%) TIX/CIL, 117 (34%) NMV/r. Main characteristics were balanced across arms. Most of the participants were infected with BA.2 (52%) or BA.4/5 (35.5%). The data carried strong evidence that the mean CT change over D1-D7 was larger in subjects receiving NMV/r vs. the other arms (p<0.001). We found no evidence that viral variant was an effect measure modifier for the contrasts of interest (p=0.14). Our analysis provides strong evidence that NMV/r exerts a greater in vivo antiviral effect than mAbs against Omicron sublineages, confirming previous in vitro data. SARS Coronavirus RCT monoclonal antibodies antiviral agents viral load antibodies response inflammatory markers Figures Figure 1 Figure 2 Figure 3 INTRODUCTION In January 2022, in the Omicron era, both monoclonal antibodies (mAbs) and antiviral agents were available for the early treatment of mild-to-moderate COVID-19 for outpatients at high risk for progression to severe disease. Most of the data supporting their use come from placebo-controlled phase-3 randomized clinical trials (RCTs) that demonstrated a reduced risk of developing severe COVID-19 or death in subjects receiving mAbs such as sotrovimab (SOT) and tixagevimab plus cilgavimab (TIX/CIL), or antivirals such as nirmatrelvir plus ritonavir (NMV/r) 1–3 . However, these studies were conducted in the pre-Omicron phase, and it is likely that the efficacy of treatment against these earlier circulating variants was different. Indeed, SARS-CoV-2 evolution and the specific mutations in the spike protein (the binding target for mAbs) harboured by Omicron sublineages resulted in an evolving escape to in vitro neutralizing activity by mAbs 4 – 7 , with an unclear impact on in vivo treatment response. Conversely, laboratory data show that the protease inhibitor nirmatrelvir, enhanced with ritonavir, seemed to have retained its antiviral activity against various Omicron sublineages 4 , 5 , 8 . For this reason, randomized clinical trials aimed to compare the virological response to available treatments in individuals infected with Omicron strains remain strategically important. In the outpatient setting, because of the low risk of severe outcomes during the Omicron phase of the pandemic, candidate surrogate markers, such as the viral load (VL) reduction in nasopharyngeal swab (NPS) samples, have been typically used in phase-3 studies as a measure of in vivo neutralizing or antiviral activity 9 – 10 . Here we show the results of the analysis of the secondary outcome of the MONET trial, which was designed to compare the efficacy and safety of early treatment with SOT, TIX/CIL, or NMV/r in the setting of a high-risk outpatient population with mild to moderate COVID-19 enrolled in several clinical sites in Italy. MATERIALS AND METHODS Trial design The MONET trial (registration number EudraCT: 2021-004188-28, 13 September 2021) is a multicentric, phase-4, three-arm, superiority, open-label RCT conducted over March 2022-February 2023, to assess the efficacy and safety of 500 mg intravenous SOT (Arm 1), 300/300 mg intramuscular TIX/CIL (Arm 2) and oral 5-days course of NMV/r 300/100 mg (or 150/100 mg for those with a creatinine clearance of 30–60 mL/min) twice daily (Arm 3), randomly assigned in a 1:1:1 ratio, in non-hospitalized adults with early COVID-19 at high-risk of progression to severe disease. The primary outcome of MONET was clinical failure within 30 days after randomization, defined as any-cause mortality, hospitalization, or progression to severe COVID-19 11 . This paper reports the results of the analysis of the main secondary outcome which was the change in SARS-CoV-2 VL in NPS between enrolment (D1) and Visit 2 (D7) by PCR cycle threshold (CT) value conducted in 3/7 sites of MONET. Several other secondary outcomes have been evaluated during each visit (at D1, D7, D29): the variation of inflammatory markers [C-reactive protein (CRP), d-dimer, and neutrophils-to-lymphocytes ratio (NLR)] and antibody level (serum anti-S IgG and anti-N IgG). See supplementary materials for further details on study design and participants, statistical analysis and methods to measure viral load. RESULTS Out of a total of 465 participants enrolled in the trial, 346 (74.4%) individuals for whom pairs of CT values at D1 and D7 were available were included: 116 (34%) received SOT, 113 (33%) TIX/CIL and 117 (34%) NMV/r (Fig. 1 for the study flow chart). Baseline characteristics of the study population, stratified by treatment arms, are reported in Table 1 . Briefly, 49.4% (N = 171) of the subjects were female with an overall median age of 66 years [Interquartile Range (IQR) 55–76], mainly infected either with BA.2 (N = 180, 52%) or BA.4/5 (N = 123, 35.5%) and with median time from symptom onset to randomization of 3 days (IQR 2–4). The participants seemed balanced across study arms with respect to all variables examined possibly with the exception of age (participants allocated to the SOT arm appeared to be slightly older than those allocated to the other trial arms, Table 1 , Figures S1 -3 for love plots). Baseline CT values were also balanced: [mean (95% CI) SOT versus (vs.) NMV/r 0.02 (-0.07, 0.1), p = 0.875; TIX/CIL vs. NMV/r -0.01 (-0.10, 0.08), p = 0.931; TIX/CIL vs. SOT − 0.03 (-0.12, 0.06) p = 0.680, Table 1 , Fig. 2]. Figure 2 also describes the distribution of the variation in raw CT values over D1-D7 by trial arm. Table 1 Description of study population by trial arm. Trial arm Characteristics SOT TIX/CIL NMV/r Total N = 116 N = 113 N = 117 N = 346 Gender, n(%) Female 53 (45.7%) 58 (51.3%) 60 (51.3%) 171 (49.4%) Ethnicity, n(%) Caucasian 111 (95.7%) 110 (97.3%) 114 (97.4%) 335 (96.8%) Age, years Median (IQR) 69 (60, 76) 65 (54, 76) 66 (55, 78) 66 (55, 76) > 65, n(%) 67 (57.8%) 52 (46.0%) 60 (51.3%) 179 (51.7%) Days from symptoms onset Median (IQR) 3 (2, 4) 3 (2, 4) 3 (2, 4) 3 (2, 4) > 2, n(%) 34 (30.1%) 28 (25.5%) 31 (27.4%) 93 (27.7%) Comorbidities, n(%) Diabetes 10 (8.6%) 5 (4.4%) 11 (9.4%) 26 (7.5%) Obesity (BMI > 30) 25 (21.6%) 26 (23.0%) 19 (16.2%) 70 (20.2%) CVD 8 (6.9%) 9 (8.0%) 9 (7.7%) 26 (7.5%) COPD 4 (3.4%) 11 (9.7%) 9 (7.7%) 24 (6.9%) Renal impairment 0 (0.0%) 0 (0.0%) 1 (0.9%) 1 (0.3%) Haematological Cancer 7 (6.0%) 5 (4.4%) 3 (2.6%) 15 (4.3%) Immunodeficiency 8 (6.9%) 8 (7.1%) 8 (6.8%) 24 (6.9%) Neurologic disease 1 (0.9%) 3 (2.7%) 1 (0.9%) 5 (1.4%) Other 47 (40.5%) 44 (38.9%) 50 (42.7%) 141 (40.8%) Vaccination, n(%) ≥ 2 doses 110 (94.8%) 105 (92.9%) 111 (94.9%) 326 (94.2%) SARS-CoV-2 variant, n(%) Omicron BA.1 6 (5.2%) 5 (4.4%) 9 (7.7%) 20 (5.8%) Omicron BA.2 62 (53.4%) 61 (54.0%) 57 (48.7%) 180 (52.0%) Omicron BA.4/5 42 (36.2%) 41 (36.3%) 40 (34.2%) 123 (35.5%) Omicron BQ.1 6 (5.2%) 6 (5.3%) 11 (9.4%) 23 (6.6%) Viral Load on NPS sample log2 scale, median (IQR) 3.99 (3.82, 4.22) 3.95 (3.76, 4.23) 4.00 (3.79, 4.20) 3.99 (3.78, 4.21) Abbrevations : SOT, sotrovimab; TIX/CIL, tixagevimab plus cilgavimab; NMV/r, nirmatrelvir plus ritonavir; N, number of participants; NPS, nasopharyngeal swab; CI, confidence interval; IQR, interquartile range; BMI, body mass index; CVD, cardiovascular disease; COPD, chronic obstructive pulmonary