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A stride by step guide for conducting a systematic review and meta-analysis with simulation data
Tropical Medicine and Wellness book 47, Article number:46 (2019) Cite this article
Abstruse
Background
The massive affluence of studies relating to tropical medicine and health has increased strikingly over the last few decades. In the field of tropical medicine and health, a well-conducted systematic review and meta-analysis (SR/MA) is considered a viable solution for keeping clinicians abreast of current prove-based medicine. Understanding of SR/MA steps is of paramount importance for its conduction. It is not piece of cake to be done equally at that place are obstacles that could face the researcher. To solve those hindrances, this methodology study aimed to provide a step-by-step approach mainly for beginners and junior researchers, in the field of tropical medicine and other health care fields, on how to properly conduct a SR/MA, in which all the steps hither depicts our experience and expertise combined with the already well-known and accustomed international guidance.
We suggest that all steps of SR/MA should be washed independently past 2–3 reviewers' discussion, to ensure data quality and accuracy.
Determination
SR/MA steps include the evolution of inquiry question, forming criteria, search strategy, searching databases, protocol registration, title, abstract, total-text screening, manual searching, extracting data, quality assessment, information checking, statistical analysis, double data checking, and manuscript writing.
Introduction
The amount of studies published in the biomedical literature, peculiarly tropical medicine and wellness, has increased strikingly over the concluding few decades. This massive affluence of literature makes clinical medicine increasingly circuitous, and knowledge from diverse researches is often needed to inform a particular clinical decision. Even so, available studies are oft heterogeneous with regard to their design, operational quality, and subjects nether report and may handle the research question in a unlike way, which adds to the complexity of show and conclusion synthesis [one].
Systematic review and meta-analyses (SR/MAs) accept a high level of testify as represented by the evidence-based pyramid. Therefore, a well-conducted SR/MA is considered a feasible solution in keeping wellness clinicians ahead regarding contemporary evidence-based medicine.
Differing from a systematic review, unsystematic narrative review tends to be descriptive, in which the authors select ofttimes manufactures based on their point of view which leads to its poor quality. A systematic review, on the other hand, is defined equally a review using a systematic method to summarize evidence on questions with a detailed and comprehensive plan of study. Furthermore, despite the increasing guidelines for finer conducting a systematic review, we found that basic steps often kickoff from framing question, then identifying relevant work which consists of criteria evolution and search for articles, assess the quality of included studies, summarize the evidence, and translate the results [ii, three]. However, those simple steps are not easy to exist reached in reality. In that location are many troubles that a researcher could be struggled with which has no detailed indication.
Conducting a SR/MA in tropical medicine and health may be difficult especially for immature researchers; therefore, understanding of its essential steps is crucial. It is not easy to be done as at that place are obstacles that could face the researcher. To solve those hindrances, we recommend a flow diagram (Fig. 1) which illustrates a detailed and step-by-step the stages for SR/MA studies. This methodology study aimed to provide a step-by-step approach mainly for beginners and junior researchers, in the field of tropical medicine and other wellness care fields, on how to properly and succinctly conduct a SR/MA; all the steps here depicts our feel and expertise combined with the already well known and accepted international guidance.
Detailed flow diagram guideline for systematic review and meta-analysis steps. Note: Star icon refers to "2–three reviewers screen independently"
Methods and results
Detailed steps for conducting whatever systematic review and meta-analysis
Nosotros searched the methods reported in published SR/MA in tropical medicine and other healthcare fields too the published guidelines like Cochrane guidelines {Higgins, 2011 #7} [four] to collect the best low-bias method for each stride of SR/MA conduction steps. Furthermore, we used guidelines that we apply in studies for all SR/MA steps. Nosotros combined these methods in order to conclude and deport a detailed flow diagram that shows the SR/MA steps how being conducted.
