Literature DB >> 35165657

Outpatient Therapies for COVID-19: How Do We Choose?

Todd C Lee1,2,3, Andrew M Morris4, Steven A Grover3,5, Srinivas Murthy6, Emily G McDonald2.   

Abstract

BACKGROUND: Several outpatient coronavirus disease 2019 (COVID-19) therapies have reduced hospitalization in randomized controlled trials. The choice of therapy may depend on drug efficacy, toxicity, pricing, availability, and available infrastructure. To facilitate comparative decision-making, we evaluated the efficacy of each treatment in clinical trials and estimated the cost per hospitalization prevented.
METHODS: Wherever possible, we obtained relative risk for hospitalization from published randomized controlled trials. Otherwise, we extracted data from press releases, conference abstracts, government submissions, or preprints. If there was >1 study, the results were meta-analyzed. Using relative risk, we estimated the number needed to treat (NNT), assuming a baseline hospitalization risk of 5%, and compared the cost per hospitalization prevented with the estimate for an average Medicare COVID-19 hospitalization ($21 752). Drug pricing was estimated from GoodRx, from government purchases, or manufacturer estimates. Administrative and societal costs were not included. Results will be updated online as new studies emerge and/or final numbers become available.
RESULTS: At a 5% risk of hospitalization, the estimated NNT was 80 for fluvoxamine, 91 for colchicine, 72 for inhaled corticosteroids, 24 for nirmatrelvir/ritonavir, 50 for molnupiravir, 28 for remdesivir, 25 for sotrovimab, 29 for casirivimab/imdevimab, and 29 for bamlanivimab/etesevimab. For drug cost per hospitalization prevented, colchicine, fluvoxamine, inhaled corticosteroids, and nirmatrelvir/ritonavir were below the Medicare estimated hospitalization cost.
CONCLUSIONS: Many countries are fortunate to have access to several effective outpatient therapies to prevent COVID-19 hospitalization. Given differences in efficacy, toxicity, cost, and administration complexity, this assessment serves as one means to frame treatment selection.
© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America.

Entities:  

Keywords:  COVID-19; SARS-CoV-2; antivirals; monoclonal antibodies; repurposed medications

Year:  2022        PMID: 35165657      PMCID: PMC8807279          DOI: 10.1093/ofid/ofac008

Source DB:  PubMed          Journal:  Open Forum Infect Dis        ISSN: 2328-8957            Impact factor:   3.835


The coronavirus disease 2019 (COVID-19) pandemic has fueled an explosion of scientific inquiry. Since the initial reports of overwhelmed health systems and hospitals, there has been tremendous interest in finding outpatient treatments that could prevent hospitalization among those who are symptomatic and at high risk for clinical deterioration. Initial studies looked at drug repurposing: identifying widely available, inexpensive, and safe medications that could prove effective. Initially, hydroxychloroquine was considered a leading candidate [1]; however, interest waned as randomized controlled trial evidence failed to demonstrate superiority over placebo [2, 3]. Since that time, there have been a number of promising repurposed medications including colchicine [4], inhaled corticosteroids [5], and fluvoxamine [6-8], all of which have shown a relative risk reduction of 20%–30% in hospitalization. Novel therapeutics have emerged, such as customized antispike protein monoclonal antibody products, which have shown up to a 55%–85% relative risk reduction in hospitalization [9-11]. However, these therapies are not always widely available, are more challenging to administer, are comparatively expensive, and may have reduced efficacy against newer variants. Most recently, repurposed and novel antiviral therapies have attracted attention, with relative risk reductions of 30%–85% [12-16]. The US government has proactively purchased these agents based on prepublished data [17, 18]. For policy makers and/or health care professionals, especially those without ready access to novel therapeutics, the decision might be between supportive care or repurposed drugs. For well-resourced health care systems such those in North America, antispike monoclonal antibodies, remdesivir, and oral antiviral therapies cost significantly more, are available in relatively limited quantities, and can be more complex to procure and/or administer. Our objective was to systematically quantify the effect sizes of available treatments with respect to preventing hospitalization and then to contextualize those results against the expected drug costs per hospitalization prevented.

