Literature DB >> 34687413

Efficacy of Interferon-β in Moderate-to-Severe Hospitalised Cases of COVID-19: A Systematic Review and Meta-analysis.

Subodh Kumar1, Manoj Kumar Saurabh1, Venkata Lakshmi Narasimha1, Vikas Maharshi2.   

Abstract

BACKGROUND AND
OBJECTIVE: Interferon-β, as with several other anti-viral agents, has been investigated as a treatment option for COVID-19 as a repurposed drug. The present study is a systematic review and meta-analysis of interferon-β to determine its efficacy among moderate-to-severe COVID-19 patients.
METHODS: A systematic literature search was done using relevant terms for 'COVID-19' and 'interferon-β'. Randomised controlled trials (RCT) evaluating the efficacy of interferon-β in COVID-19 were included. Data were extracted for outcome measures, namely mortality, time to clinical improvement and length of hospital stay. Random effects meta-analysis was performed using RevMan V.5.4.1 to calculate overall effect estimate as odds ratio/hazard ratio for categorical variables and mean difference for continuous variable. RESULT: Eight RCTs were eligible for qualitative synthesis and seven for meta-analysis. The overall effect estimate (odds ratio [OR] 0.59; 95 % CI 0.91, 1.12) and (mean difference [MD] - 1.41; 95 % CI - 2.84, 0.02) indicated no statistically significant difference between effect of IFN-β and that of control on mortality and length of hospital stay, respectively. However, the overall effect estimate (hazard ratio [HR] 1.95; 95 % CI 1.36, 2.79) denoted a favourable effect of INF-β on reducing the time to clinical improvement in moderate-to-severe COVID-19 patients.
CONCLUSION: Addition of interferon-β to standard of care resulted in significant reduction in time to clinical improvement but no significant benefit in terms of reduction in mortality and length of hospital stay in moderate-to-severe cases of COVID-19.
© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.

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Year:  2021        PMID: 34687413      PMCID: PMC8540871          DOI: 10.1007/s40261-021-01092-9

Source DB:  PubMed          Journal:  Clin Drug Investig        ISSN: 1173-2563            Impact factor:   2.859


Key Points

Introduction

Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), the causative factor for Coronavirus disease 2019 (COVID-19), like SARS-CoV and Middle-East respiratory syndrome coronavirus (MERS-CoV), is a member of the beta Coronaviridae family of Coronaviruses [1]. COVID-19 pandemic has affected approximately 235 million individuals, resulting in more than four million fatalities, according to the World Health Organization (WHO) [2]. Symptoms of the disease may range from fever, cough, sore throat and rhinorrhoea to severe pneumonia and septic shock. A few patients develop acute respiratory distress syndrome (ARDS), which leads to admission to the intensive care unit (ICU) and possible mortality in a significant proportion of patients [3, 4]. Despite great efforts across the world to find potential therapeutic agents, a handful of the medicines have been approved for emergency use, and none has been accepted globally as definitive treatment of this disease. Therefore, search for effective pharmacotherapy against COVID-19 is still ongoing. Literature suggests that COVID-19 severity may correlate with interferon-beta (IFN-β) levels in the body [5]. Interferons are well known for their antiviral as well as immunomodulatory properties. These are classified as type I, II and III IFNs. Type I IFNs are IFN-α, IFN-β, IFN-ω, IFN-κ and IFN-τ [6-8]. Type I IFNs have been found to reduce SARS-CoV-2 replication in Vero E6 cells in vitro assay, viral antigen expression, viral load reduction and plaque reduction assays [9]. Furthermore, IFN-β1b has been shown to have potential to reduce virus-induced lung fibrosis in a mouse model, which could be advantageous for COVID-19 patients with ARDS [10]. It has been found that SARS-CoV-2 could prevent IFN production by such mechanisms as escaping from recognition by pattern recognition receptors [11, 12], interfering with retinoic acid-inducible gene I or toll-like receptor signalling [13] and inhibiting phosphorylation of interferon regulatory factor 3 and its activation [14]. Because of its antiviral and immunomodulatory properties, IFN-β has been and is being investigated for management of COVID-19, especially the severe form of the disease. Variable results of treatment with IFN on COVID-19 have been found in clinical trials; therefore, a systematic review and meta-analysis was planned. The objectives of this systematic review and meta-analysis are to assess the effect(s) of IFN-β therapy in moderate-to-severe cases of COVID-19 in terms of mortality, length of hospital stay (LOHS) and time to clinical improvement, to help make decisions regarding selection of this drug as a therapeutic option for treatment of this disease.