disease. The regression model analysis using log-transformed values, carried strong evidence that the mean change in CT was larger in subjects receiving NMV/r than in those receiving SOT or TIX/CIL [SOT vs. NMV/r -0.16 log 2 (-0.25, -0.07), p < 0.001; TIX/CIL vs. NMV/r -0.20 log 2 (-0.30, -0.11), p < 0.001; TIX/CIL vs. SOT − 0.04 log 2 (-0.13, 0.05), p = 0.48; Fig. 3], even after controlling for age [SOT vs. NMV/r -0.16 log 2 (-0.25, -0.07), p < 0.001; TIX/CIL vs. NMV/r -0.20 log 2 (-0.29, -0.11), p < 0.001; TIX/CIL vs. SOT − 0.04 log 2 (-0.13, 0.05), p = 0.50; Fig. 3]. In other words, by day 7 participants randomized to NMV/r showed a larger reduction in viral shedding than those allocated to other drugs. Figure S4 shows the post-hoc forest plot of the same contrasts after stratification for viral variants (BA.2 or BA.4/5). We found little evidence for effect measure modification (interaction p-value = 0.14) The proportion of participants who achieved a CT value > 35 at D7, was also higher in participants allocated to NMV/r compared to other arms but data were compatible with the null hypothesis of no difference (12% in SOT vs. 13% in TIX/CIL vs. 19% in NMV/r, p = 0.30). Results were similar after controlling for age: adjusted (a)OR 0.60 (95% CI:0.29–1.25) for SOT vs. NMV/r and 0.64 (0.31–1.31) for TIX/CIL vs NMV/r. Regarding the other secondary outcomes, there was no evidence that the trajectories over D1-D29 of inflammatory markers varied by trial arm (p = 0.605 for CRP, p = 0.131 for d-dimer, p = 0.932 for NLR Figure S6 and Table S1 ). CRP and NLR showed a clear reduction over time, regardless of the drug received, while d-dimer showed a more stable trend. Kinetics of antibody levels showed a rapid increase of serum anti-S IgG in both mAbs arms followed by a plateau vs. a steady linear increase in the NMV/r arm; the steady increase was seen in all arms for anti-N IgG values again with no evidence for a difference by study arm (Figure S7 and Table S2). DISCUSSION Our analysis provides in vivo evidence that, when used against Omicron sublineages, NMV/r exerts a greater antiviral effect than SOT and TIX/CIL by day 7 from treatment initiation, regardless of the detected Omicron subvariant. These results confirm previous in vitro data suggesting that mAbs may not retain neutralizing activity against Omicron strains. In particular TIX/CIL appeared to show a progressive loss of efficacy against Omicron subvariants emerging over time 4 – 8 , 12 . Conversely, although for sotrovimab, there is some in vitro evidence that it may retain partial neutralizing activity against these variants 5 – 7 , including the most recent BQ.1.1 and XBB.1.5, in our analysis we found no evidence for a difference in virological potency when compared to TIX/CIL. Of note, there are very few studies which compared the in vivo virological response to these compounds. Previously published placebo-controlled RCTs designed to assess the clinical efficacy of NMV/r 3 , SOT 2 , and TIX/CIL 1,13 included the evaluation of virological outcomes, but a direct comparison between these drugs has not been performed within a single clinical trial. Several observational studies conducted in the setting of early treatment of COVID-19 for patients at high-risk of progression, have evaluated virological efficacy by comparing antivirals and mAbs 14 – 17 , but these are mainly small studies 16 , conducted during the first phase of the Omicron wave 14 – 15 , with not many participants treated with NMV/r 15 . To our knowledge, our trial is the first randomized study providing strong in vivo evidence of NMV/r antiviral superiority over both SOT and TIX/CIL in the Omicron era (including infections with BA.1/2 to BA.4/5 and BQ.1/BQ.1.1). In this analysis, we used a CT threshold value of > 35 to define a negative RT-PCR result for SARS-CoV-2 on NPS samples, and although we observed that a higher proportion of participants treated with NMV/r achieved this goal after 1 week, our analysis was underpowered to show superiority vs. mAbs. However, it should be noted that this binary outcome is often used in the clinic but rarely for research purposes. Indeed, treatment-induced acceleration of viral clearance in the first few days after therapy, rather than the proportion of individuals with CT above a certain threshold, has been proposed as a surrogate of clinical efficacy to prevent hospitalization with COVID-19 9–10,18 . Many studies, such as phase-2/3 randomized trials and observational cohorts, have compared the reduction in VL between treated and control groups (as a continuous measure) at different times after therapy as a surrogate marker of therapeutic effect. Analyses aiming to assess whether the CT reduction is a valid surrogate marker for clinical endpoints are still ongoing. A recent meta-analysis 9 of 22 RCTs found a correlation between the virological effect of the different therapies measured during the first 7 days following initiation of treatment and the corresponding clinical efficacy in preventing severe forms of COVID-19. Of note, this meta-analysis included only studies conducted in unvaccinated individuals and underscored the need of validating these findings in other settings. The MONET trial was conducted in a population with a high proportion of vaccinated individuals (94% with at least two doses of vaccine), and the results reported here, along with those related to the primary clinical efficacy outcome 11 , further indicates CT reduction as a strong candidate surrogate marker for clinical efficacy. Interestingly, in our analysis, the type of treatment did not seem to influence the development of the natural antibody response neither the level of inflammatory markers. We observed a more marked increase in serum anti-S IgG levels among participants receiving mAbs compared to those receiving NMV/r. This was somewhat expected as all the investigated mAbs targeted S antibodies; in contrast, we found no evidence for a difference in the variation over time of anti-N IgG levels by intervention suggesting that mAb administration might have no impact on the endogenous immune response, an issue that had previously been raised 19 – 21 . Similarly, we found no evidence for a difference in the trajectories of inflammatory markers by trial arm, reflecting that the kinetics of these biomarkers are likely to be a consequence of the disease evolution regardless of the specific treatment used. Similar findings came from a recent analysis of a placebo-controlled RCTs on mAbs among hospitalized individuals 21 . Our analysis has several limitations. First, 119 participants of the MONET trial with no measures for the secondary outcome had to be excluded from the analytic sample, and this may have led to selection bias 22 . However, missing CT values (either due to missing swabs or unsuccessful measurement) seemed to have occurred randomly as treatment groups were still balanced for key predictors of outcome in the analytic sample (except perhaps for age), retaining internal validity. Also, the analysis with outcome the viral load negativity by day 7 was likely underpowered. In addition, although