METHODS

Review of Literature and Estimations of Effect Size

To balance efficacy with potential toxicity, the outcome of interest we selected was all-cause hospitalization among outpatients. Where this was unavailable, we used COVID-19-related hospitalization (and have indicated this). Of note, use of the latter could underestimate toxicity, as hospitalizations due to drug side effects might be excluded. We used these results to calculate the relative risk for hospitalization with 95% CIs. Results for colchicine were taken from COLCORONA [4] and PRINCIPLE [19] and meta-analyzed using a fixed-effects model (I2 = 0.0%). For the inhaled corticosteroids, we used the results of our fixed-effects meta-analysis [5] of all available trials [20-23], with the caveat that the fixed-effects model may overestimate efficacy (I2 = 49.2%). For fluvoxamine, we obtained the number of all-cause hospitalizations in both arms directly from the authors of the 3 completed clinical trials [6, 7, 24]. In the TOGETHER trial [7], the authors originally included ER visits of ≥6 hours as a proxy for hospitalization due to the prohibitive number of admissions in Brazil exhausting capacity. To be more conservative, we chose only to include patients who spent >24 hours in the emergency department as equivalent to being hospitalized. The trial results were combined using a fixed-effects meta-analysis (I2 = 0.2%) [8]. Results for outpatient antispike protein antibody randomized controlled trials were limited to most recent phase 3 studies as most used an integrated phase 1/2/3 design that led to multiple publications describing the same patients. We limited our analysis to the latest phase 3 studies for bamlanivimab/etesevimab [9], casirivimab/imdevimab [10], and sotrovimab [11]. Bamlanivimab monotherapy was not included as it is no longer a recommended treatment. Of important note, it appears that casirivimab/imdevimab and bamlanivimab/etesevimab may not be effective against the Omicron variant [25]. Results for outpatient antiviral therapies included 1 phase 3 trial of remdesivir [15]. For molnupiravir, we included the published phase 3 trial [14], the analogous subgroup (≤5 days of symptoms and at least 1 high-risk criterion) from the phase 2 trial [26], and a press release from an Indian trial (fixed-effects model I2 = 47%; may overestimate efficacy) [12]. For nirmatrelvir with ritonavir, we relied on the Food and Drug Administration (FDA) Emergency Use Authorization [16] and press release interim analysis for a second trial [13]. A random-effects meta-analysis was conducted for a sensitivity analysis and is presented in the Supplementary Data. Recognizing that the field moves very quickly, we have developed a webpage (https://read.idtrials.com/outptcovid) that will be updated monthly at least until the end of 2022 to contain the most up-to-date efficacy and cost data possible.

Estimation of Costs

Where available, the lowest drug pricing was taken from GoodRx (www.goodrx.com). We chose budesonide for the inhaled corticosteroid analysis because it was the first corticosteroid to demonstrate a reduction in hospitalizations [22]. For antiviral and monoclonal antibody therapies, we used any publicly available data on US government purchasing and/or the manufacturer’s quoted price. Prices for injectable agents did not include the price of administration, which varies across agents. Societal costs were also not factored in and are beyond the scope of this analysis.

Estimation of Events Prevented and Costs per Event Prevented

For each drug, we took the estimates of relative risk of hospitalization and the 95% CI to generate the estimated absolute risk reduction (and CI) assuming a moderate baseline risk of hospitalization of 5%. Sensitivity analyses were conducted for 2.5% (low) and 10% (high) risk of hospitalization. For colchicine, where the CI touched 1.00 in the meta-analysis, we used an upper bound of 0.999 for calculating the NNT. By dividing 100 by the absolute risk reduction (rounded up), we estimated the number needed to treat (NNT) to prevent 1 hospitalization with corresponding CIs. We then multiplied the NNT by the drug costs per patient treated to arrive at the estimated drug cost to prevent 1 admission. For comparison, the mean cost of a COVID-19 admission to Medicare has been estimated at $21 752 [27].

Patient Consent

This study does not include factors necessitating patient consent.

