Relative Risk & Odds Ratios

Summary

This video introduces the concepts of relative risk and odds ratio, explaining how they are calculated and interpreted in epidemiological studies. It covers the differences between the two measures, their applications in cohort and case-control studies, and the importance of statistical significance. The video also discusses how to construct and use a 2x2 contingency table for these calculations and emphasizes the distinctions between odds and probability. Finally, it highlights the conditions under which each measure should be used and potential pitfalls in their interpretation.

Takeaways

• 📊 The video introduces the concepts of relative risk and odds ratio, explaining how they are used to compare the occurrence of events between two groups in studies.
• 🔍 An association is identified when the risk among the exposed is higher than among those not exposed, highlighting the relationship between exposure and outcome.
• 📈 The interpretation of relative risk or odds ratio involves two components: the point estimate (the actual number) and the statistical significance (p-value and/or confidence interval).
• 🚬 Relative risk is used for comparing the probability of an event occurring to all possible events, such as the risk of developing lung cancer in those exposed to secondhand smoke.
• 📝 A 2x2 contingency table is essential for calculating incidence rates and relative risk in cohort studies, providing frequency counts of events for both exposed and unexposed groups.
• 🔢 The formula for relative risk is the proportion of individuals with the event in the exposed group divided by the proportion in the unexposed group.
• 📉 A relative risk of one indicates no difference between groups, greater than one suggests a positive association, and less than one indicates a negative association or protective effect.
• ⚠️ The significance of relative risk is determined by the p-value and confidence interval; if the p-value is ≥ 0.05 or the interval includes 1, the risk is not statistically significant.
• 🚫 Case-control studies cannot calculate relative risk because they compare cases with the event to controls without the event, making them retrospective and not suitable for incidence or risk calculation.
• 🎰 Odds ratio is used when relative risk cannot be calculated, such as in case-control studies, and is based on the odds of an event occurring rather than the probability.
• 🔄 The formula for odds ratio is the cross product of a 2x2 table, dividing the odds of the exposed group by the odds of the unexposed group.
• 📚 Odds ratios can be calculated for both cohort and case-control studies and are comparable in magnitude to relative risk only when the outcome is rare.
• 📉 Odds ratios may overestimate risk when the outcome is common, so relative risk should be used if possible, and caution is advised when interpreting odds ratios.
• 📘 The video concludes by noting that odds ratios are common in medical literature for both study types and are often the result of logistic regression analysis.

Q & A

What are the two main statistics used to compare the occurrence of events between two groups in studies?

The two main statistics used are relative risk and odds ratio.

What is the purpose of calculating relative risk or odds ratio in a study?

The purpose is to determine whether an association exists between exposure and outcome and to assess how strong that association is.

What is the difference between the point estimate and statistical significance in the context of relative risk or odds ratio?

The point estimate is the actual number representing the relative risk or odds ratio, while statistical significance is indicated by the p-value and/or confidence interval, showing the reliability of the point estimate.

When is the relative risk used in a study?

Relative risk is used when comparing the probability of an event occurring to all possible events considered in a study, typically in cohort studies.

How is the relative risk calculated using a 2x2 contingency table?

Relative risk is calculated by dividing the proportion of individuals who suffered the event in the exposed group by the proportion of individuals who suffered the event in the unexposed group.

What does a relative risk of 5.41 imply in the context of the secondhand smoke example?

A relative risk of 5.41 implies that the risk of developing lung cancer in the exposed group is 5.41 times higher than in the unexposed group.

What are the three interpretations of relative risk values?

A relative risk of one indicates no difference between groups, a value greater than one suggests a positive association or risk factor, and a value less than one indicates a negative association or protective effect.

Why can't relative risk be calculated from a case-control study?

Relative risk cannot be calculated from a case-control study because it compares cases that have experienced the event with controls who have not, and it does not provide the necessary data to calculate incidence or risk.

What is the difference between odds and probability, and how do they relate to odds ratio?

Odds are calculated as the probability of an event divided by the probability of the event not happening, while probability is the chance of an event occurring. The odds ratio compares the odds of an event in the exposed group to the odds in the unexposed group.

Why are odds ratios preferred over relative risk in case-control studies?

Odds ratios are preferred in case-control studies because they can be calculated without needing incidence rates, which are not available in this study design.

How do you interpret an odds ratio of 1.48 in a case-control study?

An odds ratio of 1.48 suggests that the odds of the exposed group experiencing the event (e.g., children with leukemia) are 1.48 times higher than the odds of the unexposed group.

When are relative risk and odds ratios comparable in magnitude?

Relative risk and odds ratios are comparable in magnitude when the outcome under study is rare, as their formulas yield more similar results in such cases.

Why should caution be exercised when interpreting odds ratios?

Caution is needed because odds ratios can overestimate risk when the outcome is more common, and they should not be assumed to represent the true risk ratio.

Why are odds ratios common in both case-control and cohort studies?

Odds ratios are common because they are the result of logistic regression, a widely used statistical method in medical research for both types of study designs.