The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has wreaked havoc on humanity. The World Health Organization (WHO) declared the COVID-19 outbreak a pandemic on March 11, 2020.[1,2] According to current epidemiological data, the median incubation period is 6 days, and transmission can happen even before symptoms appear. Furthermore, asymptomatic cases, which account for a significant portion of infections, are likely to contribute to virus circulation.
All the positive COVID-19 cases are treated with supportive treatment, symptomatic treatment, oxygen therapy, respiratory and circulation support, and therapeutics. Warm baths and antipyretic medications such as ibuprofen and acetaminophen were used to treat severe cases of high fever as supportive treatment. Patients who are having trouble breathing should be given non-invasive mechanical ventilation (NIV). Most management strategies seek to enhance viral clearance and inhibit the cytokine storm by reducing the need for long hospital stays, mechanical ventilation, and COVID-19-related mortality. Several options, ranging from prophylactic vaccines to targeted antiviral drugs, are considered for this purpose. Anti-inflammatory drugs such as hydroxychloroquine (HCQ), dexamethasone, tocilizumab, and chloroquine (CQ) have been recommended to minimize the release/production of pro-inflammatory cytokines to reduce the cytokine storm caused by SARS-CoV-2. Remdesivir has in vitro activity against SARS-CoV-2. Other antivirals such as arbidol, oseltamivir, favipiravir, interferon beta-1a, darunavir, and cobicistat are under trials. Controversial studies are there for glucocorticoids because there was no improvement in the rate of radiographic recovery; hence, they are not recommended in mild cases. Early, low-dose, and short-term (1–2 mg/kg/d for 5–7 days) corticosteroids were linked to a faster improvement of clinical manifestations and absorption of focal lung lesions in severe COVID-19 cases. Severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS) viral loads peak 7–10 days after symptom onset; however, COVID-19 viral loads peak at the time of presentation, similarly to influenza.
Inflammatory cytokines are the first line of defense against viruses. Interferons (IFNs) are divided into three families, each of which has several subfamilies. IFN-II is the only isoform with a single isoform 33: IFN-I [α, β, ω, ε, κ]; IFN-II (γ); IFNs-III and IFN λ (λ1, λ2, λ3, λ4). IFNs are naturally occurring anti-inflammatory proteins that bind to receptors on the surface of different cells and activate the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) signaling pathway, which results in transcription of IFN-stimulated genes (ISGs) like the pro-inflammatory chemokine C-X-C Motif Chemokine Ligand 10 (CXCL10) and antiviral enzyme Ribonuclease L (RNase L). Type I and III IFNs are genetically distinct, have different receptors, elicit similar pathogen detection sensors, and activate antiviral, antiproliferative, and immunomodulatory gene expression programs. IFN-l helps to reduce harmful inflammatory responses and limits viral spread from the upper respiratory tract to the lungs by contrasting viral replication in epithelial cells at the entry point. Additionally, by stimulating adaptive immunity, it protects the mucous barrier. Finally, it protects the barrier’s integrity by reducing inflammation and its harmful effects caused by neutrophil activation. Type I IFNs (IFN-α, IFN-β, IFN-ε, IFN-κ, and IFN-ω) bind to the transcription factor type I IFN receptor (IFNAR) in a paracrine and autocrine manner in humans. Type III IFNs bind to the type III IFN receptor, which is expressed preferentially on epithelial and certain myeloid cells. Type I and III IFNs both cause ISG expression to be induced and depleted, but type I IFN signaling causes ISG expression to be induced and depleted more quickly. IFN-α and IFN-β, primarily recombinant and pegylated, have been explored to treat various disorders, including multiple sclerosis and viral hepatitis.[9,10] In contrast to antiviral activity, IFN-β is much more effective than IFN α-2 at activating the antiproliferative program, a finding that was also confirmed using the IFN α-2 variant.