RESULTS

The included studies are summarized in Table 1. The results of the analysis are presented in Figure 1 and Table 2, with a random-effects meta-analysis presented in Supplementary Figure 1. The repurposed drugs fluvoxamine and colchicine and inhaled corticosteroids had smaller effect sizes and larger numbers needed to treat assuming a 5% hospitalization risk at 80 (95% CI, 48–667), 91 (95% CI, 52–20 000), and 72 (95% CI, 45–400), respectively. By contrast, the antiviral and antibody therapies had larger effect sizes and smaller numbers needed to treat at 24 (95% CI, 22–29) for nirmatrelvir/ritonavir (COVID-19 hospitalization), 28 (95% CI, 23–80) for remdesivir, 50 (95% CI, 36–118) for molnupiravir, 25 (95% CI, 22–39) for sotrovimab, 29 (95% CI, 25–37) for casirivimab/imdevimab, and 29 (95% CI, 24–50) for bamlanivimab/etesevimab (COVID-19 hospitalization). However, the latter 2 antibody therapies likely do not retain activity against Omicron [25].
Table 1.

Summary of Included Clinical Trials

Study Location Original Primary Outcome Inclusion Criteria Demographics
Fluvoxamine
Stop Covid 1 (NCT04342663)USAClinical deterioration: hospitalization or new hypoxemia within 15 dAge ≥18 unvaccinatedPositive test with:≤7 d symptomsMedian age 46; 72% female; 70% White; 56% BMI ≥30; 20% hypertension; 11% diabetesMedian 4 d of symptoms
Stop Covid 2 (NCT04668950)USA and CanadaClinical deterioration: hospitalization or new hypoxemia within 15 dAge ≥30 unvaccinatedPositive test with:≤6 d symptomsCriterion for high riskMedian age 47; 62% female; 73% White; 44% BMI ≥30; 21% hypertension; 9% diabetesMedian 5 d of symptoms
Together (NCT04727424)BrazilER visit ≥6 h or hospitalization within 28 dAge ≥18 unvaccinatedPositive test with:≤7 d symptomsCriterion for high riskMedian age 50; 55% female; 96% mixed race; 51% BMI ≥30; 13% hypertension; 16% diabetesMean 3.8 d of symptomsb
Colchicine
Colcorona (NCT04322682)Multiple countries (majority Canada)COVID-19-related hospitalization or death from any causeAge ≥40 unvaccinated93% had positive test with:Diagnosis within 24 hCriterion for high riskMedian age 53–54; 54% female; 93% White; mean BMI 30; 36% hypertension; 20% diabetesMean 5.3 d of symptoms
PRINCIPLEa (ISRCTN86534580)UKCOVID-19-related hospitalization or death from any causeAge ≥65 or age ≥18 with comorbidity or dyspnea58% vaccinated ≥1 doseaPositive test with ongoing symptoms of fever, new continuous cough, or change in smell or taste within 14 dMedian age 48; 54% female; 89% White; BMI not reported; 24% hypertension; 13% diabetesMedian 6 d of symptoms
Inhaled corticosteroids
STOICa (NCT04416399)UKCOVID-19 urgent visitsAge ≥18 unvaccinated94% had positive test with:≤7 d of symptoms (≥1 of cough and fever or anosmia)Mean age 45; 56% female; 93% White; mean BMI 26–27; N/A hypertension; 4% diabetesMedian 3 d of symptoms
CONTAIN (NCT04435795)CanadaResolution of cough, dyspnea, and fever day 7Age ≥18 unvaccinatedPositive test with:≤6 d of symptoms (≥1 of fever, cough, or dyspnea)Median age 35; 54% female; 61% White; BMI not reported; 6% hypertension; 3% diabetesDuration of symptoms not reported