the trial was multi-centric, most of participants came from a single center and this feature, along with the underrepresentation of some high-risk groups, could limit the generalizability of our conclusions. Finally, the analysis was performed at the beginning of the advent of BQ.1.1, and it is unclear whether our results will be confirmed in the current epidemiological scenario of new circulating Omicron subvariants. In conclusion, our results provide high level of evidence for the superiority of NMV/r over mAbs (SOT and TIX/CIL), in reducing SARS-CoV-2 CT by day 7 in vaccinated non-hospitalized subjects at high-risk of progression to severe COVID-19, all infected with Omicron variants. In addition, these findings, together with the results of the analysis of the clinical outcome published elsewhere 11 , identify day 7 CT variation as a promising candidate surrogate marker for clinical efficacy. Given the currently inconsistent recommendations on the use of mAbs across countries in the Omicron era, robust data deriving from in vivo randomized studies are crucial to optimize and homogenize treatment guidelines for COVID-19. Further research is warranted to verify whether the superior virologic potency of NMV/r over mAbs is confirmed for newly emerging Omicron variants. Declarations AUTHOR CONTRIBUTIONS VM and AA conceived the study; IM and ACL wrote the first draft of the manuscript; GM, FC, MR, GB, and FM were responsible for the virological tests; VM, SL, IM, AO, AV, SR and EN enrolled the patients; JP was responsible for data entry; SL and ACL were responsible of data management and statistical analysis; VM, AA, EN, FM, EG reviewed the manuscript. All authors approved the final version of the manuscript. ACKNOWLEDGMENTS AND FUNDING We acknowledge the MONET Clinical Trial Group , the nurse staff, and all the study participants. MONET Clinical Trial Group : Samir Al Moghazi, Massimo Andreoni, Nazario Bevilacqua, Elisa Biliotti, Pierluigi Blanc, Raffaele Bruno, Emanuela Caraffa, Antonio Cascio, Anna Maria Cattelan, Roberto Cauda, Fabrizio Carletti, Carlotta Cerva, Francesca Colavita, Angela Corpolongo, Alessandra D’Abramo, Federico De Zottis, Silvia Di Bari, Giovanni Di Perri, Massimo Di Pietro, Davide Roberto Donno, Francesca Faraglia, Francesca Gavaruzzi, Ivan Gentile, Letizia Giancola, Emanuela Giombini, Andrea Gori, Paolo Grossi, Cesare Ernesto Maria Gruber, Carmelo Iacobello, Chiara Iaria, Marco Libanore, Raffaella Libertone, Miriam Lichtner, Laura Loiacono, Andrea Mariano, Marco Massari, Claudio Maria Mastroianni, Giulia Matusali, Silvia Meschi, Eugenia Milozzi, Cristina Mussini, Roberto Parrella, Massimo Puoti, Giuliano Rizzardini, Annalisa Saracino, Laura Scorzolini, Eliana Specchiarello, Marcello Tavio, Carlo Torti, Alessandra Vergori, Pierluigi Viale, Serena Vita, Pietro Vittozzi. The study has been funded by the Italian Drug Agency (AIFA) and by the Italian Ministry of Health (Ricerca Corrente Linea 1). Alessandro Cozzi-Lepri work is supported by EuCARE project funded by the EU under the HORIZON Europe programme, Grant agreement n. 101046016. CONFLICT OF INTEREST STATEMENT See separate document. DATA AVAILABILITY STATEMENT Anonymized participant data will be made available upon reasonable requests directed to the corresponding author. ETHICS STATEMENT All included individuals have signed a written informed consent to participate in the study. The study protocol and the informed consent were approved by the Scientific Committee of the Italian Medicines Agency (AIFA) and by the Ethical Committee of the National Institute for Infectious Diseases “Lazzaro Spallanzani” in Rome, Italy, as National Review Board for COVID-19 pandemic in Italy (approval number: n. 380, 30/09/2021. FAV del Registro delle Sperimentazioni 2020/2021 ). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5715907","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":400910215,"identity":"2bf8ed56-c64c-4210-923a-37a9d821cc39","order_by":0,"name":"Ilaria Mastrorosa","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Ilaria","middleName":"","lastName":"Mastrorosa","suffix":""},{"id":400910216,"identity":"9fb4bfef-6d67-4081-b4c3-b737f54e15ec","order_by":1,"name":"Alessandro Cozzi-Lepri","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIie2QsQrCMBCGrxTSJdj1JvsKLQURfJlIQRdxEaSDaEGIk7uD+A4uzoWCLtp36O7QSTo4eFERl1hHwXxLfsJ95L8AGAy/C0JDHSKGR6BYr7D73BEe4QvlOWnJLxQ3sYuiuraBOct9WWwyj4FdlJbs6RulLPSRUzGeR6vuLgsksBAtOdAXSjlDH3EmcRACKYKKtahhrDU8pQifXvHOpKyV4lw+Kr5SUkEKclISpXD1ir5YkLEwSFK1yzACse8H0uYjFLl+/eZhrn5sCq5zyqxq0vFcZ7Ety3GkX99+Jf52I/TCO7x+xGAwGP6TG3tSQFaOgdQUAAAAAElFTkSuQmCC","orcid":"","institution":"Institute for Global Health UCL","correspondingAuthor":true,"prefix":"","firstName":"Alessandro","middleName":"","lastName":"Cozzi-Lepri","suffix":""},{"id":400910217,"identity":"a9c1d298-2ef6-4e65-ad77-d871ccc17157","order_by":2,"name":"Giulia Matusali","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Giulia","middleName":"","lastName":"Matusali","suffix":""},{"id":400910218,"identity":"4d8bfcfd-3405-498a-bf25-2e648dac6946","order_by":3,"name":"Francesca Colavita","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Francesca","middleName":"","lastName":"Colavita","suffix":""},{"id":400910219,"identity":"0ba2ead7-f042-463d-8f5e-a3b3ab294a01","order_by":4,"name":"Simone Lanini","email":"","orcid":"","institution":"University of Udine","correspondingAuthor":false,"prefix":"","firstName":"Simone","middleName":"","lastName":"Lanini","suffix":""},{"id":400910220,"identity":"216c23cb-d1dc-4858-919c-e9561449d038","order_by":5,"name":"Martina Rueca","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Martina","middleName":"","lastName":"Rueca","suffix":""},{"id":400910221,"identity":"309bfd9a-f7a6-4231-acde-88f11a2a88a9","order_by":6,"name":"Alessandra Oliva","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Alessandra","middleName":"","lastName":"Oliva","suffix":""},{"id":400910222,"identity":"0bafaf92-970d-4271-a0cd-7cbebc89c6a8","order_by":7,"name":"Giulia Berno","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Giulia","middleName":"","lastName":"Berno","suffix":""},{"id":400910223,"identity":"d8519a13-b021-46d0-82e0-0397941fc541","order_by":8,"name":"Alessandra Vergori","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Alessandra","middleName":"","lastName":"Vergori","suffix":""},{"id":400910224,"identity":"6a669936-6ac2-42ec-a3be-25d214ea99e7","order_by":9,"name":"Silvia Rosati","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Silvia","middleName":"","lastName":"Rosati","suffix":""},{"id":400910225,"identity":"616a819d-c505-4ece-86d9-3fd447e228ac","order_by":10,"name":"Jessica Paulicelli","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Jessica","middleName":"","lastName":"Paulicelli","suffix":""},{"id":400910226,"identity":"2c78940a-480a-4002-b80d-f7563e5fd7bf","order_by":11,"name":"Enrico Girardi","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Enrico","middleName":"","lastName":"Girardi","suffix":""},{"id":400910227,"identity":"990f77b7-bb37-4966-8156-b8f5cdc6f885","order_by":12,"name":"Emanuele