Materials and Methods

Literature Search Strategy

Literature search was done in PubMed/MedLine, Google Scholar, EMBASE and SCOPUS. PubMed search was performed using terms namely ‘Coronavirus Infection’, ‘COVID-19’, ‘SARS-CoV-2’, ‘severe acute respiratory syndrome coronavirus 2’ in combination with ‘Interferon beta’, ‘Interferon β’ and ‘IFN-β’. Search in Google scholar, EMBASE and SCOPUS was made using keyword ‘Interferon beta for COVID-19’. Last search was made on July 31, 2021. This review was registered with PROSPERO (registration number CRD42021262804).

Inclusion/Exclusion Criteria

Randomised controlled trials (published up to July 2021) comparing efficacy of IFN-β to that of standard of care in terms of mortality, LOHS, and/or time to clinical improvement, were included. Studies with significant inconsistency between experimental and control groups and studies with use of IFN-beta in experimental as well as in control study arms, were excluded from meta-analysis (Table 1).
Table 1

Characteristics of included studies

Author/year/trial IDStudy designPopulationIntervention armComparator armOutcome(s) measuredDosage of INF
Hung et al. 2020 (NCT04276688) [10]Open-label RCTHospitalised adults with COVID-19IFN-β1b + ribavirin + SOCaSOCa

1o Viral negativity

2o Time to resolution of symptoms,

duration of hospitalisation

Mortality

SC, 8 MIU on alternate days, three doses
Monk et al. 2021 (NCT04385095) [16]Double-blind RCTHospitalised adults with COVID-19IFN-β1a + SOCbPlacebo + SOCb

1o Time to clinical improvement

2o Discharge from hospital

Inhalation, 6 MIU once daily for up to 14 days
Khamis et al. 2021 [17]Open-label RCTHospitalised adults with moderate-to-severe COVID-19Favipiravir with IFN-β1bHCQ

1o Time to clinical improvement,

2o Normalisation of inflammatory markers, improvement in oxygen saturation

Inhalation, 8 MIU (0.25 mg) twice a

day was given for 5 days

Rahmani et al. 2020 (IRCT20100228003449N27) [18]Open-label RCTHospitalised adults with severe COVID-19IFN-β1b + SOCcSOCc

1o Time to clinical improvement

2o Percentage

of patients discharged, duration of hospitalisation

SC, 250 mcg every other day for two weeks
Davoudi-Monfared et al. 2020 (IRCT20100228003449N28) [19]Open-label RCTHospitalised adults with severe COVID-19IFN-β1a + SOCcSOCc

1o Time to clinical improvement

2o Percentage of patients discharged, duration of hospitalisation

SC, 12 MIU every other day for two weeks
Darazam et al. 2021 (NCT04343768) [20]Open-label RCTHospitalised adults with severe COVID-19

1.IFN-β1a + SOCd

2. IFN-β1b + SOCd

SOCd

1o Time to clinical improvement

2o Mortality, duration of hospitalisation

1. IFN-β1a: SC, 12,000 IU/44 mcg on days 1, 3, 6

2. IFN-β1b: SC, 8 MIU on Days 1, 3, 6

WHO solidarity trial. 2020 (NCT04315948) [21]Open-label RCTHospitalised adults with COVID-19IFN-β1a + LPV/r + SOCSOC + LPV/r