Covis Pharma (NCT04377711)USATime to symptom-freeAge ≥12 unvaccinatedPositive test with:≥1 of fever, cough, or dyspneaMean age 43; 55% female; 86% White; mean BMI 29.4; 22% hypertension; 8% diabetesDuration of symptoms not reported
PRINCIPLEa (ISRCTN86534580)UKCOVID-19-related hospitalization or death from any causeAge ≥65 or ≥50 with comorbidity14% vaccinated ≥1 doseaPositive test with ongoing symptoms of fever, new continuous cough, or change in smell or taste within 14 dMean age 64–65; 51% female; 93% White; BMI not reported; 45% hypertension; 21% diabetesMean 6 d of symptoms
Nirmatrelvir/ritonavir
EPIC-HR (NCT04960202)Multiple countries (USA 45%)COVID-19-related hospitalization or death from any causeAge ≥18 unvaccinatedPositive test with:≤5 d of symptoms (≥1 at randomization)Criterion for high riskBased on FDA Emergency Use Authorization:Mean age 46; 49% female; 72% White; 36% BMI ≥30; NA hypertension; 12% diabetes66% had symptoms ≤3 d
EPIC-SR (NCT05011513)Multiple countriesTime to sustained alleviation of all targeted COVID-19 signs/symptomsAge ≥18 unvaccinatedPositive test with:≤5 d symptomsVaccinated if criterion for high riskaNot available at time of this analysis
Molnupiravir
Hetero Pharmaa (CTRI2021/05/033739)IndiaHospitalizationAge ≥18 and ≤60 (vaccination unspecified)Positive test with:≤5 d of symptomsNot available at time of this analysis
MOVe-Out Ph 2 (NCT04575597)MultipleAll-cause hospitalization or death (included ER visit ≥24 h)Age ≥18 unvaccinatedPositive test with:≤7 d of symptoms (at least 1 at randomization)≥75% with criterion for high riskMean age 49; 47% female; 72% White;49% BMI ≥30; NA hypertension; 17% diabetes67% had symptoms ≤5 d
MOVe-Out (NCT04575597)Multiple countries (majority Latin America)All-cause hospitalization or death (included ER visit ≥24 h)Age ≥18 unvaccinatedPositive test with:≤5 d of symptoms (≥1 at randomization)Criterion for high riskMedian age 43; 51% female; 79% White;74% BMI ≥30; N/A hypertension; 16% diabetes48% had symptoms ≤3 d
Remdesivir
PINETREE (NCT04501952)Multiple countries (95% USA)COVID-19-related hospitalization or all-cause deathAge ≥18 unvaccinated:Positive test with:≤7 d of symptomsCriterion for high riskMean age 50; 48% female; 80% White;55% BMI ≥30; 48% hypertension; 62% diabetesMedian duration of symptoms 5 d
Antibody therapies
Sotrovimab (NCT04545060)Multiple countries (92% USA)Hospitalization for ≥24 h or deathAge ≥18 unvaccinatedPositive test with:≤5 d of symptomsCriterion for high riskMedian age 53; 54% female; 87% White; mean BMI 32; N/A hypertension; 22% diabetes59% had duration of symptoms ≤3 d
Casirivimab/imdevimab (NCT04425629)USA and MexicoCOVID-19-related hospitalization or death from any causeAge ≥18 unvaccinatedPositive test with:≤7 d of symptomsCriterion for high riskMedian age 48–50; 52% female; 84% White; 57% BMI ≥30; 36% hypertension; 15% diabetesMedian duration of symptoms 3 d
Bamlanivimab/etesevimab (NCT04427501)USACOVID-19-related hospitalization or death from any causeAge ≥12 unvaccinatedPositive test with:SymptomsCriterion for high riskMean age 54; 52% female; 87% White; mean BMI 34; 34% hypertension; 28% diabetesMedian duration of symptoms 4 d

