The article discusses how researchers adjust the sample size needed for clinical trials to account for multiple tests being conducted. By using a simple strategy that adjusts the significance level for multiple primary measures, the researchers ensure that the study maintains enough statistical power. They found that as the number of primary measures increased, the required sample size also increased, with a 20% increase for two measures and a 30% increase for three measures. This adjustment is important in designing clinical trial protocols to prevent false-positive results while still having enough statistical power to detect real effects.