According to the World Health Organization (WHO), the COVID-19 pandemic has affected about 536 million people, resulting in more than six million deaths (1). Even though almost 80% of people infected with COVID-19 have had mild to moderate diseases, an important task is to treat and prevent developing severe and critical conditions (2, 3). Although currently, there are several effective vaccines and targeted antiviral drugs against SARS-COV-2 in the world, such as Molnupiravir and Paxlovid (4), interferons (IFN) have repeatedly attracted the attention of virologists.

Interferons are the most conservative and evolved system of combating viral infection, which is more than 400 million years old (5). Due to their classification, interferons are typically divided into type I, II, and III IFNs. In turn, type I IFNs include IFN-α, IFN-β, IFN-ω, IFN-κ, and IFN-τ (6). Type I IFNs manifest both autocrine and paracrine. These interferons trigger the JAK/STAT pathway to activate diverse genes called interferon-stimulated genes (ISGs). These ISGs work together to stop the viral life cycle at different stages (7). Type I IFNs reduce SARS-CoV-2 replication in Vero E6 cells in vitro assays, viral antigen expression, viral load reduction, and plaque reduction (8). In addition, recombinant human interferon-α1b suppresses SARS-CoV-2 more effectively than IFN-α2b in vitro (9). IFN-α can be in combination with drugs influencing viral RNA transcription, protein synthesis, and processing to create synergistic consolidations that may be good targets for future preclinical and clinical development to resist emerging and re-emerging viral infections (10).

Many viruses, including SARS-CoV-2, have developed various mechanisms to escape the antiviral function of IFN-I (11). About 10 SARS-CoV-2 proteins were identified as antivirals against IFN (12, 13). SARS-CoV-2 may avert IFN production through mechanisms such as getting away from recognition by pattern recognition receptors, interfering with retinoic acid-inducible gene I or toll-like receptor signaling, and inhibiting phosphorylation of interferon regulatory factor 3 and its activation. Non-structural protein 16 (NSP16) suppresses mRNA splicing, NSP1 leads to total inhibition of mRNA translation by binding to 18S ribosomal RNA at the mRNA entry channel, and NSP8 and NSP9 disrupt protein trafficking across the membrane (14). All these mechanisms lead to a decrease in the production of type I IFN by the affected cell. Even the IFN, which, despite these obstacles, is synthesized and leaves the cell, cannot bind to its receptors. The ORF3a protein blocks the signal that finally enters the target cell and is blocked at the level of formation of transcription factors IRF3, IRF7 or STAT1 (15).

Some other studies have also shown that low levels of type I and III IFNs are partly responsible for the peculiar and inappropriate inflammatory response observed in patients with COVID-19 (16). Different studies have detected solid grounds which advocate the use of type I IFN in combination with other antivirals to achieve positive results in COVID-19 patients. Still, many of them are limited by the number of patients receiving interferon (17). Separate clinical trials have found different outcomes for IFN treatment in COVID-19 (18). There are several meta-analyses on the efficacy of IFN-β (19, 20), but there are no such data on IFN-α that has a wide range of antiviral properties and is used as a first-line drug in the treatment of various viral diseases. Since we need more information about possible treatments for Covid-19, and there is not enough data on the potential of IFN -α against Covid-19, this meta-analysis allows us to understand the effectiveness of this line of therapy.

This meta-analysis aims to evaluate the effects of IFN-α treatment in moderate to severe COVID-19 cases concerning mortality, duration of hospital stay, and a range of other results to help guide the decision to choose this drug as a therapeutic option for this disease treatment.

We found no published meta-analysis evaluating the effectiveness of IFN-α in hospitalized patients with COVID-19. Instead, several meta-analyses assessed the efficacy of the administration of IFN-β. For instance, Kumar S. et al. (2021) (20) conducted a meta-analysis of IFN-β to determine its effect on moderate-to-severe COVID-19 patients. Seven randomized controlled trials (RCTs) were permitted to perform a meta-analysis. The overall effect estimation (OR 0.6; 95% CI 0.9-1.1) determined an insignificant difference between the effect of IFN-β and the control on mortality and length of hospital stay. However, the overall effect estimation (hazard ratio [HR] 1.95; 95% CI 1.36-2.79) was noted for the strong effect of IFN-β on the reduction in time required for clinical improvement in moderate-to-severe COVID-19 patients. In another paper, Chen W. et al. (2022) (19) systematic review and meta-analysis of RCTs were dedicated to investigating the efficacy of IFN-β-containing regimens in treating patients with COVID-19. Eight RCTs were included. A nonsignificant difference in the 28-day all-cause mortality rate was noted between the study and control groups (OR, 0.7; 95% CI, 0.4–1.2; I² = 51%). The study group was admitted to a lower-rate ICU than the control groups (OR 0.6, 95% CI 0.4–0.9; I² = 0%). Subsequently, IFN-β was not connected with an increased risk of any AE or serious AE when compared with the control group. Therefore, IFN-β does not contribute to an increased survival advantage in hospitalized patients with COVID-19 but may assist in reducing the risk of ICU admission. Moreover, IFN-β is a safe agent that can be used in COVID-19 treatment. The most famous study, Solidarity (33), also did not demonstrate the effectiveness of adding IFN-β to therapy. As for the efficacy of IFN-ω, there are currently no meta-analyses and systematic reviews using of this type of interferon in the literature.

The only available systematic reviews of the effectiveness of IFN-α therapy were conducted by Nakhlband et al. (34) and Lu et al. (35). The first group of researchers revealed that the time of viral clearance and polymerase chain reaction negative (days) in most studies were reduced in the IFN-α + standard care group. The mean days of virus clearance in the IFN-α group and the standard group were 27.3 and 32.43. Similarly, the average number of days of hospitalization was also lower in the IFN‐α group (18.55 vs. 24.36). Most of the studies have administered the drug by inhalation.

A comprehensive review of clinical studies in the literature before December 1^st, 2021 (35), was carried out to find out the current applications of IFN-α. This analysis included facts on the route of administration, the number of patients who received the treatment, the severity at the treatment initiation, age range, the period from the onset of symptoms to treatment, dose, frequency, and duration, as well as safety and efficacy. No evidence was found as opposed to the safe IFN-α treatment for COVID-19. The authors showed that early intervention, either within five days from the initial symptoms or at hospital admission, grants better clinical outcomes, whereas late intervention may cause prolonged hospitalization. Inconsistency in interpretations about IFN‐α responses in patients with coronavirus disease may be attributed to different characteristics in determining moderate, severe, and critical forms of COVID‐19.

Our meta-analysis did not demonstrate the positive effects of IFN-α administration during COVID-19 on such endpoints as mortality, length of hospital stay and nucleic acid negative conversion. The potential explanation could be the low number of eligible studies, different dosing of IFN-α, and the presence of confounding factors, such as concomitant pharmacotherapy. Additionally, due to the heterogeneity of the disease among individuals, probably owing to different factors, such as genetics, age, and gender, the response to anti-COVID-19 treatment may be variable. However, this study prioritizes the use of IFN-α, considering an increase in the number of patients discharged from the hospital.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

MB and IK contributed to the methodology. KL contributed to the software. OM contributed to validation. MB and NK contributed the formal analysis. NK - data curation; AK – writing of original draft preparation; AK and VO - writing—review and editing; AK - project administration. All authors have read and agreed to the published version of the manuscript. All authors contributed to the article and approved the submitted version.