As a result, a link is discovered between the administration of IFN β-1a and the improvement in the clinical course of COVID-19 disease. This finding was significant because it suggests that IFN could be a viable therapeutic option in severe COVID-19 cases. Patients admitted to hospitals with a high viral load suggest that a combination of antiviral drugs is more effective than single-drug treatments. In all clinical samples, aerosol inhalation of IFN-k plus trefoil factor 2 (TFF2) in combination with standard care is proven safe and superior to standard care alone in reducing the time to viral ribonucleic acid (RNA) negative conversion.[12,13] Thus, an increasing number of researchers are focusing on the IFN treatment in COVID-19. Interferon beta-1b, ribavirin, and lopinavir/ritonavir were safer and more effective in reducing virus shedding, lessening symptoms, and allowing patients with mild to moderate COVID-19 to be discharged than lopinavir/ritonavir alone.[14,15] However, there is limited evidence to know about the impact of the administration of IFN β-1b and standard care on the prognosis of COVID-19 in severely ill patients. This meta-analysis and systematic review currently aimed to explore the efficacy of the administration of IFN β-1b and standard care role versus only standard care as the therapeutic agent for managing COVID-19 patients who are severely ill.
Types of studies
Randomized controlled trials (RCTs), open label.
- RCTs of patients aged ≥18 years of both genders.
- SARS-CoV-2 patients confirmed the positive result of nasopharyngeal swabs using Real-Time Polymerase Chain Reaction (RT-PCR) with or without co-morbidities.
- We excluded articles with a single arm and self-comparison studies and papers with mild and moderate infection of COVID-19 subjects.
- Papers comparing the other types of interferon along with standard care versus standard care alone.
Types of interventions
- Intervention arm: IFN β-1b along with standard care that includes antiviral (lopinavir/ritonavir, ribavirin) therapy, corticosteroids, HCQ, and antibiotics.
- Control arm: The standard care of antiviral therapy (lopinavir/ritonavir, ribavirin), corticosteroids, HCQ, and antibiotics.
Types of outcome measures
Time for clinical improvement from admission to discharge with IFN β-1b:
- Mortality at the end of the study
- Need for ICU admission
- Duration of hospitalization
- Hospital admission requiring the invasive and non-invasive mechanical ventilation.
- Safety outcome of the study:
The search was performed for relevant studies which were published from January 1, 2020, to February 16, 2023, on the following databases: Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, Scopus, and Google Scholar. We searched the Clinical Trials Registry of India for ongoing studies. Manual searching was also conducted. The mesh terms “COVID-19, SARS-CoV-2, coronavirus, beta interferon, and interferon beta” were used. The search strategy is mentioned in Appendix 1. The retrieved article was imported into Zotero and converted into “ris” format for importing pooled studies into Rayyan.
Data collection and analysis
Selection of population in the included studies of this systematic review
- Patients ≥18 years of age from both genders.
- Patients with or without co-morbidities like diabetes mellitus, hypertension, coronary artery disease, and malignancy were included.
- Patient with the confirmed positive result of nasopharyngeal swabs using RT-PCR for COVID-19.
- Patients on the treatment of IFN β-1b and standard therapy, which includes antiviral, HCQ, and supportive therapy.
- Patients with known neuropsychiatric disorders, thyroid disorders, and cardiovascular diseases.
- Patient on other types of different IFN therapy like IFN β-1a, IFN α-2b, etc.
- Consumption of potentially interfering medications with lopinavir/ritonavir + HCQ, IFN β-1b, or having a history of alcoholism, or any illicit drug addiction within the past five years.
- Pregnant patients and lactating women.
Data extraction and management
All records were assessed by the reviewers (GSS, BMB, GT, and MAK) to confirm eligibility in Rayyan. The modified data extraction from Cochrane CENTRAL was used. The following details were extracted: trial ID, general information, methods, participants, interventions, and outcomes. For each intervention and comparison group, a number of participants randomized into each group, description and duration of the treatment, and timing and medium of delivery were abstracted. Similarly, for each outcome, data like relevancy of outcome, the time points, and unit of measurement were reported. Mean and standard deviations were extracted for continuous outcome variables, whereas in some studies, the outcome measures were mentioned in the median and interquartile range from which the mean and standard deviation were derived using Hozo’s method. The retrieved data were reviewed by the RSB.
Assessment of risk bias and summary findings of the included studies
The reviewers (GSS, RBS, BMB, GT, and MAK) separately examined the following domains using the risk of bias tool: Random sequence generation (selection bias), allocation concealment (selection bias), blinding of participants and personnel (performance bias), blinding of outcome assessment (detection bias), incomplete outcome data (attrition bias), selective reporting (reporting bias), and other biases are all involved in determining whether studies have a registration number. With correct judgment and explanation, the above-mentioned biases were labeled as “low,” “high,” or “unclear” in a table. The data were used to create a graph and figure depicting the risk of bias. Any differences were sorted out by discussing with reviewer RSB. The overall quality grading of the outcomes, such as the size of the effect of the treatments employed in the studies and the accessible important information on the outcomes, was also examined by extracting the appropriate data into the summary of results table using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) technique.