1o Mortality

2o Initiation of mechanical ventilation, duration of hospitalisation

SC, 44 mcg, on Days 1, 3 & 6

IV, 10 mcg daily for 6 days

Darazam et al. 2021 (NCT04521400) [22]RCTHospitalised adults with COVID-19IFN-β1a (high dose) + LPV/r + SOCIFN-β1a (low dose) + LPV/r + SOC

1o Time to clinical improvement

2o Mortality

SC, 88 mcg (24 MIU) on days 1, 3, 6

SC, 44 mcg (12 MIU) on Days 1, 3, 6

1o Primary outcome, 2o Secondary outcome

ATV/r atazanavir and ritonavir combination, COVID-19 Coronavirus disease 2019, HCQ hydroxychloroquine, IFN interferon, IU International Unit, IV intravenous, LPV/r lopinavir and ritonavir combination, mcg microgram, MIU million/mega International Unit, RCT randomized controlled trial, SC subcutaneous, SOC standard of care

aLPV/r[10]

bLocal standard of care[16]

c+ LPV/r or ATV/r + HCQ for 7–10 days [18, 19]

dLPV/r + HCQ single dose[20]

Data Extraction and Quality Assessment

Two reviewers screened the search results with titles and abstracts to find eligible studies. Then the full text of initially screened studies was accessed and data from intervention and control group were recorded in Microsoft Excel. The main data fields were authors, year of publication, trial identifier, study design, population, sample size, intervention(s), comparator(s), dosage and outcome(s) measured. The quality of each study was evaluated independently by ‘Cochrane Risk of Bias assessment tool version 2’ (RoB 2), which had the facility to assess for randomisation, allocation concealment, blinding, completeness and other sources of bias(es). The response options for each risk of bias judgement were low risk, some concern and high risk of bias.

Outcome Indicators

The eligible studies included hospitalised patients with moderate-to-severe COVID-19. The outcome parameters of this systematic review and meta-analysis were: (1) hospital mortality, measured in terms of proportion of participants dying between days 14–28 days (duration of study), (2) LOHS, number of days spent by participants in the hospital from the day of admission up to the day of their discharge and (3) time to clinical improvement, defined as time in terms of days required for improvement of score at least by ‘2’ points on an ordinal scale, namely National Early Warning Score 2 (NEWS2) scale [15] and/or WHO clinical progression scale [16].

Statistical Analysis

Data were entered into the Microsoft Excel. Meta-analyses were done using the software ‘Review Manager (RevMan)’ version 5.4.1 using random effect model. Relevant summary measures of efficacy were assessed using the odds ratio (OR), hazard ratio (HR) and/or mean difference (MD) for applicable variables along with corresponding 95 % confidence interval (CI). Cochrane ‘Q’ statistic was applied for statistical heterogeneity, which was quantified using the I2 statistic. I2 value below 30 was considered as ‘low’, 30–59 as ‘moderate’, 60–74 as ‘substantial’ and ≥ 75 as considerable heterogeneity. A p value of < 0.05 was considered as statistically significant.

Results

The initial search identified 1338 potential citations, of which 65 records were screened and the rest were excluded by looking into the titles and/or abstracts. Twenty-four records were found to be original research articles and were assessed for eligibility. Of these 24 studies, 16 were excluded as they were either nonclinical or non-randomised studies. The remaining eight studies [10, 16–22] were included in qualitative synthesis (systematic review), but one study [22] was excluded from meta-analysis as it used IFN in experimental as well as in the control arm. All seven of the remaining articles were included in the meta-analysis (Fig. 1).
Fig. 1

PRISMA flow chart showing inclusion of studies in systematic review and meta-analysis

PRISMA flow chart showing inclusion of studies in systematic review and meta-analysis