Whatever SR/MA must follow the widely accepted Preferred Reporting Items for Systematic Review and Meta-analysis statement (PRISMA checklist 2009) (Boosted file 5: Table S1) [5].
Nosotros proposed our methods according to a valid explanatory simulation case choosing the topic of "evaluating condom of Ebola vaccine," as it is known that Ebola is a very rare tropical illness just fatal. All the explained methods feature the standards followed internationally, with our compiled experience in the conduct of SR beside it, which we think proved some validity. This is a SR under carry by a couple of researchers teaming in a research group, moreover, as the outbreak of Ebola which took identify (2013–2016) in Africa resulted in a pregnant mortality and morbidity. Furthermore, since there are many published and ongoing trials assessing the safety of Ebola vaccines, we thought this would provide a bang-up opportunity to tackle this hotly debated consequence. Moreover, Ebola started to burn down once again and new fatal outbreak appeared in the Democratic Republic of Congo since August 2018, which caused infection to more than than 1000 people according to the Earth Health Organization, and 629 people have been killed till now. Hence, it is considered the 2nd worst Ebola outbreak, subsequently the get-go one in West Africa in 2014, which infected more than 26,000 and killed nearly 11,300 people along outbreak course.
Research question and objectives
Like other written report designs, the research question of SR/MA should exist feasible, interesting, novel, ethical, and relevant. Therefore, a articulate, logical, and well-defined research question should be formulated. Usually, 2 common tools are used: PICO or SPIDER. PICO (Population, Intervention, Comparison, Outcome) is used mostly in quantitative prove synthesis. Authors demonstrated that PICO holds more sensitivity than the more specific SPIDER approach [6]. SPIDER (Sample, Phenomenon of Involvement, Design, Evaluation, Enquiry type) was proposed as a method for qualitative and mixed methods search.
We here recommend a combined approach of using either one or both the SPIDER and PICO tools to call up a comprehensive search depending on time and resources limitations. When nosotros utilize this to our assumed inquiry topic, being of qualitative nature, the use of SPIDER approach is more valid.
PICO is ordinarily used for systematic review and meta-assay of clinical trial written report. For the observational study (without intervention or comparator), in many tropical and epidemiological questions, information technology is usually enough to utilise P (Patient) and O (effect) merely to formulate a inquiry question. We must indicate clearly the population (P), then intervention (I) or exposure. Next, it is necessary to compare (C) the indicated intervention with other interventions, i.due east., placebo. Finally, we demand to clarify which are our relevant outcomes.
To facilitate comprehension, we choose the Ebola virus disease (EVD) every bit an instance. Currently, the vaccine for EVD is beingness developed and nether phase I, 2, and III clinical trials; nosotros desire to know whether this vaccine is safe and can induce sufficient immunogenicity to the subjects.
An example of a enquiry question for SR/MA based on PICO for this effect is as follows: How is the safety and immunogenicity of Ebola vaccine in human being? (P: good for you subjects (homo), I: vaccination, C: placebo, O: condom or adverse effects)
Preliminary research and idea validation
We recommend a preliminary search to place relevant articles, ensure the validity of the proposed idea, avoid duplication of previously addressed questions, and clinch that we accept enough articles for conducting its analysis. Moreover, themes should focus on relevant and of import health-care bug, consider global needs and values, reflect the electric current science, and exist consistent with the adopted review methods. Gaining familiarity with a deep agreement of the study field through relevant videos and discussions is of paramount importance for improve retrieval of results. If we ignore this stride, our study could be canceled whenever nosotros find out a similar study published earlier. This means nosotros are wasting our time to deal with a problem that has been tackled for a long time.
To do this, we can outset by doing a simple search in PubMed or Google Scholar with search terms Ebola AND vaccine. While doing this step, we place a systematic review and meta-analysis of determinant factors influencing antibody response from vaccination of Ebola vaccine in not-human primate and human [7], which is a relevant newspaper to read to become a deeper insight and identify gaps for better formulation of our research question or purpose. We can still acquit systematic review and meta-analysis of Ebola vaccine because we evaluate safety as a unlike result and different population (only homo).
