Meta analysis.pptx

A meta-analysis is the use of statistical methods to summaries the results of the studies. Meta-analyses are conducted to assess the strength of evidence present on a disease and treatment. The results of a meta-analysis can improve precision of estimates of effect, answer questions not posed by the individual studies, settle controversies arising from apparently conflicting studies, and generate new hypotheses. In particular, the examination of heterogeneity is vital to the development of new hypotheses.

1. META -ANALYSIS BY : Dr. VISHWAS A T L, PHARM.D , (Ph.D.) ASSISTANT PROFESSOR DEPARTMENT OF PHARMACY PRACTICE BHARATHI COLLEGE OF PHARMACY BHARATHINAGARA - 571422

2. CONTENTS DEFINITION AIM AND NEEDS STEPS QUALITY ASSESSMENT ADVANTAGES DISADVANTAGES APPLICATIONS

3. DEFINITION At first meta-analysis in the social science literature is defined as "The statistical analysis of a large collection of analysis results from individual studies for the purpose of integrating the findings". Now Meta-analysis is defined as a quantitative, formal, epidemiological study design used to systematically assess the results of previous research to derive conclusions about that body of research. Typically, but not necessarily, the study is based on randomized, controlled clinical trials. Outcomes from a meta-analysis may include a more precise estimate of the effect of treatment or risk factor for disease, or other outcomes, than any individual study contributing to the pooled analysis.

4. AIM Meta-analyses are conducted to assess the strength of evidence present on a disease and treatment. One aim is to determine whether an effect exist. A nother aim is to determine whether the effect is positive or negative and, ideally, to obtain a single summary estimate of the effect. NEEDS To establish statistical significance with studies that have 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 that are not statistically significant.

5. STEPS INVOLVED IN META - ANALYSIS There are four basic steps involved in conducting meta-anal y sis : Identification Selection Abstraction Analysis

6. STEP1: IDENTIFICATION The first step in a meta-analysis is to find all of the pertinent articles on topic. Important sources of information for a meta-analysis include: MEDLINE EMBASE Cancer Lit, AIDS Line, and Tox Line Index Medicus While MEDLINE, the database of the National Library of Medicine, is a good starting point, it is not the only source of information. MEDLINE indexes approximately 4100 journals, dating from 1966 to the present. It also has an excellent feature called clinical queries.

7. There are also CD-ROM based search engines from BRS Colleague, Win SPIRS, and others which offer different search options, but use essentially the same underlying database. The European version of MEDLINE is called EMBASE, and is a Dutch/English collaboration. Depending on the topic, it may be appropriate to search the more specialized National Library of Medicine databases, such as Cancer Lit, AIDS Line, and Tox Line. The Cochrane collaboration Controlled Trials Register, established in 1993, is an important source of studies for a meta-analysis. The Register includes abstracts of thousands of trials. It includes all controlled trials in the MEDLINE and EMBASE, as well as the results of hand searches by Cochrane Collaboration volunteers of thousands of journals not indexed by MEDLINE or EMBASE. MSU students, faculty and staff can best access the Cochrane through the MSU Library.

8. STEP2 : SELECTION Once the author of a meta-analysis has assembled a large number of studies, it is important to select the right ones. There are a variety of possible inclusion criteria: Whether the study include enough information for analysis (i.e. standard deviation or standard error in addition to point estimate) The study design (i.e. controlled trials only vs randomized controlled trials only, especially for studies of therapy) The year of study, if technology or typical dosing changes (for example, only include studies since 1984 on dyspepsia if you're interested in helicobacter pylori) The dosage used in the study (to assure that an effective dose was used) The language of the article - you or a colleague have to be able to read it! The minimum sample size - very small studies may be unrepresentative and/or not worth the effort The patient age (adults only, > 60 only, etc ) The study setting (emergency department, outpatient, inpatient)

9. STEP3: ABSTRACTION Once an appropriate group of studies has been identified, the author(s) have to abstract the relevant data from each study. There are many sources of potential error in data abstraction: The article may be wrong due to typographical or copyediting errors. Tables can be misinterpreted. Errors can occur during you own data entry or abstraction process. A good meta-analysis will take some or all of the following steps to minimize errors: Use 2 independent reviewers. Use a 3 rd  reviewer or consensus meeting to resolve conflicts. Train reviewers by practicing with several articles to "calibrate“. Use a standard form or database which constrains entries to the expected range. Report the results of the data abstraction, including the percentage concordance or even a kappa statistic. Compare abstract and text to look for inconsistencies. Bias can also creep into a meta-analysis.

10. STEP4: ANALYSIS Homogeneity  and  heterogeneity  describe the degree of between-study variability in a group of studies. It is probably appropriate to combine the results from a homogenous set of studies, but many would argue that results from heterogeneous studies should not be combined.  The Q statistic, interpreted using a chi-square distribution, is often used as a test of homogeneity .  When there is significant  heterogeneity , the between-study variance becomes much larger than the within, and studies of different sample size receive relatively similar weight. When there is  homogeneity , sample size dominates, and both models give similar results. Random effects model s are therefore more "conservative" and generate a wider confidence interval. Put another way, a random effects model is less likely to show a significant treatment effect than a  fixed effects model . In general, if the studies are homogenous, the researchers should use a  fixed effects model . If the studies are heterogeneous, the researcher should use a  random effects analysis.

11. QUALITY ASSESSMENT OF THE META - ANALYSIS Assess for: Research questions clearly defined. Definition of inclusion criteria for studies. Adequacy of the search protocol. Assessment of methodological quality of the included studies. Calculation of a pooled estimate. Plot of the results (forest plot). Measurement of heterogeneity. Assessment of publication bias (funnel plot).

12. ADVANTAGES Greater statistical power. Confirmatory data analysis. Meta-analyses are used by researchers to review large and sometimes complex research. 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.

13. APPLICATIONS Pharmaceutical companies use meta-analysis to gain approval for new drugs, with regulatory agencies sometimes requiring a meta-analysis as part of the approval process. Clinicians and applied researchers in medicine, education, psychology, criminal justice, and a host of other fields use meta-analysis to determine which interventions work, and which ones work best. Meta analysis is also widely used in basic research to evaluate the evidence in areas as diverse as sociology, social psychology, sex differences, finance and economics, political science, marketing, ecology and genetics, among others.