Nicastri","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Emanuele","middleName":"","lastName":"Nicastri","suffix":""},{"id":400910228,"identity":"c2e55d37-990b-4904-8da3-20b75c33f008","order_by":13,"name":"Fabrizio Maggi","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Fabrizio","middleName":"","lastName":"Maggi","suffix":""},{"id":400910229,"identity":"282d89ac-3b8a-47e6-a9bc-a4b47d426e74","order_by":14,"name":"Andrea Antinori","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"","lastName":"Antinori","suffix":""},{"id":400910230,"identity":"122fdb3c-2022-4488-a82f-95f8fa445c5e","order_by":15,"name":"Valentina Mazzotta","email":"","orcid":"","institution":"National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Valentina","middleName":"","lastName":"Mazzotta","suffix":""}],"badges":[],"createdAt":"2024-12-26 11:53:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5715907/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5715907/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74072873,"identity":"c7301b36-bec6-45e4-b43e-b5b2cba84186","added_by":"auto","created_at":"2025-01-17 13:11:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47288,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flow chart. Abbreviations: N, number of participants; CT, cycle threshold; SOT, sotrovimab; TIX/CIL, tixagevimab plus cilgavimab; NMV/r, nirmatrelvir plus ritonavir\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5715907/v1/4b7c6893027f23e9e97a0046.png"},{"id":74072876,"identity":"f366726c-d862-41da-9e54-7f3698c24ae8","added_by":"auto","created_at":"2025-01-17 13:11:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":50692,"visible":true,"origin":"","legend":"\u003cp\u003eBox plots of cycle threshold (CT) values (raw scale) at enrollment (d1), after seven days (d7) and CT values variation d1-d7, by trial arm (SOT, sotrovimab; TIX/CIL, tixagevimab plus cilgavimab; NMV/r, nirmatrelvir plus ritonavir).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5715907/v1/d0bf71a3e4b38fad5f1233e5.png"},{"id":74072872,"identity":"6b06c0e7-802a-4115-a1d0-d9d250e06738","added_by":"auto","created_at":"2025-01-17 13:11:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":49346,"visible":true,"origin":"","legend":"\u003cp\u003eDifference in mean cycle threshold (CT) values change seven days after the enrollment (D1-D7) from fitting linear regression models, adjusted for age, among all study participants. Abbreviations: SOT, sotrovimab; TIX/CIL, tixagevimab plus cilgavimab; NMV/r, nirmatrelvir plus ritonavir; vs., versus.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5715907/v1/a2692a352de81313b8ce9740.png"},{"id":74074574,"identity":"687f43f1-e1d1-4106-a0b7-b5f53428ebc6","added_by":"auto","created_at":"2025-01-17 13:27:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":796540,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5715907/v1/18fc2578-4752-4c37-9dc0-ebb940451112.pdf"},{"id":74072877,"identity":"72463931-8758-4a38-9da1-cbeb016cb216","added_by":"auto","created_at":"2025-01-17 13:11:22","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1243473,"visible":true,"origin":"","legend":"","description":"","filename":"SecondaryoutcomesMONETMastrorosaMMIshortsupplementarymaterials.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5715907/v1/08d24b218b1ed48c8abe99b1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"SARS-COV-2 nasopharyngeal viral load change in a multicenter randomized clinical trial comparing early therapies for COVID-19 in non-hospitalized adults with high risk of severe COVID-19 (the MONET TRIAL)","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eIn January 2022, in the Omicron era, both monoclonal antibodies (mAbs) and antiviral agents were available for the early treatment of mild-to-moderate COVID-19 for outpatients at high risk for progression to severe disease. Most of the data supporting their use come from placebo-controlled phase-3 randomized clinical trials (RCTs) that demonstrated a reduced risk of developing severe COVID-19 or death in subjects receiving mAbs such as sotrovimab (SOT) and tixagevimab plus cilgavimab (TIX/CIL), or antivirals such as nirmatrelvir plus ritonavir (NMV/r)\u003csup\u003e1\u0026ndash;3\u003c/sup\u003e. However, these studies were conducted in the pre-Omicron phase, and it is likely that the efficacy of treatment against these earlier circulating variants was different. Indeed, SARS-CoV-2 evolution and the specific mutations in the spike protein (the binding target for mAbs) harboured by Omicron sublineages resulted in an evolving escape to \u003cem\u003ein vitro\u003c/em\u003e neutralizing activity by mAbs\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, with an unclear impact on \u003cem\u003ein vivo\u003c/em\u003e treatment response. Conversely, laboratory data show that the protease inhibitor nirmatrelvir, enhanced with ritonavir, seemed to have retained its antiviral activity against various Omicron sublineages\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFor this reason, randomized clinical trials aimed to compare the virological response to available treatments in individuals infected with Omicron strains remain strategically important. In the outpatient setting, because of the low risk of severe outcomes during the Omicron phase of the pandemic, candidate surrogate markers, such as the viral load (VL) reduction in nasopharyngeal swab (NPS) samples, have been typically used in phase-3 studies as a measure of \u003cem\u003ein vivo\u003c/em\u003e neutralizing or antiviral activity\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHere we show the results of the analysis of the secondary outcome of the MONET trial, which was designed to compare the efficacy and safety of early treatment with SOT, TIX/CIL, or NMV/r in the setting of a high-risk outpatient population with mild to moderate COVID-19 enrolled in several clinical sites in Italy.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTrial design\u003c/h2\u003e \u003cp\u003e The MONET trial (registration number EudraCT: 2021-004188-28, 13 September 2021) is a multicentric, phase-4, three-arm, superiority, open-label RCT conducted over March 2022-February 2023, to assess the efficacy and safety of 500 mg intravenous SOT (Arm 1), 300/300 mg intramuscular TIX/CIL (Arm 2) and oral 5-days course of NMV/r 300/100 mg (or 150/100 mg for those with a creatinine clearance of 30\u0026ndash;60 mL/min) twice daily (Arm 3), randomly assigned in a 1:1:1 ratio, in non-hospitalized adults with early COVID-19 at high-risk of progression to severe disease.\u003c/p\u003e \u003cp\u003eThe primary outcome of MONET was clinical failure within 30 days after randomization, defined as any-cause mortality, hospitalization, or progression to severe COVID-19\u003csup\u003e11\u003c/sup\u003e. This paper reports the results of the analysis of the main secondary outcome which was the change in SARS-CoV-2 VL in NPS between enrolment (D1) and Visit 2 (D7) by PCR cycle threshold (CT) value conducted in 3/7 sites of MONET. Several other secondary outcomes have been evaluated during each visit (at D1, D7, D29): the variation of inflammatory markers [C-reactive protein (CRP), d-dimer, and neutrophils-to-lymphocytes ratio (NLR)] and antibody level (serum anti-S IgG and anti-N IgG).