The protocol of this systematic review and meta-analysis was registered prospectively with PROSPERO [Registration number: CRD42021284428].
All the analysis was performed with the Review Manager version 5.4 (Cochrane Collaboration, Copenhagen, Denmark), which was used to produce forest plots with pooled estimates by importing the appropriate data. As the outcome measures were continuous, the overall effect size was calculated using mean and standard deviation values. The pooled estimates were calculated using the inverse variance approach, and both random and fixed effect models were utilized. Each outcome›s estimated mean difference (MD) and 95% confidence interval (CI) were graphically and statistically represented, along with the weight assigned by each study and the risk ratio was calculated for a dichotomous variable to know the ratio of the probability of the event to occur in the intervention group to that of the control group. Cochrane›s Q (P values) and Higgins I2 statistics, as well as ocular examination, were used to evaluate heterogeneity. The intertrial variability was represented in percentage with a P value. We used a funnel plot to assess the publication bias.
Our search from various databases yielded a total of 66 studies, out of which 36 were duplicates. This resulted in getting 30 records, of these 26 studies were excluded due to reasons: The drug used as an intervention was different, and the population included was different such as patients with MERS and articles published in foreign languages. A full-text review was performed for four articles, out of which one report was removed as the route of administration of the drug was different. A set of three studies were included in the qualitative analyses. The complete search is illustrated in Figure 1.
Characteristics of studies
Characteristics of the included studies are provided in Table 1. The included studies were all open-label randomized controlled trials with an intervention group receiving the IFN β-1b plus standard care and the control group receiving only standard care. The IFN β-1b was given subcutaneously in all three studies. The drugs included in the standard care were mainly antiviral, that is, lopinavir and ritonavir. One of the three studies has not administered HCQ to the subjects. The included participants are adults, who had a positive RT-PCR result at the time of admission, and all the patients were having severe COVID-19 and were hospitalized. The primary outcome measure for the RCTs was to monitor the time for clinical improvement. This was measured using scales such as NEW2 and WHO 7 points scale with different parameters to measure improvement status with the therapy.
The participants included in the included RCTs had co-morbidities, mainly hypertension, type-2 diabetes mellitus, and ischemic heart disease. The majority of the selected studies have finished their trial for a shorter duration, and the long-term effects of the drug are not known.
Risk of bias assessment
The risk for random sequence generation was low in all three studies. The risk for blinding was found to be high, as the included studies were an open label. Selective reporting of primary outcomes measures was found to be low in three studies. The trial registration number was confirmed for two of the included trials, and it remains unclear for one study. The complete risk assessment of all articles is depicted as a graph [Figure 2 and Table 2].
Clinical outcome measures
Time of clinical improvement
Analysis was performed for all three studies (n = 167) with similar interventional drugs, that is, IFN β-1b along with standard care which includes the antivirals like lopinavir, ritonavir, ribavirin, and the symptomatic treatment to that of only standard care provided to the control group. The COVID-19 patient who was severely ill and treated with IFN β-1b showed rapid clinical response, that is, negative RT-PCR or improvement of any two parameters in the seven-point scale or six-point scale when compared to the only standard care group (MD: -3.28 days; 95% CI: -5.65, -0.91; P value = 0.007). The intertrial variability among the included studies was found to be significantly high (χ2 = 62.56; I2 = 97%; p=<0.001) [Figure 3].
Duration of hospital stay
The analysis was conducted to know the duration of hospital stays, that is, the number of days the COVID-19-infected patients were admitted to the hospital. IFN β-1b significantly reduced the duration of the hospital stay when compared to standard care (MD: -2.43 days; 95% CI: -4.45, -0.30; P value = 0.03). On accounting for the degree of intertrial variance, it was found to be high with a statistically significant P value < 0.001 (χ2 = 83.62; I2 = 98%) [Figure 4].
Two included studies have measured the number of patients admitted to ICU, who had experienced severe COVID-19 infection. The results of the analysis stated that the number of admissions to ICU was statistically less when treated with IFN β-1b (RR: 0.71; 95% CI: 0.52, 0.97; P value = 0.03). Low heterogeneity was observed among the trials, but the results are statistically insignificant P value of 0.41 (χ2 = 0.67; I2 = 0%) [Figure 5].
