(CD, NR, NA)*
|1. Is the review based on a focused question that is adequately formulated and described?|
|2. Were eligibility criteria for included and excluded studies predefined and specified?|
|3. Did the literature search strategy use a comprehensive, systematic approach?|
|4. Were titles, abstracts, and full-text articles dually and independently reviewed for inclusion and exclusion to minimize bias?|
|5. Was the quality of each included study rated independently by two or more reviewers using a standard method to appraise its internal validity?|
|6. Were the included studies listed along with important characteristics and results of each study?|
|7. Was publication bias assessed?|
|8. Was heterogeneity assessed? (This question applies only to meta-analyses.)|
Quality Rating (Good, Fair, or Poor) (see guidance)
|Rater #1 initials:|
|Rater #2 initials:|
|Additional Comments (If POOR, please state why):|
*CD, cannot determine; NA, not applicable; NR, not reported
Guidance for Quality Assessment Tool for Systematic Reviews and Meta-Analyses
A systematic review is a study that attempts to answer a question by synthesizing the results of primary studies while using strategies to limit bias and random error.424 These strategies include a comprehensive search of all potentially relevant articles and the use of explicit, reproducible criteria in the selection of articles included in the review. Research designs and study characteristics are appraised, data are synthesized, and results are interpreted using a predefined systematic approach that adheres to evidence-based methodological principles.
Systematic reviews can be qualitative or quantitative. A qualitative systematic review summarizes the results of the primary studies but does not combine the results statistically. A quantitative systematic review, or meta-analysis, is a type of systematic review that employs statistical techniques to combine the results of the different studies into a single pooled estimate of effect, often given as an odds ratio. The guidance document below is organized by question number from the tool for quality assessment of systematic reviews and meta-analyses.
Question 1. Focused question
The review should be based on a question that is clearly stated and well-formulated. An example would be a question that uses the PICO (population, intervention, comparator, outcome) format, with all components clearly described.
Question 2. Eligibility criteria
The eligibility criteria used to determine whether studies were included or excluded should be clearly specified and predefined. It should be clear to the reader why studies were included or excluded.
Question 3. Literature search
The search strategy should employ a comprehensive, systematic approach in order to capture all of the evidence possible that pertains to the question of interest. At a minimum, a comprehensive review has the following attributes:
- Electronic searches were conducted using multiple scientific literature databases, such as MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, PsychLit, and others as appropriate for the subject matter.
- Manual searches of references found in articles and textbooks should supplement the electronic searches.
Additional search strategies that may be used to improve the yield include the following:
- Studies published in other countries
- Studies published in languages other than English
- Identification by experts in the field of studies and articles that may have been missed
- Search of grey literature, including technical reports and other papers from government agencies or scientific groups or committees; presentations and posters from scientific meetings, conference proceedings, unpublished manuscripts; and others. Searching the grey literature is important (whenever feasible) because sometimes only positive studies with significant findings are published in the peer-reviewed literature, which can bias the results of a review.
In their reviews, researchers described the literature search strategy clearly, and ascertained it could be reproducible by others with similar results.
Question 4. Dual review for determining which studies to include and exclude
Titles, abstracts, and full-text articles (when indicated) should be reviewed by two independent reviewers to determine which studies to include and exclude in the review. Reviewers resolved disagreements through discussion and consensus or with third parties. They clearly stated the review process, including methods for settling disagreements.
Question 5. Quality appraisal for internal validity
Each included study should be appraised for internal validity (study quality assessment) using a standardized approach for rating the quality of the individual studies. Ideally, this should be done by at least two independent reviewers appraised each study for internal validity. However, there is not one commonly accepted, standardized tool for rating the quality of studies. So, in the research papers, reviewers looked for an assessment of the quality of each study and a clear description of the process used.
Question 6. List and describe included studies
All included studies were listed in the review, along with descriptions of their key characteristics. This was presented either in narrative or table format.
Question 7. Publication bias
Publication bias is a term used when studies with positive results have a higher likelihood of being published, being published rapidly, being published in higher impact journals, being published in English, being published more than once, or being cited by others.425,426 Publication bias can be linked to favorable or unfavorable treatment of research findings due to investigators, editors, industry, commercial interests, or peer reviewers. To minimize the potential for publication bias, researchers can conduct a comprehensive literature search that includes the strategies discussed in Question 3.
A funnel plot–a scatter plot of component studies in a meta-analysis–is a commonly used graphical method for detecting publication bias. If there is no significant publication bias, the graph looks like a symmetrical inverted funnel.
Reviewers assessed and clearly described the likelihood of publication bias.
Question 8. Heterogeneity
Heterogeneity is used to describe important differences in studies included in a meta-analysis that may make it inappropriate to combine the studies.427 Heterogeneity can be clinical (e.g., important differences between study participants, baseline disease severity, and interventions); methodological (e.g., important differences in the design and conduct of the study); or statistical (e.g., important differences in the quantitative results or reported effects).
Researchers usually assess clinical or methodological heterogeneity qualitatively by determining whether it makes sense to combine studies. For example:
- Should a study evaluating the effects of an intervention on CVD risk that involves elderly male smokers with hypertension be combined with a study that involves healthy adults ages 18 to 40? (Clinical Heterogeneity)
- Should a study that uses a randomized controlled trial (RCT) design be combined with a study that uses a case-control study design? (Methodological Heterogeneity)
Statistical heterogeneity describes the degree of variation in the effect estimates from a set of studies; it is assessed quantitatively. The two most common methods used to assess statistical heterogeneity are the Q test (also known as the X2 or chi-square test) or I2 test.
Reviewers examined studies to determine if an assessment for heterogeneity was conducted and clearly described. If the studies are found to be heterogeneous, the investigators should explore and explain the causes of the heterogeneity, and determine what influence, if any, the study differences had on overall study results.
Last Updated March 2014