Inclusion and exclusion criteria
Eligibility criteria are based on the PICO arroyo, study design, and date. Exclusion criteria by and large are unrelated, duplicated, unavailable full texts, or abstract-only papers. These exclusions should be stated in advance to refrain the researcher from bias. The inclusion criteria would exist articles with the target patients, investigated interventions, or the comparison between two studied interventions. Briefly, it would be articles which contain information answering our research question. But the nigh important is that information technology should be clear and sufficient information, including positive or negative, to answer the question.
For the topic nosotros take chosen, we tin make inclusion criteria: (1) whatever clinical trial evaluating the safety of Ebola vaccine and (2) no restriction regarding land, patient historic period, race, gender, publication linguistic communication, and appointment. Exclusion criteria are as follows: (one) study of Ebola vaccine in not-human subjects or in vitro studies; (2) study with data not reliably extracted, duplicate, or overlapping information; (3) abstract-only papers as preceding papers, conference, editorial, and author response theses and books; (4) articles without available full text available; and (5) case reports, case series, and systematic review studies. The PRISMA flow diagram template that is used in SR/MA studies can be found in Fig. 2.
PRISMA catamenia diagram of studies' screening and selection
Search strategy
A standard search strategy is used in PubMed, then afterwards it is modified co-ordinate to each specific database to become the best relevant results. The basic search strategy is congenital based on the research question conception (i.e., PICO or PICOS). Search strategies are constructed to include free-text terms (e.1000., in the title and abstract) and whatever advisable discipline indexing (due east.g., MeSH) expected to call up eligible studies, with the help of an expert in the review topic field or an data specialist. Additionally, we advise not to utilize terms for the Outcomes as their inclusion might hinder the database being searched to think eligible studies considering the used outcome is not mentioned obviously in the articles.
The improvement of the search term is made while doing a trial search and looking for some other relevant term inside each concept from retrieved papers. To search for a clinical trial, we can use these descriptors in PubMed: "clinical trial"[Publication Type] OR "clinical trials as topic"[MeSH terms] OR "clinical trial"[All Fields]. After some rounds of trial and refinement of search term, we formulate the last search term for PubMed as follows: (ebola OR ebola virus OR ebola virus disease OR EVD) AND (vaccine OR vaccination OR vaccinated OR immunization) AND ("clinical trial"[Publication Type] OR "clinical trials equally topic"[MeSH Terms] OR "clinical trial"[All Fields]). Because the written report for this topic is limited, nosotros do non include outcome term (condom and immunogenicity) in the search term to capture more studies.
Search databases, import all results to a library, and exporting to an excel canvas
According to the AMSTAR guidelines, at to the lowest degree 2 databases have to be searched in the SR/MA [8], but as you lot increase the number of searched databases, you get much yield and more accurate and comprehensive results. The ordering of the databases depends mostly on the review questions; being in a study of clinical trials, you will rely by and large on Cochrane, mRCTs, or International Clinical Trials Registry Platform (ICTRP). Here, we propose 12 databases (PubMed, Scopus, Web of Scientific discipline, EMBASE, GHL, VHL, Cochrane, Google Scholar, Clinical trials.gov, mRCTs, POPLINE, and SIGLE), which help to cover almost all published articles in tropical medicine and other health-related fields. Among those databases, POPLINE focuses on reproductive health. Researchers should consider to choose relevant database according to the enquiry topic. Some databases practice not support the employ of Boolean or quotation; otherwise, there are some databases that have special searching way. Therefore, nosotros need to alter the initial search terms for each database to get appreciated results; therefore, manipulation guides for each online database searches are presented in Boosted file v: Table S2. The detailed search strategy for each database is institute in Additional file 5: Table S3. The search term that we created in PubMed needs customization based on a specific characteristic of the database. An case for Google Scholar avant-garde search for our topic is as follows:
- one.