\u003c/p\u003e \u003cp\u003eSee supplementary materials for further details on study design and participants, statistical analysis and methods to measure viral load.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eOut of a total of 465 participants enrolled in the trial, 346 (74.4%) individuals for whom pairs of CT values at D1 and D7 were available were included: 116 (34%) received SOT, 113 (33%) TIX/CIL and 117 (34%) NMV/r (Fig.\u0026nbsp;1 for the study flow chart).\u003c/p\u003e \u003cp\u003eBaseline characteristics of the study population, stratified by treatment arms, are reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Briefly, 49.4% (N\u0026thinsp;=\u0026thinsp;171) of the subjects were female with an overall median age of 66 years [Interquartile Range (IQR) 55\u0026ndash;76], mainly infected either with BA.2 (N\u0026thinsp;=\u0026thinsp;180, 52%) or BA.4/5 (N\u0026thinsp;=\u0026thinsp;123, 35.5%) and with median time from symptom onset to randomization of 3 days (IQR 2\u0026ndash;4). The participants seemed balanced across study arms with respect to all variables examined possibly with the exception of age (participants allocated to the SOT arm appeared to be slightly older than those allocated to the other trial arms, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-3 for love plots). Baseline CT values were also balanced: [mean (95% CI) SOT \u003cem\u003eversus\u003c/em\u003e (vs.) NMV/r 0.02 (-0.07, 0.1), p\u0026thinsp;=\u0026thinsp;0.875; TIX/CIL vs. NMV/r -0.01 (-0.10, 0.08), p\u0026thinsp;=\u0026thinsp;0.931; TIX/CIL vs. SOT \u0026minus;\u0026thinsp;0.03 (-0.12, 0.06) p\u0026thinsp;=\u0026thinsp;0.680, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;2]. Figure\u0026nbsp;2 also describes the distribution of the variation in raw CT values over D1-D7 by trial arm.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of study population by trial arm.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eTrial arm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSOT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTIX/CIL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNMV/r\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (45.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (51.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (51.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e171 (49.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaucasian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111 (95.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 (97.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114 (97.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e335 (96.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge, years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (60, 76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65 (54, 76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (55, 78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66 (55, 76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;65, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (57.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (46.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (51.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e179 (51.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDays from symptoms onset\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2, 4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2, 4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2, 4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (2, 4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (30.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (25.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (27.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93 (27.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity (BMI\u0026thinsp;\u0026gt;\u0026thinsp;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (21.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (23.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70 (20.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal impairment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaematological Cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunodeficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurologic disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (40.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (38.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50 (42.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e141 (40.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVaccination, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;2 doses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110 (94.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105 (92.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111 (94.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e326 (94.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSARS-CoV-2 variant, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOmicron BA.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOmicron BA.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (53.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (54.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57 (48.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e180 (52.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOmicron BA.4/5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (36.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (36.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40 (34.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e123 (35.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOmicron BQ.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eViral Load on NPS sample\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elog2 scale, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.99 (3.82, 4.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.95 (3.76, 4.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.00 (3.79, 4.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.99 (3.78, 4.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAbbrevations\u003c/b\u003e: \u003cem\u003eSOT, sotrovimab; TIX/CIL, tixagevimab plus cilgavimab; NMV/r, nirmatrelvir plus ritonavir; N, number of participants; NPS, nasopharyngeal swab; CI, confidence interval; IQR, interquartile range; BMI, body mass index; CVD, cardiovascular disease; COPD, chronic obstructive pulmonary disease.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe regression model analysis using log-transformed values, carried strong evidence that the mean change in CT was larger in subjects receiving NMV/r than in those receiving SOT or TIX/CIL [SOT vs. NMV/r -0.16 log\u003csub\u003e2\u003c/sub\u003e (-0.25, -0.07), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; TIX/CIL vs. NMV/r -0.20 log\u003csub\u003e2\u003c/sub\u003e (-0.30, -0.11), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; TIX/CIL vs. SOT \u0026minus;\u0026thinsp;0.04 log\u003csub\u003e2\u003c/sub\u003e (-0.13, 0.05), p\u0026thinsp;=\u0026thinsp;0.48; Fig.