Outcome Parameters

Mortality

In all the seven studies included in meta-analysis, mortality was one of the study outcomes. One of the included studies [10] did not find death in any of the study arms; however, it has been retained in the analysis as mortality as an outcome was evaluated in this study. Random effect model was used for meta-analysis. Number of events was put in the software and calculated odds ratio was used for interpretation. The overall effect estimate [OR 0.59; 95 % CI 0.91, 1.12] indicates no statistically significant difference between effect of IFN-β and that of control on mortality. Overall heterogeneity was moderate with I2 value of 57 % which was statistically significant (p = 0.04). A sensitivity analysis, performed to exclude ‘WHO SOLIDARITY trial’ [21] (accounting for the larger sample size), showed a significantly lower mortality in IFN-β intervention than that in control arm (Fig. 2A).
Fig. 2

Forest plots for various outcome parameters included in meta-analysis: A mortality; B length of hospital stay; C time to clinical improvement. CI confidence interval, IFN interferon, SD standard deviation

Forest plots for various outcome parameters included in meta-analysis: A mortality; B length of hospital stay; C time to clinical improvement. CI confidence interval, IFN interferon, SD standard deviation

Length of Hospital Stay

The LOHS was one of the study outcomes in four of the seven studies. One study [20] had two experimental arms (with IFN-β1a and IFN-β1b as two interventions, respectively), which were compared with control. The results of both these experimental arms have been included separately for meta-analysis. Random-effect model was used for analysis. The overall effect estimate, (MD − 1.41; 95 % CI − 2.84, 0.02) denotes a marginally favourable effect of INF-β on decreasing the LOHS compared to that of control, but effect was not statistically significantly different (p = 0.05) from that shown by control. Substantial heterogeneity with I2 value of 64 % was found among studies (Fig. 2B).

Time to Clinical Improvement

The data on time to clinical improvement have been reported in four of the studies. As mentioned above, results of two experimental arms (IFN-β1a and IFN-β1b) from one study [20] are used separately here as well, for meta-analysis. Random effect model was used during analysis. Overall effect estimate (HR 1.95; 95 % CI 1.36, 2.79) shows significantly less (p = 0.0003) time to clinical improvement with IFN-β intervention than that with the control. Moderate heterogeneity (I2 39 %) was found among the studies (Fig. 2C).

Risk of Bias Assessment for Included Studies

Of seven randomised controlled trials, two were deemed to be of ‘high-risk’, another two were of ‘some concern’ and the rest were regarded as having ‘low risk’ following assessment of risk of bias through Cochrane’s RoB-II tool (Fig. 3).
Fig. 3

Traffic light plot for risk of bias assessment through Cochrane RoB2 tool: A summary diagram; B percentile chart. indicates low risk; indicates some concern; indicates high risk

Traffic light plot for risk of bias assessment through Cochrane RoB2 tool: A summary diagram; B percentile chart. indicates low risk; indicates some concern; indicates high risk

Publication Bias

Funnel plot test has minimal role in cases where the number of included studies is less than 10. However, to meet the requirement of PRISMA checklist, using the inverted funnel plot method, a scatter diagram was generated with the OR on the abscissa and standard error (log [OR]) on the ordinate. Number of studies included in this meta-analysis was insufficient to distinguish a chance from real asymmetry (Fig. 4).
Fig. 4

Funnel plot of publication bias of randomised controlled trials included in meta-analysis. Six studies are shown because one study [10] had number of events as ‘0’; however, because mortality was assessed as one of the outcome parameters, the study was included in the meta-analysis. OR odds ratio,  SE standard error

Funnel plot of publication bias of randomised controlled trials included in meta-analysis. Six studies are shown because one study [10] had number of events as ‘0’; however, because mortality was assessed as one of the outcome parameters, the study was included in the meta-analysis. OR odds ratio,  SE standard error

