Study Design
This is a protocol to enable a transparent, reproducible and reliable systematic review and meta-analysis on the prevalence of hepatitis C infections in Nigeria.It focuses on observational studies that report different test methods including rapid diagnostic tests, enzyme immunoassays, and PCR methods for detection of hepatitis C infections. There is no restriction on time frame for including studies.
Study characteristics:
Inclusion criteria are
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observational studies such as cross-sectional studies, case-control studies, cohort studies, and historical cohort studies
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studies must report the prevalence of hepatitis C virus infection in Nigeria
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studies that are published or retrievable in the English language and are available in electronic databases.
Exclusion criteria will be
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narrative reviews, experimental and interventional studies;
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letters to editors, reviews, commentaries, and editorials;
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and duplicates of the same studies.
This review will be reported in line with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2015 Statement).
PICOS: In this study, participants are residents in Nigeria who are infected with hepatitis C virus. There is neither intervention nor a comparable group. The measurable outcome is the pooled prevalence of hepatitis C virus infection in Nigeria. Subgroups are children, adults, persons living with HIV/AIDS, people in prisons, blood donors, sex workers, sickle cell patients, pregnant women, and co-infection with HBV in Nigeria and multiply transfused people. The subgroups are categorical. Moderators will include the type of testing methods: rapid diagnostic test, enzyme immunoassay, and PCR methods.
Information sources
The search will employ sensitive topic-based strategies designed for each database. Nine databases will be searched: PubMed, CINAHL, Embase, Web of Science, Google Scholar, AJOL, Cochrane library, ResearchGate, and Scopus will be included. Only observational studies retrievable in the English language will be included.
Search strategy
The search strategy will include MeSH terms, text words, and entry terms. The search strategies to be used in various databases are shown in Table 1.
Table 1
S/No
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Database
|
Search strategy
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1
|
PubMed
|
(((Hepaciviruses OR Hepatitis C-Like Viruses OR Hepatitis C Like Viruses OR Hepatitis C-Like Virus OR Hepatitis C virus*) OR "Hepacivirus"[Mesh]) AND ((Federal Republic of Nigeria OR Nigeria) OR "Nigeria"[Mesh])
|
2
|
AJOL
|
(Hepaciviruses OR Hepatitis C-Like Viruses OR Hepatitis C Like Viruses OR Hepatitis C-Like Virus OR Hepatitis C virus*) OR "Hepacivirus") AND ((Federal Republic of Nigeria OR Nigeria) OR "Nigeria")
|
3
|
Google Scholar
|
(((Hepaciviruses OR Hepatitis C-Like Viruses OR Hepatitis C Like Viruses OR Hepatitis C-Like Virus OR Hepatitis C virus*) OR "Hepacivirus") AND ((Federal Republic of Nigeria OR Nigeria) OR "Nigeria")
|
4
|
Cochrane library
|
Hepaciviruses OR Hepatitis C-Like Viruses OR Hepatitis C Like Viruses OR Hepatitis C-Like Virus OR Hepatitis C virus* OR "Hepacivirus" AND Federal Republic of Nigeria OR Nigeria OR "Nigeria"
|
5
|
Embase
|
(Hepaciviruses OR Hepatitis C-Like Viruses OR Hepatitis C Like Viruses OR Hepatitis C virus* OR Hepacivirus [Mesh]) AND (Federal Republic of Nigeria OR Nigeria [Mesh])
|
6
|
CINAHL
|
(((Hepaciviruses OR Hepatitis C-Like Viruses OR Hepatitis C Like Viruses OR Hepatitis C-Like Virus OR Hepatitis C virus*) OR "Hepacivirus"[Mesh]) AND ((Federal Republic of Nigeria OR Nigeria) OR "Nigeria"[Mesh])
|
7
|
Web of Science
|
Hepaciviruses OR Hepatitis C-Like Viruses OR Hepatitis C Like Viruses OR Hepatitis C virus* OR Hepacivirus [Mesh]) AND (Federal Republic of Nigeria OR Nigeria [Mesh])
|
8
|
Research Gate
|
(((Hepaciviruses OR Hepatitis C-Like Viruses OR Hepatitis C Like Viruses OR Hepatitis C-Like Virus OR Hepatitis C virus*) OR "Hepacivirus"[Mesh]) AND ((Federal Republic of Nigeria OR Nigeria) OR "Nigeria"[Mesh])
|
9.
|
Scopus
|
(Hepaciviruses OR Hepatitis C-Like Viruses OR Hepatitis C Like Viruses OR Hepatitis C virus* OR Hepacivirus [Mesh]) AND (Federal Republic of Nigeria OR Nigeria [Mesh])
|
Data Extraction and Management
a. Data Extraction:
Studies will be searched using the search strategy in Table 1. Studies will be screened and selected in the DistillerSR using the following levels:
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level 1 is based on study design: only observational studies will be included; other study designs will be excluded.
