A simple approach is given for conducting closed testing in clinical trials with multiple endpoints in which group sequential monitoring is planned. The approach allows a flexible stopping time; the earliest and latest stopping times are described. The paradigm is applicable both to clinical trials with multiple endpoints and to the one-sided multiple comparison problem of several treatments versus a control. The approach leads to enhancements of previous methods and suggestions for new methods. An example of a respiratory disease trial with four endpoints is given.
This paper considers some methods for reducing the number of significance tests undertaken when analyzing and reporting results of clinical trials. Emphasis is placed on designing and analyzing clinical trials to examine a composite hypothesis concerning multiple endpoints and combining this multiple endpoint methodology with group sequential methodology. Four methods for composite hypotheses are considered: an ordinary least squares and a generalized least squares approach both due to O'Brien (1984, Biometrics 40, 1079-1087), a new modification of these, and an approximate likelihood ratio test, due to Tang, Gnecco, and Geller (1989, Biometrika 76, 577-583). These are extended for group sequential use. In particular, simulation is used to generate critical values and sequences of nominal significance levels for the approximate likelihood ratio test, which is not normally distributed. An example is given and the relative merits of the suggested approaches are discussed.
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SUMMARYA new multivariate statistic, designed to be sensitive to the alternative hypothesis that a mean vector lies in the positive orthant, rather than to all alternatives or to alternatives on a line (O'Brien, 1984), is proposed. The statistic is shown to approximate the likelihood ratio test statistic for such alternatives (Kud5, 1963; Perlman, 1969). Its null distribution is a special case of the chi-bar-squared distribution, which allows critical values to be obtained. Such a statistic may be used in two-armed clinical trials where we are interested in showing that one treatment is better than another with respect to several responses. As an example, a clinical trial is reanalyzed, with stronger conclusions than had been drawn originally.Some key words: Clinical trial design; Multiple endpoints; Multiple response; Multiplicity; Multivariate analysis; O'Brien's statistic; One-sided alternative.
D-cycloserine (DCS) has been shown to enhance memory and, in a previous trial, once-weekly DCS improved negative symptoms in schizophrenia subjects. We hypothesized that DCS combined with a cognitive remediation (CR) program would improve memory of a practiced auditory discrimination task and that gains would generalize to performance on unpracticed cognitive tasks. Stable, medicated adult schizophrenia outpatients participated in the Brain Fitness CR program 3–5 times per week for 8 weeks. Subjects were randomly assigned to once-weekly adjunctive treatment with DCS (50 mg) or placebo administered before the first session each week. Primary outcomes were performance on an auditory discrimination task, the MATRICS cognitive battery composite score and the Scale for the Assessment of Negative Symptoms (SANS) total score. 36 subjects received study drug and 32 completed the trial (average number of CR sessions = 26.1). Performance on the practiced auditory discrimination task significantly improved in the DCS group compared to the placebo group. DCS was also associated with significantly greater negative symptom improvement for subjects symptomatic at baseline (SANS score ≥20). However, improvement on the MATRICS battery was observed only in the placebo group. Considered with previous results, these findings suggest that DCS augments CR and alleviates negative symptoms in schizophrenia patients. However, further work is needed to evaluate whether CR gains achieved with DCS can generalize to other unpracticed cognitive tasks.
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