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edX

CERTaIN: Knowledge Synthesis: Systematic Reviews and Clinical Decision Making

The University of Texas MD Anderson Cancer Center via edX

Overview

Discover practical ways to critically appraise scientific literature, including the conduction and interpretation of systematic reviews and meta-analyses. Additionally, you will learn how to conduct literature searches using online academic databases, hear about economic evaluations, and understand how clinical practice guidelines are used to guide decision making.

This course includes the following 11 lectures:

  1. Overview of Systematic Reviews
  2. Finding and Managing the Evidence from the Biomedical Literature
  3. Intervention Reviews Methodology
  4. Meta-Analysis of Clinical Trials: Direct Comparisons
  5. Introduction to Meta-Analysis: Indirect Comparisons
  6. Meta-Analysis of Non-Randomized Studies
  7. Diagnostic Test Evaluation
  8. Meta-Synthesis
  9. Clinical Practice Guidelines
  10. Economic Evaluation
  11. Decision Analysis for Outcomes Research

This course is intended for anyone interested in comparative effectiveness research (CER) and patient-centered outcomes research (PCOR) methods.

This course is supported by grant number R25HS023214 from the Agency for Healthcare Research and Quality.

Syllabus

Overview of Systematic Reviews

  • Knowledge synthesis and the knowledge-to-action process
  • Benefits and limitations of systematic reviews
  • Steps of a systematic review and levels of evidence

Finding and Managing the Evidence from the Biomedical Literature

  • How to search published and unpublished materials on topic of interest in a systematic and repeatable manner

Intervention Reviews Methodology

  • How to select and appraise studies
  • Strategies for collecting and analyzing data
  • How to report and update systematic reviews

Meta-Analysis of Clinical Trials: Direct Comparisons

  • Qualitative and quantitative synthesis
  • Models to use during data analysis
  • Heterogeneity
  • Reporting methods for meta-analyses

Introduction to Meta-Analysis: Indirect Comparisons

  • Indirect comparisons
  • Evidence networks
  • Effect modifiers and how they are a source of bias

Meta-Analysis of Non-Randomized Studies

  • Risks of bias in non-randomized studies
  • Meta-regression as a tool to reduce risk of bias
  • Caveats of meta-regression
  • Reporting meta-analyses of non-randomized studies

Diagnostic Test Evaluation

  • Purposes for medical testing
  • Precision and accuracy
  • Measures of validity for diagnostic/screening tests
  • Likelihood ratio for analysis of test performance
  • ROC curves for analysis of test performance

Meta-Synthesis

  • Methods for collecting and synthesizing data
  • Reporting of meta-synthesis findings

Clinical Practice Guidelines

  • Process of guideline development
  • How evidence is evaluated
  • How clinical practice guidelines are evaluated and revised

Economic Evaluation

  • Clinical decision analysis and economic evaluation
  • Costs and methods for economic evaluation
  • Cost-effectiveness and cost analysis
  • Steps for economic evaluation

Decision Analysis for Outcomes Research

  • Decision analysis and modeling
  • Markov modeling
  • Capturing of uncertainty in models
  • Examples of decision modeling in cancer outcomes research

Taught by

Maria E. Suarez-Almazor, MD, PhD and Maria A. Lopez-Olivo, MD, PhD

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