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Critique of Randomized Controlled Trials: Validity and Study Design Essentials

This study guide critically examines the validity of randomized controlled trials (RCTs) focusing on their internal, construct, and external validity. It provides a detailed framework for assessing relationships between study variables, evaluating causal relationships, and generalizing findings. Key concepts such as random error, bias, and confounding effects are elucidated. The guide outlines the essential steps in designing a study, including topic selection, hypothesis formulation, sample size determination, and data analysis. By understanding these principles, researchers can enhance the rigor and reliability of their investigations.

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Critique of Randomized Controlled Trials: Validity and Study Design Essentials

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  1. Research Rotation Part II B Kanna MD, MPH, FACP Associate Program Director of Internal Medicine Associate Director of Graduate Medical Education for Research

  2. Section I Critique of A randomized controlled clinical trial

  3. Validity • the best available approximation to the truth of a given proposition, inference, or conclusion • Accurate & reproducible Person 2 Person 1

  4. Checking Validity • Conclusion Validity: • In this study, is there a relationship between the two variables? • Internal Validity: • Assuming that there is a relationship in this study, is the relationship a causal one? • Construct Validity: • Assuming that there is a causal relationship in this study, did we implement the program we intended to implement and did we measure the outcome we wanted to measure? • External Validity: • Assuming that there is a causal relationship in this study between the constructs of the cause and the effect, can we generalize this effect to other persons, places or times? http://www.socialresearchmethods.net/kb/introval.php

  5. Random Error Sample 2 Universe of subjects Sample 1 CHANCE Sample 3 CHANCE

  6. Checking Internal validity Universe of subjects Sample 2 Confounding Rx Outcome Sample 3 Bias

  7. Applying this to a study/observation Day 1 Red pill Sx improves Day 2 Red pill Sx improves Day 3 Red pill Sx improves

  8. THREE THINGS TO REMEMBER! • CHANCE – RANDOM ERROR • BIAS – SYSTEMATIC ERROR • CONFOUNDING – ADDITIONAL FACTORS

  9. How to apply these concepts during the critique of RCT • Learn the general steps in a study design • Choose a topic • Define a hypothesis • Select patients • Sample size • Randomization • Treatment • Follow-up • Collection of data • Analysis • Interpretation • Conclusion • Generalize findings

  10. Section II Selected topics

  11. Study designs • Observational • Case control • Cohort • Cross sectional • Interventional • Randomized • Non-randomized

  12. Number needed to Rx and harm • NNT = 1/ Absolute risk reduction • Rx = 0.9% • Placebo = 3.2% • ARR = 5.0- 2.5 = 2.3% • NNT = 1/ 0.023 = 45 • NNH = 1 / Absolute risk of adverse events

  13. Sensitivity, Specificity & Post test probability

  14. How to design & start a study • Step 1: Select a topic • Step 2: Choose a mentor and guide • Step 3: Define topic • Step 4: Search literature • Step 5: Define problem • Step 6: Collect back ground information • Step 7: Study Methods Study design; Sample selection; Sample size; Inclusion & Exclusion criteria Follow-up; Measurements; Endpoints; Statistical methods;, P value, CI, Test of significance Confounding factors, Stratification, Regression Results, Discussion , Limitations • Step 8: IRB application along with aggregate data request • Step 9: IRB approval • Step 10: Start project (Revise protocol if needed and apply for IRB modifications)

  15. How to write an IRB protocol Simplified Guide for residents • 1. Title page Title; Authors; Contact information of primary authors; Department • 2. Summary of the protocol • 3. Introduction Problem definition; Magnitude; Need for study • 4. Background Physiologic principles; Cause and effect; Hypothesis • 5. Methods Study design; Sample selection; Inclusion & Exclusion criteria; Sample size Data collection (tool); Follow-up( If applicable) ; Measurements ( if applicable); Endpoints • 6. Statistical methods Testing hypothesis; P value; CI; Tests of significance; Others analyses (e.g. subgroups) • 7. Confounding & Bias Confounding ; Stratification; Regression; Methods used to Limit Bias • 8. Confidentiality and Privacy • 9. Consent/Waiver ( see Lincoln IRB consent procedures) • 10. Reporting of results • 11. Significance or Implications of the study • 12. References • 13. Tables, Figures and legends

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