<\/span><\/h2>\nNo, a p-value is not necessary for non-inferiority trials<\/strong>. In non-inferiority trials, the primary analysis should focus on confidence interval estimates rather than p-values. Confidence intervals provide a more informative estimate of the treatment effect and its precision, allowing researchers to assess whether the new treatment is non-inferior to the active control.<\/p>\nNonetheless, many regulatory agencies and journals still require p-values to be reported alongside confidence intervals in non-inferiority trials. This requirement stems from the historical practice of using p-values for hypothesis testing. However, relying solely on p-values can be misleading and may lead to incorrect interpretations of the results.<\/p>\n
Instead of focusing on p-values, it is more appropriate to assess the confidence interval around the treatment effect estimate. The goal is to demonstrate that the lower boundary of the confidence interval is entirely above the predefined non-inferiority margin, indicating that the new treatment is not worse than the active control by a clinically relevant margin.<\/p>\n