Critical Appraisal of Cohort Studies

Introduction

• Focus: Critical appraisal of cohort studies using the Critical Appraisal Skills Program (CASP) approach.
• Previous module: Discussed RCTs (Randomized Controlled Trials) and their importance in healthcare for attributing causality.
• Importance of observational studies:
  • Not always possible to perform RCTs due to ethical, feasibility, or rarity of outcomes.
• Observational studies:
  • Interest in risk factors, exposures, and outcomes.
  • Researchers observe without manipulating exposures.
  • Calculate measures to quantify risk.

Learning Outcomes

• Introduction to cohort studies, their purpose, and value in healthcare research.
• Critical appraisal using the CASP checklist.
• Calculation and interpretation of the risk ratio.
• Link to a quiz to test knowledge and understanding.

What is a Cohort Study?

• Strongest observational study design.
• Involves identifying participants without the outcome of interest.
• Classify participants by exposure status and follow up over time.
• Example: Smoking and lung cancer.
  • Identify people without lung cancer, classify by smoking status, follow up to compare lung cancer rates.

Risk Ratio

• Ratio of the incidence of disease in the exposed group to the unexposed group.
• Incidence refers to new cases of a disease.
• Relative Risk (RR) interpretation:
  • RR > 1: Exposure increases the risk of disease.
  • RR < 1: Exposure decreases the risk of disease.
  • RR = 1: No difference in risk between exposed and unexposed groups.
• Calculation Example: Smoking and lung cancer.
  • Exposed group risk: a / (a + b) = 0.85
  • Unexposed group risk: c / (c + d) = 0.05
  • Risk Ratio: 0.85 / 0.05 = 17

Cohort Study Appraisal Using CASP Checklist

• Sections: Validity (A), Trustworthiness of Results (B), and Value/Relevance (C).
• Example: Gerhardt et al. (2015) on lithium treatment and dementia risk in bipolar disorder.
  • A. Validity
    • Clearly focused question.
    • Acceptable recruitment method (addresses selection bias).
    • Independent exposure and outcome measurement (addresses measurement bias).
    • Consideration of confounders (e.g., age, gender, health behaviors).
    • Adequate follow-up period.
  • B. Trustworthiness of Results
    • Hazard Ratio: Similar to risk ratio but accounts for time period/rate of events.
    • Confidence Intervals: Range where the true value lies, indicating precision.
  • C. Value/Relevance
    • Biological plausibility and context within the research field.
    • Local applicability of results.

Summary

• Importance of recognizing biases (selection, measurement, confounding).
• Cohort studies' role in quantifying associations between exposure and outcomes.
• Risk and hazard ratios as tools for interpretation.
• Precision and applicability of results.
• Upcoming module focuses on case control studies.
• Support from various NHS trusts and Economic and Social Research Council.
• Link provided for a follow-up quiz to test knowledge.