With all of the words: ebola virus
With at least one of the words: vaccine vaccination vaccinated immunization
Where my words occur: in the title of the article
- 2.
With all of the words: EVD
With at least one of the words: vaccine vaccination vaccinated immunization
Where my words occur: in the title of the article
Finally, all records are collected into ane Endnote library in society to delete duplicates so to it consign into an excel canvass. Using remove duplicating function with 2 options is mandatory. All references which have (1) the same championship and author, and published in the same year, and (2) the aforementioned title and author, and published in the same journal, would be deleted. References remaining later on this footstep should be exported to an excel file with essential information for screening. These could exist the authors' names, publication year, journal, DOI, URL link, and abstract.
Protocol writing and registration
Protocol registration at an early stage guarantees transparency in the inquiry process and protects from duplication issues. Besides, it is considered a documented proof of team plan of action, enquiry question, eligibility criteria, intervention/exposure, quality assessment, and pre-analysis plan. It is recommended that researchers send information technology to the principal investigator (PI) to revise information technology, then upload it to registry sites. There are many registry sites available for SR/MA similar those proposed past Cochrane and Campbell collaborations; yet, we recommend registering the protocol into PROSPERO as information technology is easier. The layout of a protocol template, according to PROSPERO, can be found in Additional file 5: File S1.
Title and abstruse screening
Decisions to select retrieved articles for further cess are based on eligibility criteria, to minimize the chance of including not-relevant articles. Co-ordinate to the Cochrane guidance, two reviewers are a must to practice this footstep, simply as for beginners and inferior researchers, this might be tiresome; thus, we advise based on our experience that at least three reviewers should work independently to reduce the chance of error, particularly in teams with a large number of authors to add more scrutiny and ensure proper conduct. Mostly, the quality with three reviewers would be amend than two, equally 2 just would have dissimilar opinions from each other, and so they cannot decide, while the third opinion is crucial. And here are some examples of systematic reviews which nosotros conducted following the aforementioned strategy (by a different group of researchers in our enquiry group) and published successfully, and they feature relevant ideas to tropical medicine and affliction [9,ten,11].
In this step, duplications will be removed manually whenever the reviewers notice them out. When there is a incertitude nearly an article determination, the team should exist inclusive rather than sectional, until the main leader or PI makes a decision after word and consensus. All excluded records should exist given exclusion reasons.
Full text downloading and screening
Many search engines provide links for costless to access full-text articles. In case not institute, nosotros tin search in some research websites as ResearchGate, which offer an option of direct full-text asking from authors. Additionally, exploring archives of wanted journals, or contacting PI to buy it if bachelor. Similarly, 2–iii reviewers piece of work independently to decide about included full texts according to eligibility criteria, with reporting exclusion reasons of articles. In case any disagreement has occurred, the final decision has to be made past word.
Manual search
One has to exhaust all possibilities to reduce bias by performing an explicit paw-searching for retrieval of reports that may have been dropped from get-go search [12]. We utilize v methods to make transmission searching: searching references from included studies/reviews, contacting authors and experts, and looking at related manufactures/cited articles in PubMed and Google Scholar.
We describe here three consecutive methods to increase and refine the yield of manual searching: firstly, searching reference lists of included articles; secondly, performing what is known as citation tracking in which the reviewers track all the articles that cite each ane of the included articles, and this might involve electronic searching of databases; and thirdly, similar to the citation tracking, we follow all "related to" or "similar" articles. Each of the abovementioned methods can be performed by 2–3 independent reviewers, and all the possible relevant article must undergo further scrutiny confronting the inclusion criteria, later on following the aforementioned records yielded from electronic databases, i.e., championship/abstract and full-text screening.