Discussion

IFN-β, a subtype of type I IFN, has been investigated widely as one of the treatment options for COVID-19 as a repurposed drug [11, 16–22]. The present piece of work is a systematic review and meta-analysis of the randomised controlled trials evaluating the efficacy of IFN-β in terms of mortality, LOHS and time to clinical improvement. Although latter two parameters seem to be overlapping and measuring the same clinical outcome, there is a subtle difference between these two outcome parameters. The ‘LOHS’ measures the time spent by the participants in hospital (duration from the day of admission to the day of discharge) whereas ‘time to clinical improvement’ measures a time required for an upgradation of clinical status of participant specified by a predefined increase in the score on an appropriate ordinal scale. Characteristics of included studies 1o Viral negativity 2o Time to resolution of symptoms, duration of hospitalisation Mortality 1o Time to clinical improvement 2o Discharge from hospital 1o Time to clinical improvement, 2o Normalisation of inflammatory markers, improvement in oxygen saturation Inhalation, 8 MIU (0.25 mg) twice a day was given for 5 days 1o Time to clinical improvement 2o Percentage of patients discharged, duration of hospitalisation 1o Time to clinical improvement 2o Percentage of patients discharged, duration of hospitalisation 1.IFN-β1a + SOCd 2. IFN-β1b + SOCd 1o Time to clinical improvement 2o Mortality, duration of hospitalisation 1. IFN-β1a: SC, 12,000 IU/44 mcg on days 1, 3, 6 2. IFN-β1b: SC, 8 MIU on Days 1, 3, 6 1o Mortality 2o Initiation of mechanical ventilation, duration of hospitalisation SC, 44 mcg, on Days 1, 3 & 6 IV, 10 mcg daily for 6 days 1o Time to clinical improvement 2o Mortality SC, 88 mcg (24 MIU) on days 1, 3, 6 SC, 44 mcg (12 MIU) on Days 1, 3, 6 1o Primary outcome, 2o Secondary outcome ATV/r atazanavir and ritonavir combination, COVID-19 Coronavirus disease 2019, HCQ hydroxychloroquine, IFN interferon, IU International Unit, IV intravenous, LPV/r lopinavir and ritonavir combination, mcg microgram, MIU million/mega International Unit, RCT randomized controlled trial, SC subcutaneous, SOC standard of care aLPV/r[10] bLocal standard of care[16] c+ LPV/r or ATV/r + HCQ for 7–10 days [18, 19] dLPV/r + HCQ single dose[20] A total of eight randomised control trials were included in the systematic review, of which seven were included in the meta-analysis. One study [22] was excluded from the meta-analysis as IFN-β (although in different doses) was used in both of the study arms (Table 1).

Mortality

Individually, no included studies found significant impact of IFN-β on mortality in COVID-19 patients as compared to standard of care/control. Also, pooled data in this meta-analysis found no significant effect of this intervention on mortality compared with control [OR 0.59; 95 % CI 0.31–1.12]. However, the analysis results might have drawn largely by the WHO Solidarity trial with a larger sample size. The sensitivity analysis performed that excluded this study shows a significant reduction in mortality as compared to control group, OR, 0.45 [95 % CI 0.24–0.82]. The possible explanation for moderate heterogeneity among studies pooled to analyse data on mortality could be an outlying sample size, varying dosage used and varying characteristics of study population. The WHO Solidarity trial, which investigated the effects of four interventions in COVID-19 patients namely: remdesivir, hydroxychloroquine, lopinavir/ritonavir and IFN-β, found no significant effect of any of the trial drugs on mortality [23], which was the chief aim of this trial. Based on interim results, the IFN-β arm was discontinued from this trial. Another trial ‘Adaptive COVID-19 Treatment Trial 3 (ACTT-3)’ that evaluated the effect of IFN-β in combination with remdesivir versus remdesivir plus placebo, has completed its recruitment (969 participants) and results are still awaited [24]. This study could be helpful in decision making regarding use of IFN-β as a potential therapeutic agent in COVID-19. No meta-analyses were found to assess the effect of IFN-β on mortality in COVID-19 patients. Nakhlband et al. [25] conducted a meta-analysis to evaluate the effect of IFN-β, but did not analyse for mortality.