\u0026nbsp;3], even after controlling for age [SOT vs. NMV/r -0.16 log\u003csub\u003e2\u003c/sub\u003e (-0.25, -0.07), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; TIX/CIL vs. NMV/r -0.20 log\u003csub\u003e2\u003c/sub\u003e (-0.29, -0.11), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; TIX/CIL vs. SOT \u0026minus;\u0026thinsp;0.04 log\u003csub\u003e2\u003c/sub\u003e (-0.13, 0.05), p\u0026thinsp;=\u0026thinsp;0.50; Fig.\u0026nbsp;3]. In other words, by day 7 participants randomized to NMV/r showed a larger reduction in viral shedding than those allocated to other drugs. Figure S4 shows the post-hoc forest plot of the same contrasts after stratification for viral variants (BA.2 or BA.4/5). We found little evidence for effect measure modification (interaction p-value\u0026thinsp;=\u0026thinsp;0.14) The proportion of participants who achieved a CT value\u0026thinsp;\u0026gt;\u0026thinsp;35 at D7, was also higher in participants allocated to NMV/r compared to other arms but data were compatible with the null hypothesis of no difference (12% in SOT vs. 13% in TIX/CIL vs. 19% in NMV/r, p\u0026thinsp;=\u0026thinsp;0.30). Results were similar after controlling for age: adjusted (a)OR 0.60 (95% CI:0.29\u0026ndash;1.25) for SOT vs. NMV/r and 0.64 (0.31\u0026ndash;1.31) for TIX/CIL vs NMV/r.\u003c/p\u003e \u003cp\u003eRegarding the other secondary outcomes, there was no evidence that the trajectories over D1-D29 of inflammatory markers varied by trial arm (p\u0026thinsp;=\u0026thinsp;0.605 for CRP, p\u0026thinsp;=\u0026thinsp;0.131 for d-dimer, p\u0026thinsp;=\u0026thinsp;0.932 for NLR Figure S6 and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). CRP and NLR showed a clear reduction over time, regardless of the drug received, while d-dimer showed a more stable trend. Kinetics of antibody levels showed a rapid increase of serum anti-S IgG in both mAbs arms followed by a plateau vs. a steady linear increase in the NMV/r arm; the steady increase was seen in all arms for anti-N IgG values again with no evidence for a difference by study arm (Figure S7 and Table S2).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur analysis provides \u003cem\u003ein vivo\u003c/em\u003e evidence that, when used against Omicron sublineages, NMV/r exerts a greater antiviral effect than SOT and TIX/CIL by day 7 from treatment initiation, regardless of the detected Omicron subvariant. These results confirm previous \u003cem\u003ein vitro\u003c/em\u003e data suggesting that mAbs may not retain neutralizing activity against Omicron strains. In particular TIX/CIL appeared to show a progressive loss of efficacy against Omicron subvariants emerging over time\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6 CR7\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Conversely, although for sotrovimab, there is some \u003cem\u003ein vitro\u003c/em\u003e evidence that it may retain partial neutralizing activity against these variants\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, including the most recent BQ.1.1 and XBB.1.5, in our analysis we found no evidence for a difference in virological potency when compared to TIX/CIL.\u003c/p\u003e \u003cp\u003eOf note, there are very few studies which compared the \u003cem\u003ein vivo\u003c/em\u003e virological response to these compounds. Previously published placebo-controlled RCTs designed to assess the clinical efficacy of NMV/r\u003csup\u003e3\u003c/sup\u003e, SOT\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, and TIX/CIL\u003csup\u003e1,13\u003c/sup\u003e included the evaluation of virological outcomes, but a direct comparison between these drugs has not been performed within a single clinical trial. Several observational studies conducted in the setting of early treatment of COVID-19 for patients at high-risk of progression, have evaluated virological efficacy by comparing antivirals and mAbs\u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, but these are mainly small studies\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, conducted during the first phase of the Omicron wave\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, with not many participants treated with NMV/r\u003csup\u003e15\u003c/sup\u003e. To our knowledge, our trial is the first randomized study providing strong \u003cem\u003ein vivo\u003c/em\u003e evidence of NMV/r antiviral superiority over both SOT and TIX/CIL in the Omicron era (including infections with BA.1/2 to BA.4/5 and BQ.1/BQ.1.1).\u003c/p\u003e \u003cp\u003eIn this analysis, we used a CT threshold value of \u0026gt;\u0026thinsp;35 to define a negative RT-PCR result for SARS-CoV-2 on NPS samples, and although we observed that a higher proportion of participants treated with NMV/r achieved this goal after 1 week, our analysis was underpowered to show superiority vs. mAbs. However, it should be noted that this binary outcome is often used in the clinic but rarely for research purposes. Indeed, treatment-induced acceleration of viral clearance in the first few days after therapy, rather than the proportion of individuals with CT above a certain threshold, has been proposed as a surrogate of clinical efficacy to prevent hospitalization with COVID-19\u003csup\u003e9\u0026ndash;10,18\u003c/sup\u003e. Many studies, such as phase-2/3 randomized trials and observational cohorts, have compared the reduction in VL between treated and control groups (as a continuous measure) at different times after therapy as a surrogate marker of therapeutic effect. Analyses aiming to assess whether the CT reduction is a valid surrogate marker for clinical endpoints are still ongoing. A recent meta-analysis\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e of 22 RCTs found a correlation between the virological effect of the different therapies measured during the first 7 days following initiation of treatment and the corresponding clinical efficacy in preventing severe forms of COVID-19. Of note, this meta-analysis included only studies conducted in unvaccinated individuals and underscored the need of validating these findings in other settings. The MONET trial was conducted in a population with a high proportion of vaccinated individuals (94% with at least two doses of vaccine), and the results reported here, along with those related to the primary clinical efficacy outcome\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, further indicates CT reduction as a strong candidate surrogate marker for clinical efficacy.