We propose an contained reviewing past assigning each member of the teams a "tag" and a distinct method, to compile all the results at the terminate for comparing of differences and discussion and to maximize the retrieval and minimize the bias. Similarly, the number of included articles has to exist stated earlier add-on to the overall included records.
Data extraction and quality assessment
This step entitles data collection from included total-texts in a structured extraction excel canvas, which is previously airplane pilot-tested for extraction using some random studies. We recommend extracting both adjusted and non-adapted data because it gives the most immune confounding cistron to be used in the assay past pooling them later [xiii]. The procedure of extraction should be executed by 2–3 independent reviewers. More often than not, the sheet is classified into the study and patient characteristics, outcomes, and quality assessment (QA) tool.
Data presented in graphs should be extracted by software tools such as Web plot digitizer [14]. Most of the equations that can be used in extraction prior to analysis and estimation of standard deviation (SD) from other variables is found inside Boosted file 5: File S2 with their references as Hozo et al. [15], Xiang et al. [xvi], and Rijkom et al. [17]. A variety of tools are available for the QA, depending on the design: ROB-two Cochrane tool for randomized controlled trials [18] which is presented as Additional file one: Figure S1 and Additional file 2: Figure S2—from a previous published article data—[19], NIH tool for observational and cantankerous-sectional studies [xx], ROBINS-I tool for non-randomize trials [21], QUADAS-2 tool for diagnostic studies, QUIPS tool for prognostic studies, CARE tool for case reports, and ToxRtool for in vivo and in vitro studies. We recommend that 2–3 reviewers independently assess the quality of the studies and add to the data extraction grade earlier the inclusion into the analysis to reduce the risk of bias. In the NIH tool for observational studies—accomplice and cantankerous-sectional—equally in this EBOLA case, to evaluate the risk of bias, reviewers should rate each of the 14 items into dichotomous variables: yes, no, or non applicable. An overall score is calculated by adding all the items scores every bit yep equals one, while no and NA equals zero. A score will be given for every paper to allocate them as poor, fair, or good conducted studies, where a score from 0–5 was considered poor, 6–nine as fair, and 10–fourteen as good.
In the EBOLA case instance in a higher place, authors can extract the post-obit information: name of authors, land of patients, year of publication, study design (case report, cohort study, or clinical trial or RCT), sample size, the infected point of fourth dimension afterward EBOLA infection, follow-up interval subsequently vaccination time, efficacy, rubber, adverse furnishings subsequently vaccinations, and QA sail (Additional file vi: Information S1).
Data checking
Due to the expected man fault and bias, nosotros recommend a information checking step, in which every included article is compared with its analogue in an extraction sheet by prove photos, to discover mistakes in data. We suggest assigning articles to 2–three contained reviewers, ideally not the ones who performed the extraction of those manufactures. When resources are limited, each reviewer is assigned a different article than the one he extracted in the previous stage.
Statistical analysis
Investigators utilise different methods for combining and summarizing findings of included studies. Before analysis, there is an of import step called cleaning of data in the extraction sheet, where the analyst organizes extraction sheet information in a course that can be read past analytical software. The analysis consists of 2 types namely qualitative and quantitative analysis. Qualitative analysis by and large describes data in SR studies, while quantitative analysis consists of two main types: MA and network meta-assay (NMA). Subgroup, sensitivity, cumulative analyses, and meta-regression are appropriate for testing whether the results are consistent or non and investigating the event of certain confounders on the outcome and finding the best predictors. Publication bias should be assessed to investigate the presence of missing studies which can affect the summary.
