Common measures of clinical significance are used to evaluate the practical importance or relevance of research findings in clinical practice or real-world settings. These measures focus on assessing the magnitude of the effect, its impact on patient outcomes, and its relevance to healthcare decision-making. Here are some common measures of clinical significance:

1. Effect Size:
   • Effect size quantifies the magnitude of the observed effect or difference between groups. Common effect size measures include Cohen’s d for means comparison, odds ratio for binary outcomes, and correlation coefficient for association between variables. A larger effect size indicates a more substantial or clinically meaningful effect.
2. Risk Difference (Absolute Risk Reduction or Increase):
   • Risk difference measures the absolute difference in risk or probability of an event occurring between two groups (e.g., treatment group vs. control group). It provides information about the absolute impact of an intervention on reducing or increasing the risk of an outcome.
3. Number Needed to Treat (NNT) or Number Needed to Harm (NNH):
   • NNT represents the number of patients who need to be treated with a specific intervention to prevent one additional adverse outcome or to achieve one additional positive outcome compared to a control group. Similarly, NNH represents the number of patients who need to be exposed to a risk factor for one additional adverse outcome to occur compared to those not exposed.
4. Relative Risk (RR) or Relative Risk Reduction (RRR):
   • Relative risk compares the risk of an event occurring in one group (e.g., treatment group) to the risk in another group (e.g., control group). Relative risk reduction calculates the proportional reduction in risk associated with an intervention compared to a control group.
5. Hazard Ratio (HR):
   • Hazard ratio is commonly used in survival analysis to compare the risk of an event (e.g., death) between two groups over time. It represents the ratio of the hazard rates (instantaneous failure rates) in the treatment group to the control group.
6. Quality of Life Measures:
   • Quality of life measures assess the impact of an intervention or treatment on patients’ quality of life, well-being, and functional status. These measures include validated questionnaires and scales that capture physical, emotional, social, and functional aspects of health-related quality of life.
7. Cost-effectiveness Measures:
   • Cost-effectiveness measures evaluate the economic implications of healthcare interventions by comparing the costs and outcomes associated with different treatment strategies. These measures assess the value of interventions in terms of their cost per unit of health benefit gained.

These measures of clinical significance provide important insights into the practical implications of research findings and guide healthcare decision-making by considering both the effectiveness and relevance of interventions in clinical practice. These measures should be included when reporting analysis results and used to broaden the interpretation of study results.