enrolled, not 100 patients per group, but 1,000 patients per group, and observed the same event rates as before, so that there were 200 deaths in the control group (X = 200/1,000 = 0.20) and 150 deaths in the treatment group (Y = 150/1,000 = 0.15). Again, the point estimate of the RRR is 25% (1-Y/X = 1 - [0.15/0.20] x 100 = 25%). In this larger trial, you might think that the true reduction in risk is much closer to 25% and, again, you would be right; the 95% confidence interval on the RRR for this set of results is all on the positive side of zero and runs from 9% to 41%. What these examples show is that the larger the sample size of a trial, the larger the number of outcome events, and the greater our confidence that the true relative risk reduction (or any other measure of efficacy) is close to what we have observed. In the second example above, the lowest plausible value for the RRR was 9% and the highest value 41%. The point estimate -- in this case 25% -- is the one value most likely to represent the true relative risk reduction. As one considers values farther and farther from the point estimate, they become less and less consistent with the observed relative risk reduction. By the time one crosses the upper or lower boundaries of the 95% confidence interval, the values are extremely unlikely to represent the true RRR, given the