What method is used to convey survival probabilities in patients after an intervention?

The Kaplan-Meier survival curve is a statistical method used to estimate the survival probabilities of patients over time after an intervention. This method is particularly beneficial in clinical research for analyzing survival data because it can handle censored data, which occurs when some patients may drop out of the study or when they have not yet experienced the event of interest (such as death or disease recurrence) by the end of the study period.

By plotting the survival probability on the y-axis against time on the x-axis, the Kaplan-Meier curve visually represents the likelihood of survival at various time points, allowing for a clear comparison of the effectiveness of different interventions. This graphical representation makes it easier for clinicians and researchers to interpret the data regarding patient survival outcomes.

While regression analysis may also be used to assess survival, it does not provide the same clear, visual representation of survival probabilities over time. Normal distribution refers to a specific statistical distribution, primarily applicable in scenarios involving continuous data, and does not specifically relate to survival analysis. A randomized control trial is a study design rather than a method of conveying survival probabilities, as it focuses on comparing the outcomes of different interventions in a controlled setting. Thus, the Kaplan-Meier survival curve is the most appropriate method for conveying survival probabilities in patients following