Evaluation of the Current Therapeutic Approaches for COVID-19: A Systematic Review and a Meta-analysis

Background: Limited data on the efficacy and safety of currently applied COVID-19 therapeutics and their impact on COVID-19 outcomes have raised additional concern. Objective and Methods: To estimate the efficacy and safety of COVID-19 therapeutics, we performed meta-analyses of the studies reporting clinical features and treatments of COVID-19 published from January 21 to September 6, 2020. Results: We included 136 studies that involved 102,345 COVID-19 patients. The most prevalent treatments were antibiotics (proportion: 0.59, 95% CI: [0.51, 0.67]) and antivirals (proportion: 0.52, 95% CI: [0.44, 0.60]). The combination of lopinavir/ritonavir and Arbidol was the most effective in treating COVID-19 (standardized mean difference (SMD) = 0.68, 95% CI: [0.15, 1.21]). The use of corticosteroids was associated with a small clinical improvement (SMD = −0.40, 95% CI: [−0.85, −0.23]), but with a higher risk of disease progression and death (mortality: RR = 9.26, 95% CI: [4.81, 17.80]; hospitalization length: RR = 1.54, 95% CI: [1.39, 1.72]; severe adverse events: RR = 2.65, 95% CI: [2.09, 3.37]). The use of hydroxychloroquine was associated with a higher risk of death (RR = 1.68, 95% CI: [1.18, 2.38]). The combination of lopinavir/ritonavir, ribavirin, and interferon-β (RR = 0.34, 95% CI: [0.22, 0.54]); hydroxychloroquine (RR = 0.58, 95% CI: [0.39, 0.58]); and lopinavir/ritonavir (RR = 0.72, 95% CI: [0.56, 0.91]) was associated with reduced hospitalization length. Hydrocortisone (RR = 0.05, 95% CI: [0.03, 0.10]) and remdesivir (RR = 0.74, 95% CI: [0.62, 0.90]) were associated with lower incidence of severe adverse events. Dexamethasone was not significant in reducing disease progression (RR = 0.45, 95% CI: [0.16, 1.25]) and mortality (RR = 0.90, 95% CI: [0.70, 1.16]). The estimated combination of corticosteroids with antivirals was associated with a better clinical improvement than antivirals alone (SMD = −1.09, 95% CI: [−1.64, −0.53]). Conclusion: Antivirals are safe and effective in COVID-19 treatment. Remdesivir cannot significantly reduce COVID-19 mortality and hospitalization length, while it is associated with a lower incidence of severe adverse events. Corticosteroids could increase COVID-19 severity, but it could be beneficial when combined with antivirals. Our data are potentially valuable for the clinical treatment and management of COVID-19 patients.


Rationale
3 Describe the rationale for the review in the context of what is already known. 3

Objectives 4
Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS).

Protocol and registration 5
Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.
-Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.

3-5
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

3-5
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated. 4 Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).

4
Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

3-5
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.
3-5 4 Section/topic # Checklist item Reported on page # Risk of bias in individual studies 12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.

5
Summary measures 13 State the principal summary measures (e.g., risk ratio, difference in means).

4-5
Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I 2 ) for each meta-analysis.

4-5
Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).

5
Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.

Study selection 17
Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.

5
Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.

5
Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12).

6-7
Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.

6-7
Synthesis of results 21 Present results of each meta-analysis done, including confidence intervals and measures of consistency.

6-7
Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15). 5

Summary of evidence 24
Summarize the main findings including the strength of evidence for each main outcome, consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).