how to conduct a meta-analysis arindam basu md mph about the author required browsing
DESCRIPTION
What is Meta-analysis? Synthesis of previous studies Providing a Summary estimate Steps –Identify studies –Define Eligibility Criteria –Abstract Data –Do Statistical AnalysisTRANSCRIPT
How to Conduct a Meta-Analysis
Arindam Basu MD MPHAbout the AuthorRequired Browsing
Objectives
Following the course, you will be able to:• Define Meta-analysis • Select Studies for a Meta-analysis• Identify different types of Models• Calculate Summary Effects • Interpret Results of a Meta-analysis
What is Meta-analysis?• Synthesis of previous studies• Providing a Summary estimate• Steps
–Identify studies–Define Eligibility Criteria–Abstract Data–Do Statistical Analysis
Identify Studies: Overview• Steps:
–Search Your Personal Files First–Search Electronic Databases–Review Reference Lists of Articles–Contact Experts and Researchers–Retrieve New Articles
• Evaluate Quality of the Studies• Set Up Eligibility Criteria
Searching Electronic Databases• First, Define a Search Strategy • Limitations of Databases
–incomplete and imperfect queries–language problems–problems with fugitive literature
• Publication Bias is important–What is publication bias–How to deal with publication bias
Evaluating Study Quality
• Define Study Quality Criteria Early • Set Up A Good Scoring System• Develop A Form for Assessment• Calculate Quality for each Study• Use this for Sensitivity Analysis
–stratify studies according to quality
Defining Eligibility of StudiesSelect Eligible Studies Based On:• Study Designs• Years of Publication• Language• Choice among multiple articles• Sample-size or follow-up issues• Similarity of Exposure and/or Rx• Completeness of information
Abstract Data - Review!Steps:• Identify Relevant Articles• Sort out Eligible Articles• Set up a Form for Abstraction• Enter the Eligible Studies• Use this as your databaseStatistical Analysis is next...
Statistical Analysis - Overview• Select An Estimate of Effect• Choose An Effects Measure• Select An Effects Model • For Each Model:
–Calculate Summary Effect Size–Calculate Confidence Intervals–Calculate Q-statistic for Homogeneity
• Perform Sensitivity Analysis
Selecting Estimate of Effect• Choose Only One Estimate• For RCTS, choose the one with
–Once randomized always randomized• For nonrandomized trials, choose:
–estimate adjusted only for age–that, and for a known confounder –the “most adjusted” estimate–estimate presented in the abstract
Choosing An Effect Measure• RCTs or Cohort Studies
–Rate Difference between Treatment and Control Groups
–Ratio of Disease Rates• Case Control Studies
–Odds’ Ratio–Rate Ratio
Selecting An Effects Model
• Available Types:–Fixed Effects Model–Random Effects Model
• Difference Between the Two• Special Cases:
–When Outcomes are not binary• Methods to be Used for them
Fixed Effects Model• Methods:
–Mantel Haenszel Method–Peto’s Method–General Variance Based Methods
• For Rate Difference• For Rate Ratios• When only RR and 95 CI given
• Tests of Homogeneity–Calculation of Q Statistic
Mantel Haenszel Method
• Download Spreasheet Calculator• Strength of Mantel Haenszel
–Very powerful–Widely Used
• Limitation–Cannot Control For Confounding!
Peto’s Method• Similar to Mantel Haenszel• Download Calculator• Simpler Computation• No Control for Confounding• Good for RCTs• Requires 2 X 2 Table
Variance-Based Methods• Download Calculators For:
–Rate Difference –For only Relative Risk and 95% CI
• Strengths and Limitations–Good For Rate Differences–Computationally Intensive
Tests of Homogeneity• Establish Null Hypothesis that Effect
Sizes Are Equal in All of the Studies [FAIL TO REJECT NULL]
• Tested By Using Q-statistic• Q-statistic is distributed as chi-square
distribution with degree of freedom = n-1 where n = number of studies
Random Effects Model
• Download The Calculator!• Strengths and Limitations:
–Can Generalize the Conclusions–Computationally Intensive
Continuous Outcomes
• Measurement Scale: Continuous• Outcome Measured in Same Scale
–Download Spreadsheet Calculator!• Essentially Extension of ANOVA• Useful For Integrating Social
Science Research Data
Sensitivity and Publication Bias
• Conduct Sensitivity Analysis–Stratify studies by their quality rating–Compare Fixed and Random Effects
• Deal With Publication Bias–Construct A Funnel Plot