Length of Hospital Stay (LOHS)

In the present meta-analysis, IFN-β was found to reduce the LOHS but this benefit was not statistically significant as compared to that conferred by control (MD − 1.41; 95 % CI − 2.84, 0.02). In two of the included studies [10, 18] LOHS was significantly less in IFN-β arm than that in the control arm. Overall heterogeneity among included studies was found to be moderate. Sensitivity analysis revealed that exclusion of one study (Davoudi-Monfared et al. 2020 [19]) reduced the heterogeneity to 46 % with negligible change in overall LOHS. Nakhlband et al. [25] analysed the effect of IFN-β on LOHS in their meta-analysis, which included three studies, and found a significant reduction in the LOHS by IFN-β in comparison to control. Another systematic review by Sosa et al. [26] also shows a decrease in overall hospital stay following addition of IFN-β to the current standard of care. However, WHO Solidarity trial found no significant difference in LOHS between groups of COVID-19 patients treated with IFN-β compared to standard of care [21, 23]. Results of this meta-analysis may be considered in line with the findings of WHO Solidarity trial because the benefit found is only marginal and was not statistically significant.

Time to Clinical Improvement

Four studies in the literature were found that showed significantly less time to clinical improvement with IFN-β as compared to that with control [10, 17, 18, 20]. Similarly, pooled data from the included studies in this meta-analysis show significantly less (p = 0.0003) time to clinical improvement in COVID-19 patients receiving IFN-β compared to those receiving standard of care. The test for heterogeneity shows I2 value of 39 %, which is in the moderate category. One study by Darazam et al. [20, 22] further evaluated low-dose (three doses of 12 million IU) versus high-dose (three doses of 24 million IU) IFN-β1a in hospitalised patients with moderate-to-severe COVID-19. This study found no significant difference (p = 0.55) in mortality between the two study arms. Interestingly, time to clinical improvement was significantly shorter (p = 0.018) in the low-dose arm as compared to that in the high-dose arm [22]. Longer time to clinical improvement in case of high-dose IFN-β may be due to more adverse events in this arm. In the included studies, IFN-β was administered irrespective of magnitude of predicted IFN response. It is worth noting that only a subpopulation of COVID-19 patients suffers from a defective type I IFN response, while some others produce stronger response [27]. Indeed, screening patients for IFN impairment, by quantifying IFN-β levels with highly sensitive assays and/or interferon stimulated gene expression by real time-polymerase chain reaction technique could have been performed on the day of admission to determine which patients may benefit from IFN treatment. Moreover, the timing of IFN-β administration is also important as administration in the early stage of the infection may result in a favourable clinical outcome [19]. In this regard, the number of properly designed studies and those designed to investigate the early versus late effect of IFN-β in COVID-19 patients is low, and future studies are needed to further confirm the importance of IFN-β therapy in COVID-19 taking these factors into consideration.

Conclusion

This systematic review and meta-analysis found no significant benefit of IFN-β in terms of reduction in mortality and LOHS among COVID-19 patients. The possible reasons for the same could be the limited number of the eligible studies, different dosage of IFN-β and presence of confounding factors like concomitant pharmacotherapy. Moreover, due to the heterogeneity of the disease between individuals, possibly due to different factors such as genetics, age and sex, the response to anti-COVID-19 treatment may be variable. However, this study favours use of IFN-β in terms of reducing the time to clinical improvement in moderate-to-severe COVID-19 patients.
Many anti-viral agents, including interferon-β, have been investigated for the treatment of COVID-19.
There are limited data on the effect of interferon-β on outcome of COVID-19 in moderate-to-severe cases.
This systematic review and meta-analysis included all the available randomised clinical trials and evaluated the effect of interferon-β on outcome of COVID-19 in moderate-to-severe cases.
Interferon-β significantly reduced the time to clinical improvement but did not affect mortality and length of hospital stay outcomes as compared to standard of care.
  23 in total

Review 1.  Interferons alpha and beta as immune regulators--a new look.