\u003c/p\u003e \u003cp\u003eInterestingly, in our analysis, the type of treatment did not seem to influence the development of the natural antibody response neither the level of inflammatory markers. We observed a more marked increase in serum anti-S IgG levels among participants receiving mAbs compared to those receiving NMV/r. This was somewhat expected as all the investigated mAbs targeted S antibodies; in contrast, we found no evidence for a difference in the variation over time of anti-N IgG levels by intervention suggesting that mAb administration might have no impact on the endogenous immune response, an issue that had previously been raised\u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Similarly, we found no evidence for a difference in the trajectories of inflammatory markers by trial arm, reflecting that the kinetics of these biomarkers are likely to be a consequence of the disease evolution regardless of the specific treatment used. Similar findings came from a recent analysis of a placebo-controlled RCTs on mAbs among hospitalized individuals\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur analysis has several limitations. First, 119 participants of the MONET trial with no measures for the secondary outcome had to be excluded from the analytic sample, and this may have led to selection bias\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. However, missing CT values (either due to missing swabs or unsuccessful measurement) seemed to have occurred randomly as treatment groups were still balanced for key predictors of outcome in the analytic sample (except perhaps for age), retaining internal validity. Also, the analysis with outcome the viral load negativity by day 7 was likely underpowered. In addition, although the trial was multi-centric, most of participants came from a single center and this feature, along with the underrepresentation of some high-risk groups, could limit the generalizability of our conclusions. Finally, the analysis was performed at the beginning of the advent of BQ.1.1, and it is unclear whether our results will be confirmed in the current epidemiological scenario of new circulating Omicron subvariants.\u003c/p\u003e \u003cp\u003eIn conclusion, our results provide high level of evidence for the superiority of NMV/r over mAbs (SOT and TIX/CIL), in reducing SARS-CoV-2 CT by day 7 in vaccinated non-hospitalized subjects at high-risk of progression to severe COVID-19, all infected with Omicron variants. In addition, these findings, together with the results of the analysis of the clinical outcome published elsewhere\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, identify day 7 CT variation as a promising candidate surrogate marker for clinical efficacy. Given the currently inconsistent recommendations on the use of mAbs across countries in the Omicron era, robust data deriving from \u003cem\u003ein vivo\u003c/em\u003e randomized studies are crucial to optimize and homogenize treatment guidelines for COVID-19. Further research is warranted to verify whether the superior virologic potency of NMV/r over mAbs is confirmed for newly emerging Omicron variants.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVM and AA conceived the study; IM and ACL wrote the first draft of the manuscript; GM, FC, MR, GB, and FM were responsible for the virological tests; VM, SL, IM, AO, AV, SR and EN enrolled the patients; JP was responsible for data entry; SL and ACL were responsible of data management and statistical analysis; VM, AA, EN, FM, EG reviewed the manuscript. All authors approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENTS AND FUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the \u003cem\u003eMONET Clinical Trial Group\u003c/em\u003e, the nurse staff, and all the study participants.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMONET Clinical Trial Group\u003c/em\u003e: Samir Al Moghazi, Massimo Andreoni, Nazario Bevilacqua, Elisa Biliotti, Pierluigi Blanc, Raffaele Bruno, Emanuela Caraffa, Antonio Cascio, Anna Maria Cattelan, Roberto Cauda, Fabrizio Carletti, Carlotta Cerva, Francesca Colavita, Angela Corpolongo, Alessandra D’Abramo, Federico De Zottis, Silvia Di Bari, Giovanni Di Perri, Massimo Di Pietro, Davide Roberto Donno, Francesca Faraglia, Francesca Gavaruzzi, Ivan Gentile, Letizia Giancola, Emanuela Giombini, Andrea Gori, Paolo Grossi, Cesare Ernesto Maria Gruber, Carmelo Iacobello, Chiara Iaria, Marco Libanore, Raffaella Libertone, Miriam Lichtner, Laura Loiacono, Andrea Mariano, Marco Massari, Claudio Maria Mastroianni, Giulia Matusali, Silvia Meschi, Eugenia Milozzi, Cristina Mussini, Roberto Parrella, Massimo Puoti, Giuliano Rizzardini, Annalisa Saracino, Laura Scorzolini, Eliana Specchiarello, Marcello Tavio, Carlo Torti, Alessandra Vergori, Pierluigi Viale, Serena Vita, Pietro Vittozzi.\u003c/p\u003e\n\u003cp\u003eThe study has been funded by the Italian Drug Agency (AIFA) and by the Italian Ministry of Health (Ricerca Corrente Linea 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlessandro Cozzi-Lepri work is supported by EuCARE project funded by the EU under the HORIZON Europe programme, Grant agreement n. 101046016.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONFLICT OF INTEREST STATEMENT\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSee separate document.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY STATEMENT\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnonymized participant data will be made available upon reasonable requests directed to the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICS STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll included individuals have signed a written informed consent to participate in the study. The study protocol and the informed consent were approved by the Scientific Committee of the Italian Medicines Agency (AIFA) and by the Ethical Committee of the National Institute for Infectious Diseases “Lazzaro Spallanzani” in Rome, Italy, as National Review Board for COVID-19 pandemic in Italy (approval number: \u0026nbsp;n. \u003cem\u003e380, 30/09/2021. FAV del Registro delle Sperimentazioni 2020/2021\u003c/em\u003e).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMontgomery H, Hobbs FDR, Padilla F, 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(10):985-996. doi:10.1016/S2213-2600(22)00180-1.\u003c/li\u003e\n\u003cli\u003eGupta A, Gonzalez-Rojas Y, Juarez E; COMET-ICE Investigators. Early Treatment for Covid-19 with SARS-CoV-2 Neutralizing Antibody Sotrovimab. N Engl J Med. 2021 Nov 18;385(21):1941-1950. doi: 10.1056/NEJMoa2107934.\u003c/li\u003e\n\u003cli\u003eHammond J, Leister-Tebbe H, Gardner A, et al. Oral nirmatrelvir for high-risk, non-hospitalized adults with Covid-19. N Engl J Med. 2022;386(15):1397-1408. doi:10.1056/NEJMoa2118542.\u003c/li\u003e\n\u003cli\u003eTakashita E, Yamayoshi S, Simon V, 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(5):468-470. doi:10.1056/NEJMc2207519.\u003c/li\u003e\n\u003cli\u003eCao Y, Wang J, Jian F, et al. Omicron escapes the majority of existing SARS-CoV-2 neutralizing antibodies. Nature. 2022;602(7898):657-663. doi:10.1038/s41586-021-04385-3.\u003c/li\u003e\n\u003cli\u003eYamasoba D, Kosugi Y, Kimura I, et al. Neutralisation sensitivity of SARS-CoV-2 omicron subvariants to therapeutic monoclonal antibodies. Lancet Infect Dis. 2022;22(7):942-943. doi:10.1016/S1473-3099(22)00365-6.\u003c/li\u003e\n\u003cli\u003eTouret F, Giraud E, Bourret J, et al. Enhanced neutralization escape to therapeutic monoclonal antibodies by SARS-CoV-2 omicron sub-lineages. iScience. 