But if one of the treatments in the two arm trial looks to be inferior on any measure you care about, then you would not want to take a risk of being randomized to that treatment in the current three-arm trial. An interesting dilemma for the researchers will be what to do if the two arm trial reaches their statistical criteria for declaring one of the treatments inferior before the three arm trial stops accepting patients. Presumably they'd have to stop accruing to the inferior arm at that point. In the two arm trial, the response rate is higher for high dose IL-2, and the number of complete and durable responses is higher as well. The question is whether this is just due to random chance, or whether the high dose treatment is really more effective.
Statistical tests are a way to gauge how likely it is that the treatments are really different.
The logic is to assume that the treatments are really the same and then, using a statistical test appropriate for the situation, to determine the probability that the results would be at least as different as they are, given that assumption. If the differences between the groups are not statistically significant that absolutely does not mean there is no difference between them. It may only mean there is not enough data to be able to tell that the observed difference is not due to chance. My Analysis of the Two Arm Trial For outcomes which can be categorized like responded versus didn't respond, the typical statistical test is called the Chi-Squared test . For 2x2 tables there is another test called the Fisher Exact Test which is valid even if some of the numbers are small, and that's what I used.