To illustrate basic meta-analysis, we provide an imaginary data for the research question about Ebola vaccine rubber (in terms of agin events, xiv days after injection) and immunogenicity (Ebola virus antibodies ascent in geometric mean titer, half-dozen months after injection). Assuming that from searching and data extraction, we decided to do an analysis to evaluate Ebola vaccine "A" safety and immunogenicity. Other Ebola vaccines were not meta-analyzed because of the limited number of studies (instead, it will be included for narrative review). The imaginary data for vaccine prophylactic meta-analysis can exist accessed in Additional file 7: Information S2. To do the meta-analysis, we can use free software, such every bit RevMan [22] or R package meta [23]. In this example, we volition utilize the R packet meta. The tutorial of meta package tin be accessed through "General Package for Meta-Analysis" tutorial pdf [23]. The R codes and its guidance for meta-assay done tin be establish in Additional file 5: File S3.
For the analysis, we presume that the report is heterogenous in nature; therefore, we choose a random effect model. We did an assay on the safety of Ebola vaccine A. From the data table, we can see some adverse events occurring after intramuscular injection of vaccine A to the subject field of the report. Suppose that nosotros include vi studies that fulfill our inclusion criteria. We tin can do a meta-analysis for each of the adverse events extracted from the studies, for example, arthralgia, from the results of random outcome meta-analysis using the R meta package.
From the results shown in Additional file three: Figure S3, we can see that the odds ratio (OR) of arthralgia is 1.06 (0.79; 1.42), p value = 0.71, which ways that there is no association betwixt the intramuscular injection of Ebola vaccine A and arthralgia, as the OR is well-nigh ane, and besides, the P value is insignificant as information technology is > 0.05.
In the meta-analysis, we can also visualize the results in a woods plot. It is shown in Fig. iii an instance of a forest plot from the simulated analysis.
Random effect model forest plot for comparing of vaccine A versus placebo
From the forest plot, we tin come across six studies (A to F) and their respective OR (95% CI). The green box represents the event size (in this example, OR) of each study. The bigger the box ways the study weighted more (i.e., bigger sample size). The blue diamond shape represents the pooled OR of the 6 studies. We tin can see the blue diamond cross the vertical line OR = 1, which indicates no significance for the association equally the diamond almost equalized in both sides. We can confirm this also from the 95% confidence interval that includes one and the p value > 0.05.
For heterogeneity, we see that I 2 = 0%, which means no heterogeneity is detected; the study is relatively homogenous (it is rare in the real report). To evaluate publication bias related to the meta-analysis of adverse events of arthralgia, we tin use the metabias function from the R meta package (Additional file 4: Figure S4) and visualization using a funnel plot. The results of publication bias are demonstrated in Fig. four. We run across that the p value associated with this exam is 0.74, indicating symmetry of the funnel plot. Nosotros can confirm it by looking at the funnel plot.
Publication bias funnel plot for comparison of vaccine A versus placebo
Looking at the funnel plot, the number of studies at the left and right side of the funnel plot is the aforementioned; therefore, the plot is symmetry, indicating no publication bias detected.
Sensitivity assay is a process used to discover how different values of an independent variable will influence the significance of a particular dependent variable past removing one study from MA. If all included study p values are < 0.05, hence, removing any study will not change the significant association. It is just performed when there is a meaning clan, so if the p value of MA done is 0.7—more than one—the sensitivity assay is not needed for this case report instance. If there are ii studies with p value > 0.05, removing any of the two studies volition result in a loss of the significance.
Double data checking
For more assurance on the quality of results, the analyzed information should exist rechecked from total-text data by evidence photos, to allow an obvious check for the PI of the study.
Manuscript writing, revision, and submission to a journal
Writing based on four scientific sections: introduction, methods, results, and give-and-take, more often than not with a conclusion. Performing a feature tabular array for study and patient characteristics is a mandatory step which can be found every bit a template in Additional file 5: Tabular array S3.
After finishing the manuscript writing, characteristics table, and PRISMA menstruum diagram, the squad should transport it to the PI to revise information technology well and reply to his comments and, finally, choose a suitable journal for the manuscript which fits with considerable impact factor and fitting field. We demand to pay attention by reading the writer guidelines of journals before submitting the manuscript.