Hospital admission with invasive mechanical ventilation
The studies have monitored the number of patients needing mechanical ventilation during the hospital stay as most patients included in studies have oxygen saturation (SpO2) <95%. The analysis of the two studies which were included depicts that there is no statistically significant difference between both the groups. The risk for invasive mechanical ventilation was not reduced when treated with IFN β-1b along with standard care (RR: 0.82; 95% CI: 0.39, 1.74; P value = 0.60). The intertrial variability was found to be significantly low (χ2 = 0.57; I2 = 0%; P = 0.45) for the included studies [Figure 6].
Hospital admission with Non-invasive mechanical ventilation
As mentioned above, the studies have also measured the need for NIV between the groups. The analysis from the included studies revealed that there was no statistically significant difference between the groups (RR: 1.27; 95% CI: 0.51, 3.20; P value = 0.61). Low heterogeneity was observed among the trials but with a statistically insignificant P value of 0.57 (χ2 = 0.33; I2 = 0%) [Figure 7].
All the included studies have noted several mortalities that occurred in both groups during the study period. The analysis results stated that there is a significant difference between the groups (RR: 0.41; 95% CI: 0.15, 1.14; P value = 0.09). Low heterogeneity was observed between the trials, and the results were statistically insignificant (χ2 = 0.30; I2 = 0% P value = 0.59) [Figure 8].
The safety outcomes were analyzed in this meta-analysis to assess if the common adverse drug reactions (ADRs) reported in the included studies are significantly different between both the groups. The ADRs reported in the studies are nausea and vomiting (RR: 1.03; 95% CI: 0.65, 1.62; P value = 0.90), diarrhea (RR: 0.95; 95% CI: 0.63, 1.44; P value = 0.81), injection site reaction (RR: 1.50; 95% CI: 0.26, 8.75; P value = 0.65), flu-like syndrome (RR: 1.13; 95% CI: 0.72, 1.80; P value = 0.59), increased aminotransferase (RR: 0.73; 95% CI: 0.49, 1.08; P value = 0.64), hyperalbuminemia (RR: 0.71; 95% CI: 0.20, 2.53; P value = 0.11), acute respiratory distress syndrome (RR: 0.63; 95% CI: 0.33, 1.19; P value = 0.15), acute kidney injury (RR: 0.70; 95% CI: 0.29, 1.68; P value = 0.42), shock (RR: 0.40; 95% CI: 0.08, 1.98; P value = 0.26), and increased creatinine (RR: 0.70; 95% CI: 0.29, 1.69; P value = 0.43). Our results showed that there was no statistically significant difference found with the severity of ADRs experienced between both the groups. The intertrial variability was found to be insignificantly low for most of the parameters except for flu-like syndrome [Figure S1].
Assessment of Reporting bias
We investigated the publication bias by using the funnel plot for all the primary outcome measures for included studies in the analysis. We found that the funnel plot was symmetrical for all the primary outcome measures [Figures S2-S7].
The outcome of GRADE approach assessment
Quality grading for the clinical outcomes was performed using the GRADE approach which is depicted in Table 3. The certainty of the extracted evidence was categorized into very low to high grades for six outcomes: time of clinical improvement, duration of hospital stay, mortality, hospital admission with invasive mechanical ventilation, hospital admission with NIV, and number of ICU admission. It was found that for all the six outcomes, the certainty of the evidence was found to be moderate. Thus, further, there is a need to have a substantial number of RCTs to be conducted to achieve the certainty of evidence to be strong.
Since December 2019, the world has been shrouded by the COVID-19 newborn idiopathic coronavirus and an increasing number of infected patients. Since then, antiviral and immunomodulatory drugs have been tested in clinical trials to see if they can prevent the coronavirus from spreading. To date, no certified antiviral drugs with proven efficacy for COVID-19 treatment have been identified. Following that, it appears critical to collect and summarize a variety of evidence to achieve an effective COVID-19 treatment.