Authors:  C A Biron
Journal:  Immunity       Date:  2001-06       Impact factor: 31.745

Review 2.  Antiviral actions of interferons.

Authors:  C E Samuel
Journal:  Clin Microbiol Rev       Date:  2001-10       Impact factor: 26.132

3.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.

Authors:  Chaolin Huang; Yeming Wang; Xingwang Li; Lili Ren; Jianping Zhao; Yi Hu; Li Zhang; Guohui Fan; Jiuyang Xu; Xiaoying Gu; Zhenshun Cheng; Ting Yu; Jiaan Xia; Yuan Wei; Wenjuan Wu; Xuelei Xie; Wen Yin; Hui Li; Min Liu; Yan Xiao; Hong Gao; Li Guo; Jungang Xie; Guangfa Wang; Rongmeng Jiang; Zhancheng Gao; Qi Jin; Jianwei Wang; Bin Cao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

4.  Triple combination of interferon beta-1b, lopinavir-ritonavir, and ribavirin in the treatment of patients admitted to hospital with COVID-19: an open-label, randomised, phase 2 trial.

Authors:  Ivan Fan-Ngai Hung; Kwok-Cheung Lung; Eugene Yuk-Keung Tso; Raymond Liu; Tom Wai-Hin Chung; Man-Yee Chu; Yuk-Yung Ng; Jenny Lo; Jacky Chan; Anthony Raymond Tam; Hoi-Ping Shum; Veronica Chan; Alan Ka-Lun Wu; Kit-Man Sin; Wai-Shing Leung; Wai-Lam Law; David Christopher Lung; Simon Sin; Pauline Yeung; Cyril Chik-Yan Yip; Ricky Ruiqi Zhang; Agnes Yim-Fong Fung; Erica Yuen-Wing Yan; Kit-Hang Leung; Jonathan Daniel Ip; Allen Wing-Ho Chu; Wan-Mui Chan; Anthony Chin-Ki Ng; Rodney Lee; Kitty Fung; Alwin Yeung; Tak-Chiu Wu; Johnny Wai-Man Chan; Wing-Wah Yan; Wai-Ming Chan; Jasper Fuk-Woo Chan; Albert Kwok-Wai Lie; Owen Tak-Yin Tsang; Vincent Chi-Chung Cheng; Tak-Lun Que; Chak-Sing Lau; Kwok-Hung Chan; Kelvin Kai-Wang To; Kwok-Yung Yuen
Journal:  Lancet       Date:  2020-05-10       Impact factor: 79.321

5.  Role of interferon therapy in severe COVID-19: the COVIFERON randomized controlled trial.

Authors:  Ilad Alavi Darazam; Shervin Shokouhi; Mohamad Amin Pourhoseingholi; Seyed Sina Naghibi Irvani; Majid Mokhtari; Minoosh Shabani; Mahdi Amirdosara; Parham Torabinavid; Maryam Golmohammadi; SayedPayam Hashemi; Arsalan Azimi; Mohammad Hossein Jafarazadeh Maivan; Omidvar Rezaei; Alireza Zali; Mohammadreza Hajiesmaeili; Hadiseh Shabanpour Dehbsneh; Akram Hoseyni Kusha; Maryam Taleb Shoushtari; Negar Khalili; Azam Soleymaninia; Latif Gachkar; Ali Khoshkar
Journal:  Sci Rep       Date:  2021-04-13       Impact factor: 4.379