Word
The function of prove-based medicine in biomedical enquiry is speedily growing. SR/MAs are also increasing in the medical literature. This paper has sought to provide a comprehensive approach to enable reviewers to produce high-quality SR/MAs. Nosotros hope that readers could gain full general knowledge about how to conduct a SR/MA and take the confidence to perform one, although this kind of study requires complex steps compared to narrative reviews.
Having the bones steps for conduction of MA, there are many advanced steps that are applied for certain specific purposes. One of these steps is meta-regression which is performed to investigate the association of any confounder and the results of the MA. Furthermore, at that place are other types rather than the standard MA similar NMA and MA. In NMA, we investigate the deviation betwixt several comparisons when there were not enough data to enable standard meta-analysis. It uses both direct and indirect comparisons to conclude what is the all-time between the competitors. On the other hand, mega MA or MA of patients tend to summarize the results of independent studies by using its individual subject data. As a more detailed analysis can exist done, it is useful in conducting repeated measure out assay and time-to-effect assay. Moreover, it can perform analysis of variance and multiple regression analysis; however, it requires homogenous dataset and information technology is time-consuming in conduct [24].
Conclusions
Systematic review/meta-analysis steps include evolution of research question and its validation, forming criteria, search strategy, searching databases, importing all results to a library and exporting to an excel sheet, protocol writing and registration, championship and abstract screening, full-text screening, manual searching, extracting information and assessing its quality, data checking, conducting statistical analysis, double data checking, manuscript writing, revising, and submitting to a journal.
Availability of data and materials
Non applicable.
Abbreviations
- NMA:
-
Network meta-assay
- PI:
-
Chief investigator
- PICO:
-
Population, Intervention, Comparing, Event
- PRISMA:
-
Preferred Reporting Items for Systematic Review and Meta-assay statement
- QA:
-
Quality assessment
- SPIDER:
-
Sample, Miracle of Interest, Design, Evaluation, Research blazon
- SR/MAs:
-
Systematic review and meta-analyses
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Funding
This report was conducted (in part) at the Articulation Usage/Research Center on Tropical Disease, Institute of Tropical Medicine, Nagasaki University, Japan.
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NTH and GMT were responsible for the thought and its design. The figure was done by GMT. All authors contributed to the manuscript writing and approval of the concluding version.
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Additional files
Boosted file 1:
Figure S1. Hazard of bias assessment graph of included randomized controlled trials. (TIF 20 kb)
Additional file 2:
Effigy S2. Risk of bias assessment summary. (TIF 69 kb)
Additional file iii:
Effigy S3. Arthralgia results of random result meta-analysis using R meta package. (TIF 20 kb)
Boosted file 4:
Figure S4. Arthralgia linear regression test of funnel plot asymmetry using R meta package. (TIF thirteen kb)
Additional file 5:
Table S1. PRISMA 2009 Checklist. Table S2. Manipulation guides for online database searches. Table S3. Detailed search strategy for twelve database searches. Table S4. Baseline characteristics of the patients in the included studies. File S1. PROSPERO protocol template file. File S2. Extraction equations that can exist used prior to analysis to go missed variables. File S3. R codes and its guidance for meta-analysis done for comparison betwixt EBOLA vaccine A and placebo. (DOCX 49 kb)
Additional file vi:
Data S1. Extraction and quality assessment data sheets for EBOLA example case. (XLSX 1368 kb)
Boosted file 7:
Data S2. Imaginary data for EBOLA example case. (XLSX 10 kb)
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Tawfik, One thousand.Grand., Dila, G.A.S., Mohamed, Yard.Y.F. et al. A step by step guide for conducting a systematic review and meta-analysis with simulation information. Trop Med Wellness 47, 46 (2019). https://doi.org/10.1186/s41182-019-0165-6
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DOI : https://doi.org/10.1186/s41182-019-0165-6
Keywords
- Search
- Data
- Extraction
- Analysis
- Written report
- Results
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