Type I IFNs are antiviral proteins that aim and prevent the replication and progression of a variety of viral pathogens while also promoting an immune response to clear virus infection. Hepatitis B and C, autoimmune disorders, SARS and MERS, and certain cancers are all treated with type I IFNs. This prompted the start of COVID-19 treatment with IFN. According to the National Health Commission of the People’s Republic of China, the drug of choice for COVID-19 treatment is a combination of IFN and an antiviral. A recent study carried out in Iran proposed the need for IFN therapy in severe COVID-19. IFNs cause the expression of multiple genes in the host cells to shift into an antiviral state, preventing virus propagation and secondary replication. Although there are three major forms of IFNs, type I, II, and III, type I IFN plays a major role in the antiviral response and affects the adaptive immune responses. Given the striking similarities between COVID-19 and the SARS and MERS in terms of changes in total neutrophil and lymphocyte counts in patients, it is widely assumed that SARS-CoV-2 may also inhibit type I IFNs in the early stages of COVID-19 disease. Similarly, we discovered a significant relationship between the administration of IFN β-1a and the amelioration of the clinical course of COVID-19 disease. This finding was particularly significant as it suggests that IFN could be a powerful therapeutic option in severe COVID-19 cases. Because the development of a newer antiviral takes years before it is approved for clinical use, specific high active antivirals are required for any novel emerging infectious disease. As a result, in the event of a pandemic, the most feasible approach is to test existing broad-spectrum antiviral drugs that have previously been used to treat other viral infections. Antiviral agents should be started as soon as possible after the onset of symptoms to control viral replication and prevent tissue viral invasion. Antiviral efficacy decreased significantly after the cytokine release phase was established in COVID-19.
As of our knowledge, no meta-analysis states that the standard treatment when combined with IFNs increases the treatment efficacy and reduces hospital stay. Thus, we think it is a necessity to carry out this meta-analysis. In the current study, we found that IFN with antivirals (lopinavir/ritonavir, ribavirin) and HCQ effectively suppresses SARS-CoV-2 by reducing hospitalization time, viral-load clearance, and time for clinical improvement when compared to the standard care (lopinavir/ritonavir, ribavirin, and HCQ).
The result of our meta-analysis depicts that the patients administered with IFN along with standard care had a reduced need for ICU admission compared to the standard care group. The IFN β-1b could not prevent invasive mechanical ventilation as there is no significant difference between the groups. The number of patients that needed NIV during the hospital stay was similar in both groups. Although two of the three included studies have reported mortality in both groups, our analysis results have statistically shown no difference in the number of deaths between the groups. The systematic review meta-analysis conducted by Kumar S et al. included the studies which used interferon β-1b and β-1a in the intervention arm, whereas in this review we have included the studies conducted with interferon β-1b alone. The review conducted by Kumar S et al. concluded that there was a significant reduction with respect to clinical improvement, and all other outcome parameters did not show any significant improvement between the intervention and the control arm. In this review, the patients who received interferon β-1b in the intervention arm have shown significant improvement in reducing the number of hospital stays, increase in clinical response, and decrease in ICU admission. Our meta-analysis also includes safety concerns. The adverse outcomes reported by each study were included in the analysis, and it was observed that there is no statistically significant difference seen between the intervention and the control group.
As for limitations, all the included studies were open label. Hence, the subjects and investigators were aware of the treatment provided which could lead to performance bias. Though the route of administration was the same, the dose and dosing interval of IFN β-1b varied among the included studies. A substantial group of participants recruited in the studies had co-morbid conditions such as diabetes, hypertension, cardiovascular disease, and malignancy. This may increase the risk of interaction with other concomitant medications which might have an antagonistic or synergistic action with IFN β-1b or standard care treatment provided to COVID-19 patients. The concomitant medications might have an impact on the estimate of the IFN β-1b effect on COVID-19. Future RCTs must be performed to overcome the limitations mentioned in this review.
Our results demonstrate that administration of interferon beta-1b along with the standard care, that is, antiviral such as lopinavir/ritonavir, ribavirin, and HCQ had reduced the need for ICU admission and had better efficacy in shortening the duration of virus shedding, reducing the cytokine response, and reducing the symptoms of COVID-19. This study also gives insight to clinicians and to have informed them about the efficacy and safety of interferon beta-1b and a reasonable therapeutic option that can be used in severely ill COVID-19 patients for a better prognosis.
