Nội dung text 10. META ANALYSIS.pdf
PHARMD GURU Page 1 INTRODUCTION: Definition of meta-analysis (from Glass, 1976): The statistical analysis of a large collection of analysis results for the purpose of integrating the findings. The basic purpose of meta-analysis is to provide the same methodological rigor to a literature review that we require from experimental research. We refer to the direct investigation of human or animal data as “primary research.” Providing a report of primary research using statistical methodology and analysis is called “quantitative synthesis” or “meta-analysis.” A report of primary research using traditional, literary methods is called a “narrative review.” Meta-analyses are generally centered on the relationship between one explanatory and one response variable. This relationship, “the effect of X on Y,” defines the analysis. Meta-analysis provides an opportunity for shared subjectivity in reviews, rather than true objectivity. Authors of meta-analyses must sometimes make decisions based on their own judgment, such as when defining the boundaries of the analysis or deciding exactly how to code moderator variables. However, meta- analysis requires that these decisions are made public so they are open to criticism from other scholars. Meta-analyses are most easily performed with the assistance of computer databases (Microsoft Access, Paradox) and statistical software (DSTAT, SAS). Some people consider Meta-analysis as "conducting research about previous research." In Pharmacoepidemiology, it is the compilation of results from a group of studies to arrive at an overall summary estimate of the drug effect, namely benefit or risk. Meta analysis utilizes a variety of methods for aggregating results. The unit of analysis in a meta-analysis is the variable common to the studies being reviewed rather than the individual patient. It is a low statistical analysis of a large collection of analytical results from, individual studies for the purpose of integrating the findings. It is of is a state of art review of literature employing statistical methods in conjunction with a thorough and systematic qualitative review. META ANALYSIS
PHARMD GURU Page 2 Meta analysis can be applied to RCT, Case Control or Cohort Studies. Meta-analysis combines the result of several studies that address a set of related research hypotheses. Meta-analysis appears to be prone to the "garbage in, garbage out" phenomenon. (garbage in garbage out is used in computer or information technology to explain that the quality of output is determined by the quality of the input) Combining a group of poorly done studies can produce a praise summary result made on a weak foundation. The method is not restricted to situations in which one or more variables are defined as "dependent." For example, a meta-analysis could be performed on a collection of studies each of which attempts to estimate the incidence of left-handedness in various groups of people. Researchers should be aware that variations in sampling schemes can introduce heterogeneity to the result, which is the presence of more than one intercept in the solution. For instance, if some studies used 30 mg of a drug, and others used 50 mg, then we would plausibly expect two clusters to be present in the data, each varying around the mean of one dosage or the other. This can be modeled using a "random effects model." Results from studies are combined using different approaches. One approach frequently used in meta-analysis in health care research is termed 'inverse variance method'. The average effect size across all studies is computed as a weighted mean, whereby the weights are equal to the inverse variance of each study’s effect estimator. Larger studies and studies with less random variation are given greater weight than smaller studies. The first meta-analysis was performed by Karl Pearson in 1904. It was an attempt to overcome the problem of reduced statistical power in studies with small sample sizes. Analyzing the results from a group of studies can allow more accurate data analysis. Although meta-analysis is widely used in epidemic logy and evidence- based medicine today, a meta-analysis of a medical treatment was not published until 1955. In the 1970s, more sophisticated analytical techniques were introduced in educational research.
PHARMD GURU Page 3 TYPES OF META-ANALYSIS: By far the most common use of meta-analysis has been in quantitative literature reviews. These are review articles where the authors select a research finding or “effect” that has been investigated in primary research under a large number of different circumstances. They then use meta-analysis to help them describe the overall strength of the effect, and under what circumstances it is stronger and weaker. Recently, as knowledge of meta-analytic techniques has become more widespread, researchers have begun to use meta-analytic summaries within primary research papers. In this case, meta-analysis is used to provide information supporting a specific theoretical statement, usually about the overall strength or consistency of a relationship within the studies being conducted. As might be expected, calculating a meta-analytic summary is typically a much simpler procedure than performing a full quantitative literature review. STEPS TO PERFORM META-ANALYSIS: 1) Define the theoretical relationship of interest. 2) Collect the population of studies that provide data on the relationship. 3) Code the studies and compute effect sizes. 4) Examine the distribution of effect sizes and analyze the impact of moderating variables. 5) Interpret and report the results. USES: Meta-analysis would be used for the following purposes: To establish statistical significance with studies that has conflicting results. To develop a more correct estimate of effect magnitude. To provide a more complex analysis of harms, safety data, and benefits. To examine subgroups with individual numbers those are not statistically significant. If the individual studies utilized randomized controlled trials (RCT), combining several selected RCT results would be the highest-level of evidence on the evidence hierarchy, followed by systematic reviews, which analyze all available studies on a topic.
PHARMD GURU Page 4 ADVANTAGES: Greater statistical power. Confirmatory data analysis. Greater ability to extrapolate to general population affected. Considered an evidence-based resource. DISADVANTAGES: Difficult and time consuming to identify appropriate studies. Not all studies provide adequate data for inclusion and analysis. Requires advanced statistical techniques. Heterogeneity of study populations.