Distribution of the Probability of Survival Is a Strategic Issue for Randomized Trials in Critically Ill Patients

Background: Many randomized clinical trials in trauma have failed to demonstrate a significant improvement in survival rate. Using a trauma patient database, we simulated what could happen in a trial designed to improve survival rate in this setting.

Methods: The predicted probability of survival was assessed using the TRISS methodology in 350 severely injured trauma patients. Using this probability of survival, the authors simulated the effects of a drug that may increase the probability of survival by 10-50% and calculated the number of patients to be included in a triad, assuming [alpha] = 0.05 and [beta] = 0.10 by using the percentage of survivors or the individual probability of survival. Other distributions (Gaussian, J shape, uniform) of the probability of survival were also simulated and tested.

Results: The distribution of the probability of survival was bimodal with two peaks (< 0.10 and > 0.90). There were major discrepancies between the number of patients to be included when considering the percentage of survivors or the individual value of the probability of survival: 63,202 versus 2,848 if the drug increases the probability of survival by 20%. This discrepancy also occurred in other types of distribution (uniform, J shape) but to a lesser degree, whereas it was very limited in a Gaussian distribution.