6.  Repurposed Antiviral Drugs for Covid-19 - Interim WHO Solidarity Trial Results.

Authors:  Hongchao Pan; Richard Peto; Ana-Maria Henao-Restrepo; Marie-Pierre Preziosi; Vasee Sathiyamoorthy; Quarraisha Abdool Karim; Marissa M Alejandria; César Hernández García; Marie-Paule Kieny; Reza Malekzadeh; Srinivas Murthy; K Srinath Reddy; Mirta Roses Periago; Pierre Abi Hanna; Florence Ader; Abdullah M Al-Bader; Almonther Alhasawi; Emma Allum; Athari Alotaibi; Carlos A Alvarez-Moreno; Sheila Appadoo; Abdullah Asiri; Pål Aukrust; Andreas Barratt-Due; Samir Bellani; Mattia Branca; Heike B C Cappel-Porter; Nery Cerrato; Ting S Chow; Najada Como; Joe Eustace; Patricia J García; Sheela Godbole; Eduardo Gotuzzo; Laimonas Griskevicius; Rasha Hamra; Mariam Hassan; Mohamed Hassany; David Hutton; Irmansyah Irmansyah; Ligita Jancoriene; Jana Kirwan; Suresh Kumar; Peter Lennon; Gustavo Lopardo; Patrick Lydon; Nicola Magrini; Teresa Maguire; Suzana Manevska; Oriol Manuel; Sibylle McGinty; Marco T Medina; María L Mesa Rubio; Maria C Miranda-Montoya; Jeremy Nel; Estevao P Nunes; Markus Perola; Antonio Portolés; Menaldi R Rasmin; Aun Raza; Helen Rees; Paula P S Reges; Chris A Rogers; Kolawole Salami; Marina I Salvadori; Narvina Sinani; Jonathan A C Sterne; Milena Stevanovikj; Evelina Tacconelli; Kari A O Tikkinen; Sven Trelle; Hala Zaid; John-Arne Røttingen; Soumya Swaminathan
Journal:  N Engl J Med       Date:  2020-12-02       Impact factor: 91.245

7.  Effects of Interferon Beta in COVID-19 adult patients: Systematic Review.

Authors:  Juan Pablo Sosa; Maria Mercedes Ferreira Caceres; Jennifer Ross Comptis; Jorge Quiros; Fortunato S Príncipe-Meneses; Adrian Riva-Moscoso; Marie Pierre Belizaire; Freda Q Malanyaon; Kuchalambal Agadi; Syeda Sheharbano Jaffery; Juhi Sahajwani; Asma Arshia; Andrelle Senatus; Graciela Verdecia; Lordstrong Akano; Aminah Abdul Razzack; Sanna Salam; Vinay Kumar Gadamidi; Sheeba Marian
Journal:  Infect Chemother       Date:  2021-06

Review 8.  A comprehensive review on drug repositioning against coronavirus disease 2019 (COVID19).

Authors:  Maryam Rameshrad; Majid Ghafoori; Amir Hooshang Mohammadpour; Mohammad Javad Dehghan Nayeri; Hossein Hosseinzadeh
Journal:  Naunyn Schmiedebergs Arch Pharmacol       Date:  2020-05-19       Impact factor: 3.000

9.  Why Are Lopinavir and Ritonavir Effective against the Newly Emerged Coronavirus 2019? Atomistic Insights into the Inhibitory Mechanisms.

Authors:  Bodee Nutho; Panupong Mahalapbutr; Kowit Hengphasatporn; Nawanwat Chainuwong Pattaranggoon; Nattapon Simanon; Yasuteru Shigeta; Supot Hannongbua; Thanyada Rungrotmongkol
Journal:  Biochemistry       Date:  2020-04-24       Impact factor: 3.162

10.  Interferon β-1b in treatment of severe COVID-19: A randomized clinical trial.

Authors:  Hamid Rahmani; Effat Davoudi-Monfared; Anahid Nourian; Hossein Khalili; Nooshin Hajizadeh; Narjes Zarei Jalalabadi; Mohammad Reza Fazeli; Monireh Ghazaeian; Mir Saeed Yekaninejad
Journal:  Int Immunopharmacol       Date:  2020-08-24       Impact factor: 4.932

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