Abbreviations: BMI, body mass index; COVID-19, coronavirus disease 2019; ER, emergency room; FDA, Food and Drug Administration.

Open label.

Missing data on ~23%.

Figure 1.

Effect sizes of the various drugs on hospitalization. aUrgent care, emergency room, or hospitalization. bBased on COVID-19 hospitalization because all-cause not available. cSubgroups and doses matched the phase 3 trial. Abbreviation: COVID-10, coronavirus disease 2019.

Table 2.

Number Needed to Treat and Costs per Hospitalization Prevented

Number Needed to TreatCost per Hospitalization Prevented
DrugCost/Patient2.5% Risk 5% Risk 10% Risk 2.5% Risk 5% Risk 10% Risk
Fluvoxamine (meta-analysis)14160 (96–1334)80 (48–667)40 (24–334)2244 (1346–18 709)1122 (673–9355)561 (337–4684)
Colchicine (meta-analysis)37182 (103–40 000)91 (52–20 000)46 (26–10 000)6667 (3773–1 465 200)3333 (1905–732 600)1685 (952–366 300)
Inhaled corticosteroids (meta-analysis)a132143 (89–800)72 (45–400)36 (23–200)18 819 (11 712–105 280)9475 (5922–52 640)4738 (3027–26 320)
Nirmatrelvir/ritonavir (meta-analysis)b53048 (44–57)24 (22–29)12 (11–15)25 440 (23 320–30 210)12 720 (11 660–15 370)6360 (5830–7950)
Molnupiravir (meta-analysis)a700100 (72–236)50 (36–118)25 (18–59)70 000 (50 400–165 200)35 000 (25 200–82 600)17 500 (12 600–41 300)
Remdesivir (phase 3)187256 (45–160)28 (23–80)14 (12–40)104 832 (84 240–299 520)52 416 (43 056–149 760)26 208 (22 464–74 880)
Sotrovimab (phase 3)210050 (44–77)25 (22–39)13 (11–20)105 000 (92 400–161 700)52 500 (46 200–81 900)27 300 (23 100–42 000)
Casirivimab/imdevimab (phase 3)210057 (50–73)29 (25–37)15 (13–19)119 700 (105 000–153 300)60 900 (52 500–77 700)31 500 (27 300–39 900)
Bamlanivimab/etesevimab (phase 3)b210058 (48–99)29 (24–50)15 (12–25)121 800 (100 800–207 900)60 900 (50 400–105 000)31 500 (25 200–52 500)

Lowest drug prices for repurposed therapy (eg, GoodRx) may underestimate the costs of acquisition for patients/drug plans. Monoclonal antibody and remdesivir prices do not include price of administration. Shaded monoclonal antibodies likely have significantly reduced efficacy against the Omicron variant.

Abbreviation: COVID-19, coronavirus disease 2019.

Fixed-effects models had moderate heterogeneity.

All-cause hospitalization not provided; COVID-19-related hospitalizations used, which may inflate efficacy.

Summary of Included Clinical Trials Abbreviations: BMI, body mass index; COVID-19, coronavirus disease 2019; ER, emergency room; FDA, Food and Drug Administration. Open label. Missing data on ~23%. Number Needed to Treat and Costs per Hospitalization Prevented Lowest drug prices for repurposed therapy (eg, GoodRx) may underestimate the costs of acquisition for patients/drug plans. Monoclonal antibody and remdesivir prices do not include price of administration. Shaded monoclonal antibodies likely have significantly reduced efficacy against the Omicron variant. Abbreviation: COVID-19, coronavirus disease 2019. Fixed-effects models had moderate heterogeneity. All-cause hospitalization not provided; COVID-19-related hospitalizations used, which may inflate efficacy. Effect sizes of the various drugs on hospitalization. aUrgent care, emergency room, or hospitalization. bBased on COVID-19 hospitalization because all-cause not available. cSubgroups and doses matched the phase 3 trial. Abbreviation: COVID-10, coronavirus disease 2019. At a 5% risk of hospitalization, the corresponding drug costs per hospitalization prevented were $1122 (95% CI, $673–$9355) for fluvoxamine, $3333 (95% CI, $1905–$732 600) for colchicine, $9475 (95% CI, $5922–$52 640) for inhaled corticosteroids, $12 720 (95% CI, $11 660–$15 370) for nirmatrelvir/ritonavir, $35 000 (95% CI, $25 200–$82 600) for molnupiravir, $52 416 (95% CI, $43 056–$149 760) for remdesivir, $52 500 (95% CI, $46 200–$81 900) for sotrovimab, $60 900 (95% CI, $52 500–$77 700) for casirivimab/imdevimab, and $60 900 (95% CI, $50 400–$10 500) for bamlanivimab/etesevimab.

