Phenomenon that data will continue to accumulate after it is decided to stop a trial ( Whitehead, 1992). Overrunning consists of extra data, collected by investigators while awaiting results of the interim analysis (IA). Overrunning is the
Group sequential design is the most common type of adaptive design as described in the FDA guidance " adaptive designs for clinical trials".Īs mentioned in an early post " overrunning issues in adaptive design clinical trials", one of the issues with interim analyses in group sequential design is the overrunning issue. A study with formal interim analyses to look at the comparative efficacy is called 'group sequential design' even though the 'group sequential design' may not be formally used in the study protocol. It is pretty common these days that clinical trials (especially the late phase, adequate, and well-controlled studies) employ interim analyses to determine if the efficacy results are too good so that the study should be stopped early for overwhelming efficacy, or if the efficacy results are not good so that the study should be stopped early for futility, or both. How the 228 subjects in the concordance ‘No Change’ category are split has no impact on the p-value calculation. Matter with our calculation of chi-square statistics and therefore the p-value.įor the data highlighted in yellow, McNemar’s test canīe performed using the SAS codes like this ( weight statement indicates count variable is the frequency of the observation and agree option requests McNemar's test). How the # of subjects with the ‘No Change’ is split doesn’t Will only contribute to the sample size (therefore the degree of freedom), not have an impact on the p-value. The concordant cells (in our case, the # of no change) Are they more subjects with improvement than deterioration?Īssuming that change from category 1 to 0 is 'Improved' and change from category 0 to 1 is 'Deteriorated', the table above can be converted into a 2 × 2 table:įor McNemar’s test, only the numbers in the diagonal discordantĬells (in our case, the # of improved and the # of deteriorated) are relevant. At Week 12, there are more subjects in the 'Improved' category than in the 'Deteriorated' category even though the majority of subjects are in the 'No Change' category.
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