Greeshma Sai Sree Nayudu (GSS), Binit Mamkoottathil Benny (BMB), Grace Thomas (GT), Maria Adil Khan (MAK), and Roopa Satyanarayan Basutkar (RSB) were involved in the conception of the study from the inception of the protocol development and throughout. GSS, BMB, and GT conducted the literature search, and the relevant information was also extracted. Risk assessment was performed by MAK and GSS. Any discrepancies were sorted, discussed, and resolved by RSB. GSS had entered the data into Review Manager 5.3 and contributed to the analysis. All the tables and figures were prepared by GSS, GT, and BMB. The first and subsequent drafts of the manuscript were prepared by GSS, BMB, GT, and MAK. RSB reviewed and corrected all the drafts of the manuscript. The final version of the manuscript was approved by all authors.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
The authors thank JSS College of Pharmacy, JSS Academy of Higher Education and Research, Rocklands, Ooty, The Nilgiris, Tamil Nadu, India, for the support, technical assistance, and resources provided throughout the study.
1. Chuan A, Liu Y, Shao Y, Yang CZ, Xu J, Yang B. Hydroxychloroquine and Interferons for the prophylaxis and early treatment of COVID-19-current clinical advances. J. clin. cell. immunol 2020;11:596. doi:10.35248/2155-9899.20.11:596.
2. Basutkar RS, Sagadevan S, Sri Hari O, Sirajudeen MJ, Ramalingam G, Gobinath P, et al. A study on the assessment of impact of COVID-19 pandemic on depression:An observational study among the pregnant women. J Obstet Gynecol India 2021;71:28–35.
3. Galluccio F, Ergonenc T, Garcia Martos A, Allam AE, Pérez-Herrero M, Aguilar R, et al. Treatment algorithm for COVID-19:A multidisciplinary point of view. Clin Rheumatol 2020;39:2077–84.
4. Haji Abdolvahab M, Moradi-kalbolandi S, Zarei M, Bose D, Majidzadeh-A K, Farahmand L. Potential role of interferons in treating COVID-19 patients. Int Immunopharmacol 2021;90:107171. doi:10.1016/j.intimp.2020.107171.
5. Bakadia BM, He F, Souho T, Lamboni L, Ullah MW, Boni BO, et al. Prevention and treatment of COVID-19:Focus on interferons, chloroquine/hydroxychloroquine, azithromycin, and vaccine. Biomed Pharmacother 2021;133:111008.
6. Peng F, Tu L, Yang Y, Hu P, Wang R, Hu Q, et al. Management and treatment of COVID-19:The Chinese experience. Can J Cardiol 2020;36:915–30.
7. Alavi Darazam I, Shokouhi S, Pourhoseingholi MA, Naghibi Irvani SS, Mokhtari M, Shabani M, et al. Role of interferon therapy in severe COVID-19:The COVIFERON randomized controlled trial. Sci Rep 2021;11:8059.
8. Gallo CG, Fiorino S, Posabella G, Antonacci D, Tropeano A, Pausini E, et al. COVID-19:Role of the Interferons. Preprints 2020 2020080018.
9. Park A, Iwasaki A. Type I and Type III interferons –induction, signaling, evasion, and application to combat COVID-19. Cell Host Microbe 2020;27:870–78.
10. Palermo E, di Carlo D, Sgarbanti M, Hiscott J. Type i interferons in COVID-19 pathogenesis. Biology 2021;10:829–46.
11. Shalhoub S. Interferon beta-1b for COVID-19. Lancet 2020;395:1670–1.
12. Fu W, Liu Y, Liu L, Hu H, Cheng X, Liu P, et al. An open-label, randomized trial of the combination of IFN-k plus TFF2 with standard care in the treatment of patients with moderate COVID-19. EClinicalMedicine 2020;27:100547.
13. Jean SS, Lee PI, Hsueh PR. Treatment options for COVID-19:The reality and challenges. J Microbiol Immunol Infect 2020;53:436–43.
14. Hung IFN, Lung KC, Tso EYK, Liu R, Chung TW, Chu MY, et al. 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. Lancet 2020;395:1695–704.
15. Rahmani H, Davoudi-Monfared E, Nourian A, Khalili H, Hajizadeh N, Jalalabadi NZ, et al. Interferon β-1b in treatment of severe COVID-19:A randomized clinical trial. Int Immunopharmacol 2020;88:106903. doi:10.1016/j.intimp.2020.106903.
16. Hozo SP, Djulbegovic B, Hozo I. Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol 2005;5:1–10.
17. Kumar S, Saurabh MK, Narasimha VL, Maharshi V. Efficacy of Interferon-β in moderate-to-severe hospitalised cases of COVID-19:A systematic review and meta-analysis. Clin Drug Investig 2021;41:1037–46.