Additional outcomes
Incidence of elevation in liver enzymes, infusion-related reaction,
neutropenia, and bacteremia.
Search methods for identification of
studies
Information sources:
The following databases have been checked from the first of July 2020
and continued through August to identify relevant studies:
ClinicalTrial.gov, ProQuest, PubMed, Embase, Cochrane, Google Scholar,
Science direct, Chinese Clinical Trial Registry (ChiCTR), and medRxiv.
The following search terms were used: ”actemra”, ”tocilizumab”, ”SARS”
and ”COVID.” In addition, a deep manual search through checking
references in bibliography of original articles and relevant reviews was
performed.
Study selection:
Studies were selected based on PRISMA flow diagram (Fig. 1 ).
Two authors (HKE and MAE) independently selected potentially eligible
studies from screened ones based on the title and/or abstract. The full
text has been presented in order to review the articles screened for
inclusion criteria. The reasons for excluded studies were discussed and
any disagreements were resolved through discussion. A third author (MS)
revised the process of the study selection and eligibility assessment.
Data collection and
analysis:
Data was extracted using a predefined extraction form. The form
included:
Study characteristics: title, authors, year of publication, country, and
journal name.
Study design: type of the study design, hospital name, time of
interventions, time of follow-up, and other settings
Population: age, sex, baseline clinical factors, disease severity
definition, inflammation status, inclusion and exclusion criteria, and
the disease onset
Intervention: Tocilizumab dose, route of administration, and duration.
Comparator: Any other treatment or care that was given to the patients
Outcomes: All outcomes either efficacy or safety-related were extracted
extensively including numbers or data presented with graphs that were
transformed with a specific software; Get Data Graph Digitizer 2.26
Assessment of risk of bias in included
studies:
The methodological quality of selected cohort studies were assessed
based on the basis of ” risk of bias in non-randomized studies of
interventions” (ROBINS-I) (Sterne et al., 2016); a tool provides a more
comprehensive framework for identifying potential sources of bias
(Losilla, Oliveras, Marin-Garcia, & Vives, 2018). The following points
were scored as low, moderate, serious, critical or no information (where
’low’ indicated that the study was less risk to bias and thus best
quality), and were reported in a ”Risk of bias figure”: bias due to
confounding, bias in selection of participants into the study, bias in
classification of interventions, bias due to deviations from intended
interventions, bias due to missing data, bias in measurement of
outcomes, and bias in selection of the reported result.
A consensus criteria in the present meta-analysis for bias judgment
included that a study was judged at low risk of bias if all key domains
were judged at low risk of bias, a study was judged at high risk of bias
if two or more key domains were judged at high risk of bias, otherwise
the study was judged at unclear risk of bias.
Studies of low quality were not excluded, instead they were involved in
data synthesis after performing sensitivity analysis.
Synthesis of the quantitative
results
Measures of treatment effect: risk ratios (RR) with 95%confidence
intervals (CI) was used to analyze dichotomous data. None of our
included studies reported continuous data.
Data synthesis: The overall treatment effect was estimated by the pooled
RR with 95% CI by RevMan version 5.4 using a fixed-effect model
(Mantel-Haenszel). A random effects model was used in cases of
significant heterogeneity.
Assessment of heterogeneity: Chi-square test of heterogeneity and the
I2 statistic of heterogeneity were used to assess
effects heterogeneity. For Chi-square test, the data study findings were
considered to be heterogeneous if P -value was ≤ 0.05. When a
significant heterogeneity occurred, the differences were explained as
they related to types of participants and study design.
Sensitivity analysis: Sensitivity analysis was conducted for only those
cohort studies assessed as having a low overall risk of bias based on
our consensus criteria in key domains.
Publication bias: The publication bias was assessed by using funnel
plots when there were more than 10 studies reporting the same effect
measure of an outcome.