DISCUSSION

Scientific advancement has been exponential during the pandemic. We have gone from the discovery of a new disease with no treatment in December 2019 to numerous effective vaccines coupled with a suite of proven therapies that prevent hospitalization and, by extension, presumably impact progression to death. Within these treatments, several are inexpensive and widely available worldwide, while others are expensive, limited in availability, and/or limited in accessibility. The purpose of this review was to contrast the efficacy of these therapies against a measure of cost. Evidence suggests that the antiviral therapies and monoclonal antibodies are more effective than repurposed drugs. While we show that this efficacy comes at a price that often exceeds that of COVID-19 hospitalization, this was not a formal cost-effectiveness analysis and we did not factor in death, long-term outcomes, societal costs, patient preferences, or costs of administration. The higher an individual’s baseline risk of deterioration, the greater the absolute benefit and less costly these options become. If one conservatively estimates a risk of death of 5%–10% for those who are hospitalized, the NNTs for death (and costs) would be ~10–20 times higher. Furthermore, some of these therapies have already been purchased, which necessarily alters the dialogue. Essentially, at the right price or if prescribed to a high enough risk individual, most drugs on this list have the potential to be cost-saving to the system as a whole. Accurate country-specific models for prediction of hospitalization risk will be essential in contextualizing and maximizing the benefits of any therapy. This analysis has several limitations. First, most of the agents studied have only had a single positive randomized controlled trial, and several are prepublication. Replication in science is important, and while the pandemic necessitated speed, which led to single trials, with many vaccinations and outpatient therapy options now available, the safeguards of confirmatory trials are likely needed for reproducibility and generalizability. Second, some of the data are currently limited to government documents and press releases. In normal times, peer-reviewed results would be required; however, major decisions are being made based on industry public relations material, confidential submissions, and limited data [17, 18], and our analysis can serve to inform those conversations elsewhere. Third, our sensitivity analysis for inhaled corticosteroids found that the benefits were not statistically significant in the random-effects model, and thus the results of this current analysis are predicated on additional trials confirming that these drugs have benefit. Fourth, the efficacy of antispike protein antibodies requires ongoing confirmation for emerging variants, as there are suggestions that some therapies may no longer be as effective against Omicron [25]. Fifth, 2 molnupiravir trials [14, 26] and 1 fluvoxamine trial [7] included emergency room visits of >24 hours in their outcomes, which may not necessarily be completely exchangeable with hospitalizations. Sixth, drug prices from GoodRx likely represent the lowest drug pricing, and costs for some patients could be substantially higher. Finally, very few patients in these clinical trials were vaccinated, and the risk for hospitalization may not be the same in vaccinated patients. Nonetheless, hospitalization in vaccinated patients can be estimated [28], and this is one of the reasons we present sensitivity analyses for different baseline risks of hospitalization. Prospective studies in vaccinated patients are urgently needed. There is an ongoing need to identify effective treatments that can be administered early in the disease course to prevent COVID-19 hospitalization and death and to make them available and accessible in all regions. While many countries worldwide are fortunate to have access to novel treatments, the number and location of available doses may wax and wane over time, and access may be challenging in remote regions or in congregate care settings. Some degree of decision-making will be required at the level of the individual clinician, hospitals, and regional and federal governments to prioritize deployment of therapies and capacity-building. This analysis provides one means of contextualizing those discussions.

Supplementary Data

Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author. Click here for additional data file.
  19 in total

1.  Fluvoxamine vs Placebo and Clinical Deterioration in Outpatients With Symptomatic COVID-19: A Randomized Clinical Trial.

Authors:  Eric J Lenze; Caline Mattar; Charles F Zorumski; Angela Stevens; Julie Schweiger; Ginger E Nicol; J Philip Miller; Lei Yang; Michael Yingling; Michael S Avidan; Angela M Reiersen
Journal:  JAMA       Date:  2020-12-08       Impact factor: 56.272

2.  Hydroxychloroquine for Early Treatment of Adults With Mild Coronavirus Disease 2019: A Randomized, Controlled Trial.

Authors:  Oriol Mitjà; Marc Corbacho-Monné; Maria Ubals; Cristian Tebé; Judith Peñafiel; Aurelio Tobias; Ester Ballana; Andrea Alemany; Núria Riera-Martí; Carla A Pérez; Clara Suñer; Pep Laporte; Pol Admella; Jordi Mitjà; Mireia Clua; Laia Bertran; Maria Sarquella; Sergi Gavilán; Jordi Ara; Josep M Argimon; Jordi Casabona; Gabriel Cuatrecasas; Paz Cañadas; Aleix Elizalde-Torrent; Robert Fabregat; Magí Farré; Anna Forcada; Gemma Flores-Mateo; Esteve Muntada; Núria Nadal; Silvia Narejos; Aroa Nieto; Nuria Prat; Jordi Puig; Carles Quiñones; Juliana Reyes-Ureña; Ferran Ramírez-Viaplana; Lidia Ruiz; Eva Riveira-Muñoz; Alba Sierra; César Velasco; Rosa Maria Vivanco-Hidalgo; Alexis Sentís; Camila G-Beiras; Bonaventura Clotet; Martí Vall-Mayans
Journal:  Clin Infect Dis       Date:  2021-12-06       Impact factor: 9.079

