What ensures a statistically significant difference between groups in a clinical trial when the hazard ratio (HR) is less than 1?

What ensures a statistically significant difference between groups in a clinical trial when the hazard ratio (HR) is less than 1?

• A. p-value less than 0.05
• B. p-value less than 0.0001
• C. p-value greater than 0.05
• D. p-value equal to 0.05

Answer: (A)

In clinical trials, a statistically significant difference between groups is often determined by the p-value, which indicates the probability that the observed results could have occurred by chance under the null hypothesis. A p-value less than 0.05 is commonly accepted as the threshold for statistical significance. When a hazard ratio (HR) is less than 1, it suggests that there is a reduced hazard (or risk) of the event occurring in the treatment group compared to the control group. However, to confirm that this difference is statistically significant, the accompanying p-value must also be low. Using a p-value threshold of less than 0.05 means that there’s less than a 5% likelihood that the observed difference is due to random variation rather than a true effect of the treatment. This provides a clear indication that the treatment is likely having a real impact on the outcome, thereby supporting the hypothesis that the treatment is beneficial compared to the control. While the other options reflect varying levels of statistical significance (like p-values less than 0.0001 being even more stringent), they are not required to establish statistical significance when the common cut-off of 0.05 suffices. A p-value greater than 0.05 indicates a lack of statistical significance and

In clinical trials, a statistically significant difference between groups is often determined by the p-value, which indicates the probability that the observed results could have occurred by chance under the null hypothesis. A p-value less than 0.05 is commonly accepted as the threshold for statistical significance. When a hazard ratio (HR) is less than 1, it suggests that there is a reduced hazard (or risk) of the event occurring in the treatment group compared to the control group. However, to confirm that this difference is statistically significant, the accompanying p-value must also be low.

Using a p-value threshold of less than 0.05 means that there’s less than a 5% likelihood that the observed difference is due to random variation rather than a true effect of the treatment. This provides a clear indication that the treatment is likely having a real impact on the outcome, thereby supporting the hypothesis that the treatment is beneficial compared to the control.

While the other options reflect varying levels of statistical significance (like p-values less than 0.0001 being even more stringent), they are not required to establish statistical significance when the common cut-off of 0.05 suffices. A p-value greater than 0.05 indicates a lack of statistical significance and