Clinical Trials

Clinical Trials: A Practical Guide ■❚❙❘Table 1. A 2 × 2 contingency table (notation) for the myocardial infarction trial.Death Treatment TotalActive drugPlaceboYes 110 (a) 165 (b) 275 (a + b)No 1935 (c) 1857 (d) 3792 (c + d)Total 2045 (n 1) 2022 (n 2) 4067 (n 1+ n 2)Proportion of deaths 5.38% (p 1= a × 100) 8.16% (p 2= b × 100) 6.76% (p = a + b × 100)n 1n 2nthe observed difference. In other words, we need to assess whether there isstatistical evidence against the null hypothesis that there is no difference betweenthe active drug and placebo in terms of mortality at 30 days.In the following sections, we describe some basic methods for reporting andanalyzing this type of data and illustrate these methods with the MI trial data. Inaddition, we discuss dealing with analyses of outcomes with more than two categories.Making statistical inferences for one treatment groupConsider that the true population proportions of patients who die on the activedrug or placebo are π 1and π 2, respectively. We aim to estimate the two populationparameters and make statistical inferences using the two respective sampleproportions, p 1and p 2. While the main focus of the analysis will be a comparisonof proportions in the two treatment groups, it might also be clinically useful toknow whether, within a treatment group, the proportion of patients who died isequal to some expected value.For example, suppose that, from other observational studies, we know that about8% of such MI patients who are not treated with the new drug will die within30 days. It may be of clinical interest to know whether the proportion of MIpatients treated with the test drug is (statistically) significantly different from 8%.The following hypotheses can be constructed to address this question:H 0: π 1= π 0= 8%vs (1)H a: π 1≠π 0219