3.  Inhaled budesonide in the treatment of early COVID-19 (STOIC): a phase 2, open-label, randomised controlled trial.

Authors:  Sanjay Ramakrishnan; Dan V Nicolau; Beverly Langford; Mahdi Mahdi; Helen Jeffers; Christine Mwasuku; Karolina Krassowska; Robin Fox; Ian Binnian; Victoria Glover; Stephen Bright; Christopher Butler; Jennifer L Cane; Andreas Halner; Philippa C Matthews; Louise E Donnelly; Jodie L Simpson; Jonathan R Baker; Nabil T Fadai; Stefan Peterson; Thomas Bengtsson; Peter J Barnes; Richard E K Russell; Mona Bafadhel
Journal:  Lancet Respir Med       Date:  2021-04-09       Impact factor: 30.700

4.  Molnupiravir for Oral Treatment of Covid-19 in Nonhospitalized Patients.

Authors:  Angélica Jayk Bernal; Monica M Gomes da Silva; Dany B Musungaie; Evgeniy Kovalchuk; Antonio Gonzalez; Virginia Delos Reyes; Alejandro Martín-Quirós; Yoseph Caraco; Angela Williams-Diaz; Michelle L Brown; Jiejun Du; Alison Pedley; Christopher Assaid; Julie Strizki; Jay A Grobler; Hala H Shamsuddin; Robert Tipping; Hong Wan; Amanda Paschke; Joan R Butterton; Matthew G Johnson; Carisa De Anda
Journal:  N Engl J Med       Date:  2021-12-16       Impact factor: 91.245

5.  Effect of early treatment with fluvoxamine on risk of emergency care and hospitalisation among patients with COVID-19: the TOGETHER randomised, platform clinical trial.

Authors:  Gilmar Reis; Eduardo Augusto Dos Santos Moreira-Silva; Daniela Carla Medeiros Silva; Lehana Thabane; Aline Cruz Milagres; Thiago Santiago Ferreira; Castilho Vitor Quirino Dos Santos; Vitoria Helena de Souza Campos; Ana Maria Ribeiro Nogueira; Ana Paula Figueiredo Guimaraes de Almeida; Eduardo Diniz Callegari; Adhemar Dias de Figueiredo Neto; Leonardo Cançado Monteiro Savassi; Maria Izabel Campos Simplicio; Luciene Barra Ribeiro; Rosemary Oliveira; Ofir Harari; Jamie I Forrest; Hinda Ruton; Sheila Sprague; Paula McKay; Alla V Glushchenko; Craig R Rayner; Eric J Lenze; Angela M Reiersen; Gordon H Guyatt; Edward J Mills
Journal:  Lancet Glob Health       Date:  2021-10-28       Impact factor: 38.927

6.  Inhaled corticosteroids for outpatients with COVID-19: a meta-analysis.

Authors:  Todd C Lee; Émilie Bortolussi-Courval; Sara Belga; Nick Daneman; Adrienne K Chan; Ryan Hanula; Nicole Ezer; Emily G McDonald
Journal:  Eur Respir J       Date:  2022-05-05       Impact factor: 33.795

7.  Hydroxychloroquine in Nonhospitalized Adults With Early COVID-19 : A Randomized Trial.

Authors:  Caleb P Skipper; Katelyn A Pastick; Nicole W Engen; Ananta S Bangdiwala; Mahsa Abassi; Sarah M Lofgren; Darlisha A Williams; Elizabeth C Okafor; Matthew F Pullen; Melanie R Nicol; Alanna A Nascene; Kathy H Hullsiek; Matthew P Cheng; Darlette Luke; Sylvain A Lother; Lauren J MacKenzie; Glen Drobot; Lauren E Kelly; Ilan S Schwartz; Ryan Zarychanski; Emily G McDonald; Todd C Lee; Radha Rajasingham; David R Boulware
Journal:  Ann Intern Med       Date:  2020-07-16       Impact factor: 25.391

8.  Inhaled budesonide for COVID-19 in people at high risk of complications in the community in the UK (PRINCIPLE): a randomised, controlled, open-label, adaptive platform trial.

