Reporting in medical literature

Relative Risk - Cohort's Crystal Ball

• What it is: The probability of an outcome in an exposed group compared to the probability in a non-exposed group.
• When to use it: The primary measure for cohort studies (both prospective and retrospective).
• Formula: $RR = \frac{a/(a+b)}{c/(c+d)}$
• Interpretation:
  • $RR = 1$: No association between exposure and outcome.
  • $RR > 1$: Exposure increases the risk of the outcome.
  • $RR < 1$: Exposure decreases the risk of the outcome (protective effect).

⭐ Because RR relies on calculating incidence, it can only be determined in studies that follow groups over time to see who develops the disease.

Odds Ratio - Case-Control's Clue

• Primary Use: The go-to measure of association in case-control studies.
• Calculation: Compares the odds of prior exposure among cases (with disease) to the odds of prior exposure among controls (without disease).
  • Formula: $OR = (a/c) / (b/d) = ad/bc$
• Interpretation:
  • $OR = 1$: No association.
  • $OR > 1$: Increased odds of disease with exposure.
  • $OR < 1$: Decreased odds of disease with exposure (protective).

⭐ For rare diseases (low prevalence, typically <10%), the odds ratio closely approximates the relative risk (RR).

OR vs. RR - The Great Debate

• Odds Ratio (OR): The primary measure for case-control studies. Compares the odds of exposure in the disease group to the odds of exposure in the control group.
• Relative Risk (RR): The standard for cohort studies. Compares the risk of developing a disease in the exposed group to the unexposed group. Requires incidence data.
• The Approximation: OR approximates RR when the disease is rare (the "rare disease assumption").
  • As disease prevalence ↑, the OR increasingly overestimates the RR.

⭐ When interpreting studies, always check the study design. If it's a case-control study, the reported OR is an estimate of the RR. For common diseases, this estimate can be a significant exaggeration of the true risk.

Interpretation - Confidence is Everything

• The 95% Confidence Interval (CI) is key to interpreting RR & OR. It estimates the range where the true population value lies.
• If the 95% CI includes 1.0: The result is NOT statistically significant (p ≥ 0.05). There is no significant association between the exposure and outcome.
• If the 95% CI does NOT include 1.0: The result IS statistically significant (p < 0.05).
  • CI entirely > 1.0: Statistically significant ↑ risk/odds.
  • CI entirely < 1.0: Statistically significant ↓ risk/odds (protective effect).

⭐ If the 95% CI for an odds ratio or relative risk does not include 1.0, the corresponding p-value will be < 0.05, indicating a statistically significant result.

High‑Yield Points - ⚡ Biggest Takeaways

• The odds ratio (OR) is the primary measure of association in case-control studies.
• The relative risk (RR) is the primary measure for cohort studies.
• When the disease prevalence is low (typically <10%), the OR provides a good approximation of the RR.
• If the 95% confidence interval for an OR or RR contains 1.0, the result is not statistically significant.
• An OR overestimates the strength of an association compared to the RR, especially as disease prevalence increases.