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level 2: studies will be screened by titles and abstracts using entry terms, keywords, and meSh terms.
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level 3: studies will be screened by full-text reading using the same strategy.
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level 4: snowballing of literature from included studies.
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level 5: screening of outcomes: both primary and secondary outcomes will be identified at this level.
Seventeen reviewers are involved in this study. A pair of reviewers will independently screen studies in the DistillerSR. Conflicts will be resolved by a third independent reviewer. The review will be blinded.
b. Selection process:
Screened studies will be selected based on pre-defined study characteristics, primary and secondary outcomes. Authors of studies with missing data will be contacted via phone and email. Selected studies will be assessed for risk of bias in the Distiller SR.
c. Data collection process:
De-duplication of the studies and extraction of data items into predefined forms will be done in the DistillerSR and exported into Microsoft Excel. Also, Prisma flow chart will be created in the DistillerSR. The following data items will be extracted from selected studies:
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First author's surname and year of publication.
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prevalence of hepatitis C virus infection in Nigeria.
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sample size.
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method of testing (ELISA, RDT, and PCR).
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and sub-populations: blood donor, prisoner, pregnant women, etc of the tested subjects.
Data in Excel format will be imported to the CMA Software for meta-analysis.
Data items (Measurable outcomes):
Data items to be extracted include the following: prevalence of hepatitis C virus infection in Nigeria reported as the number of cases in sample size or prevalence or incidence which is convertible to prevalence. Data for subgroup analysis will include prevalence in children, adults, persons living with HIV/AIDS, people in prisons, blood donors, sex workers, sickle cell patients, pregnant women, multiply transfused persons; and also, co-infection with HBV in Nigeria. Hence, the measurable outcome is the proportion of people with hepatitis C virus infection in Nigeria and among different sub-populations and its effect size is the prevalence.
Risk of bias
The risk of bias in included studies will be accessed for the individual studies using the National Institute of Health (NIH) Quality assessment tool for observational cohort and cross-sectional studies (22). This will be cross-checked with the Cochrane tool of risk of bias assessment for the strength of the body of evidence; i.e. using specific relevant items from this tool to assess the strength of the body of evidence.
The following areas shall be assessed and any study with extreme bias will be excluded following a consensus decision.
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Method of testing/reporting will be assessed at the outcome level.
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Reporting of study: whether prevalence with confidence interval or number of positive cases per sample size is reported at the outcome level
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Heterogeneity will be assessed at the study level
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Publication bias will be assessed at the study level.
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Sensitivity testing will be performed at the study level using the include/exclude function in the CMA Software.
Data synthesis
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Studies that passed the methodological quality assessment using the NIH quality assessment tool will be extracted. The results will be presented in tabular format in addition to a narrative synthesis.
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The following shall be included in the meta-analysis;
i. The reported prevalence of hepatitis C virus infection and sample size by individual studies and subpopulations. Effect size is the prevalence. This variable must be present for a study to be included. It is the primary measurable outcome.
ii. A subpopulation of study subjects as categorical data and different test methods will be used as moderators.
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Eligible studies will be quantitatively analyzed using the CMA Software Version 3 (BioStat, USA). For each reported prevalence of hepatitis C virus infection, standard error, and variance for each specific eligible study will be calculated by the CMA software. Subgroup analysis will also be done.
Assessment of Meta-bias
To test for heterogeneity: Cochrane’s Q value and its p-value, I², Ʈ² will be used. The effect size is the prevalence at a 95% Confidence Interval (CI, 95%). Publication bias will be assessed using a funnel plot. As a rule of thumb, I² values of less than 40% will be considered low heterogeneity while values > 40 but < 75 % will be considered moderate and values > 75% are high.
Further Analysis
Subpopulations in this study are categorical and will be used for subgroup analysis. Diagnostic testing methods will be used as moderators. The pooled effect size for national prevalence and subgroup analysis will be reported in forest plots. Both random and fixed effect models will be assessed, and the appropriate model will be taken based on the forest plots. Publication bias in the selection of studies will be tested using a funnel plot (trim and fill method) and test for funnel plot asymmetry. A cumulative meta-analysis will be performed to check for the trend in the prevalence of hepatitis c virus infection in Nigeria over the years.
Presentation and Reporting of Results
The study selection process will be summarised in a flow diagram according to the PRISMA 2015 (23) Statement and PRISMA-P Checklist (24). A table of the search strategy in various databases showing text words, MeSH, and entry terms will be included. A list of included studies will be summarized in a table. Quantitative data such as effect size (prevalence), 95 % CI, P values, and relative weights assigned to studies and heterogeneity tests will be included in the forest plots. A table of quality scores and risk of bias of each eligible study will be included. Forest plots to show sub-group analysis will be included. A cumulative meta-analysis to check for trends will also be included.