Authors:  Ly-Mee Yu; Mona Bafadhel; Jienchi Dorward; Gail Hayward; Benjamin R Saville; Oghenekome Gbinigie; Oliver Van Hecke; Emma Ogburn; Philip H Evans; Nicholas P B Thomas; Mahendra G Patel; Duncan Richards; Nicholas Berry; Michelle A Detry; Christina Saunders; Mark Fitzgerald; Victoria Harris; Milensu Shanyinde; Simon de Lusignan; Monique I Andersson; Peter J Barnes; Richard E K Russell; Dan V Nicolau; Sanjay Ramakrishnan; F D Richard Hobbs; Christopher C Butler
Journal:  Lancet       Date:  2021-08-10       Impact factor: 79.321

9.  mRNA booster immunization elicits potent neutralizing serum activity against the SARS-CoV-2 Omicron variant.

Authors:  Henning Gruell; Kanika Vanshylla; Florian Kurth; Leif E Sander; Florian Klein; Pinkus Tober-Lau; David Hillus; Philipp Schommers; Clara Lehmann
Journal:  Nat Med       Date:  2022-01-19       Impact factor: 53.440

10.  Bamlanivimab plus Etesevimab in Mild or Moderate Covid-19.

Authors:  Michael Dougan; Ajay Nirula; Masoud Azizad; Bharat Mocherla; Robert L Gottlieb; Peter Chen; Corey Hebert; Russell Perry; Joseph Boscia; Barry Heller; Jason Morris; Chad Crystal; Awawu Igbinadolor; Gregory Huhn; Jose Cardona; Imad Shawa; Princy Kumar; Andrew C Adams; Jacob Van Naarden; Kenneth L Custer; Michael Durante; Gerard Oakley; Andrew E Schade; Timothy R Holzer; Philip J Ebert; Richard E Higgs; Nicole L Kallewaard; Janelle Sabo; Dipak R Patel; Matan C Dabora; Paul Klekotka; Lei Shen; Daniel M Skovronsky
Journal:  N Engl J Med       Date:  2021-07-14       Impact factor: 91.245

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  4 in total

1.  Implementing Early Phase Treatments for COVID-19 in Outpatient Settings: Challenges at a Tertiary Care Center in Italy and Future Outlooks.

Authors:  Tommaso Manciulli; Filippo Lagi; Anna Barbiero; Marco Fognani; Nicoletta Di Lauria; Costanza Malcontenti; Costanza Fiorelli; Michele Spinicci; Vega Ceccherini; Paola D'Onofrio; Manuela Angileri; Francesca Malentacchi; Michele Cecchi; Gian Maria Rossolini; Matteo Tomaiuolo; Lorenzo Zammarchi; Alessandro Bartoloni
Journal:  Infect Dis Rep       Date:  2022-04-25

Review 2. 

Authors:  Emily G McDonald; Todd C Lee
Journal:  CMAJ       Date:  2022-03-07       Impact factor: 16.859

3.  Real-world effectiveness of molnupiravir and nirmatrelvir plus ritonavir against mortality, hospitalisation, and in-hospital outcomes among community-dwelling, ambulatory patients with confirmed SARS-CoV-2 infection during the omicron wave in Hong Kong: an observational study.

Authors:  Carlos K H Wong; Ivan C H Au; Kristy T K Lau; Eric H Y Lau; Benjamin J Cowling; Gabriel M Leung
Journal:  Lancet       Date:  2022-10-08       Impact factor: 202.731

4.  Nirmatrelvir-ritonavir for COVID-19.

Authors:  Emily G McDonald; Todd C Lee
Journal:  CMAJ       Date:  2022-02-03       Impact factor: 16.859

  4 in total

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