2023;26(4):106413. doi: 10.1016/j.isci.2023.106413.\u003c/li\u003e\n\u003cli\u003eImai M, Ito M, Kiso M, et al. Efficacy of antiviral agents against Omicron subvariants BQ.1.1 and XBB. N Engl J Med. 2023;388(1):89-91. doi:10.1056/NEJMc2214302.\u003c/li\u003e\n\u003cli\u003eElias KM, Khan SR, Stadler E, et al. Viral clearance as a surrogate of clinical efficacy for COVID-19 therapies in outpatients: a systematic review and meta-analysis. Lancet Microbe. 2024;5(5):e459-e467. doi:10.1016/S2666-5247(23)00398-1.\u003c/li\u003e\n\u003cli\u003eSchilling WHK, Jittamala P, Watson JA, et al. Antiviral efficacy of molnupiravir versus ritonavir-boosted nirmatrelvir in patients with early symptomatic COVID-19 (PLATCOV): an open-label, phase 2, randomised, controlled, adaptive trial [published correction appears in Lancet Infect Dis. 2023 Dec;23(12):e511. doi: 10.1016/S1473-3099(23)00649-7]. Lancet Infect Dis. 2024;24(1):36-45. doi:10.1016/S1473-3099(23)00493-0.\u003c/li\u003e\n\u003cli\u003eMazzotta V, Mazzaferri F, Lanini S, et al. Pooled analysis of the MANTICO2 and MONET randomized controlled trials comparing drug efficacy for early treatment of COVID-19 during Omicron waves. J Infect. 2024;89(5):106294. doi:10.1016/j.jinf.2024.106294.\u003c/li\u003e\n\u003cli\u003eConvertino I, Ferraro S, Cappello E, et al. Tixagevimab + cilgavimab against SARS-CoV-2: the preclinical and clinical development and real-world evidence. Expert Opin Drug Discov. 2023;18(3):231-245. doi: 10.1080/17460441.2023.2170348.\u003c/li\u003e\n\u003cli\u003eBender Ignacio RA, Chew KW, Moser C, et al. Safety and Efficacy of Combined Tixagevimab and Cilgavimab Administered Intramuscularly or Intravenously in Nonhospitalized Patients With COVID-19: 2 Randomized Clinical Trials. JAMA Netw Open. 2023;6(4):e2310039. Published 2023 Apr 3. doi:10.1001/jamanetworkopen.2023.10039.\u003c/li\u003e\n\u003cli\u003eMazzotta V, Cozzi Lepri A, Colavita F, et al. Viral load decrease in SARS-CoV-2 BA.1 and BA.2 Omicron sublineages infection after treatment with monoclonal antibodies and direct antiviral agents. J Med Virol. 2023;95(1):e28186. doi:10.1002/jmv.28186.\u003c/li\u003e\n\u003cli\u003eMartin-Blondel G, Marcelin AG, Souli\u0026eacute; C, et al. Time to negative PCR conversion amongst high-risk patients with mild-to-moderate Omicron BA.1 and BA.2 COVID-19 treated with sotrovimab or nirmatrelvir. Clin Microbiol Infect. 2023;29(4):543.e5-543.e9. doi:10.1016/j.cmi.2022.12.016.\u003c/li\u003e\n\u003cli\u003eColaneri M, Matone M, Fassio F, et al. Exploring early COVID-19 therapies, variants, and viral clearance dynamics: Insights from a high-risk outpatients study. Diagn Microbiol Infect Dis. 2024;110(2):116452. doi:10.1016/j.diagmicrobio.2024.116452.\u003c/li\u003e\n\u003cli\u003eColaneri M, Scaglione G, Fassio F, et al. Early administration of nirmatrelvir/ritonavir leads to faster negative SARS-CoV-2 nasal swabs than monoclonal antibodies in COVID 19 patients at high-risk for severe disease. Virol J. 2024;21(1):68. Published 2024 Mar 20. doi:10.1186/s12985-024-02333-x.\u003c/li\u003e\n\u003cli\u003eParienti JJ, de Grooth HJ. Clinical relevance of nasopharyngeal SARS-CoV-2 viral load reduction in outpatients with COVID-19. J Antimicrob Chemother 2022; 77: 2038\u0026ndash;39. \u003c/li\u003e\n\u003cli\u003eZhang L, Poorbaugh J, Dougan M, et al. Endogenous Antibody Responses to SARS-CoV-2 in Patients With Mild or Moderate COVID-19 Who Received Bamlanivimab Alone or Bamlanivimab and Etesevimab Together. Front Immunol. 2021;12:790469. Published 2021 Dec 9. doi:10.3389/fimmu.2021.790469.\u003c/li\u003e\n\u003cli\u003eKim PS, Dimcheff DE, Siler A, Schildhouse RJ, Chensue SW. Effect of monoclonal antibody therapy on the endogenous SARS-CoV-2 antibody response. Clin Immunol. 2022;236:108959. doi:10.1016/j.clim.2022.108959.\u003c/li\u003e\n\u003cli\u003eTomas O Jensen, Greg A Grandits, Mamta K Jain, et al., for the ACTIV-3/TICO Study Group , Effect of Neutralizing Monoclonal Antibody Treatment on Early Trajectories of Virologic and Immunologic Biomarkers in Patients Hospitalized With COVID-19, \u003cem\u003eThe Journal of Infectious Diseases\u003c/em\u003e, Volume 229, Issue 3, 15 March 2024, Pages 671\u0026ndash;679, https://doi.org/10.1093/infdis/jiad446.\u003c/li\u003e\n\u003cli\u003eLu H, Cole SR, Howe CJ, Westreich D. Toward a Clearer Definition of Selection Bias When Estimating Causal Effects. Epidemiology. 2022;33(5):699-706. doi:10.1097/EDE.0000000000001516.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"SARS Coronavirus, RCT, monoclonal antibodies, antiviral agents, viral load, antibodies response, inflammatory markers ","lastPublishedDoi":"10.21203/rs.3.rs-5715907/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5715907/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlthough \u003cem\u003ein vitro\u003c/em\u003e studies suggest that neutralization by monoclonal antibodies (mAbs) against SARS CoV2 Omicron sub lineages is reduced, \u003cem\u003ein vivo\u003c/em\u003evirological response data are lacking.\u003c/p\u003e\n\u003cp\u003eMONET (EudraCT: 2021-004188-28) was multi-centric phase 4 open-label parallel randomized clinical trial, conducted in Italy over 2022-2023, to assess the efficacy of sotrovimab (SOT), tixagevimab/cilgavimab (TIX/CIL) and Nirmatrelvir/ritonavir (NMV/r), in outpatients at high risk for severe COVID-19. The outcome (secondary in the trial protocol) was SARS-CoV-2 variation in cycle threshold (CT) values over the first 7 days (D1-D7) of the trial. CT variation was compared by trial arms using unadjusted linear regression and after controlling for age.\u003c/p\u003e\n\u003cp\u003eWe included 346 individuals: 116 (34%) received SOT, 113 (33%) TIX/CIL, 117 (34%) NMV/r. Main characteristics were balanced across arms. Most of the participants were infected with BA.2 (52%) or BA.4/5 (35.5%). The data carried strong evidence that the mean CT change over D1-D7 was larger in subjects receiving NMV/r vs. the other arms (p\u0026lt;0.001). We found no evidence that viral variant was an effect measure modifier for the contrasts of interest (p=0.14).\u003c/p\u003e\n\u003cp\u003eOur analysis provides strong evidence that NMV/r exerts a greater \u003cem\u003ein vivo\u003c/em\u003e antiviral effect than mAbs against Omicron sublineages, confirming previous \u003cem\u003ein vitro\u003c/em\u003e data.\u003c/p\u003e","manuscriptTitle":"SARS-COV-2 nasopharyngeal viral load change in a multicenter randomized clinical trial comparing early therapies for COVID-19 in non-hospitalized adults with high risk of severe COVID-19 (the MONET TRIAL)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-17 13:11:18","doi":"10.21203/rs.3.rs-5715907/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ee4365be-41b9-4b58-9491-ccc5612812bd","owner":[],"postedDate":"January 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-17T13:11:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-17 13:11:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5715907","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5715907","identity":"rs-5715907","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}