Common outcome scales in acute stroke trials are ordered categorical or pseudocontinuous in structure but most have been analyzed as binary measures. The use of fixed dichotomous analysis of ordered categorical outcomes after stroke (such as the modified Rankin Scale) is rarely the most statistically efficient approach and usually requires a larger sample size to demonstrate efficacy than other approaches. Preferred statistical approaches include sliding dichotomous, ordinal, or continuous analyses. Because there is no best approach that will work for all acute stroke trials, it is vital that studies are designed with a full understanding of the type of patients to be enrolled (in particular their case mix, which will be critically dependent on their age and severity), the potential mechanism by which the intervention works (ie, will it tend to move all patients somewhat, or some patients a lot, and is a common hazard present), a realistic assessment of the likely effect size, and therefore the necessary sample size, and an understanding of what the intervention will cost if implemented in clinical practice. If these approaches are followed, then the risk of missing useful treatment effects for acute stroke will diminish.

/pdf/statistical-analysis-of-the-primary-outcome-in-acute-stroke-477wmzyjfk.pdf

Statistical Analysis of the Primary Outcome in Acute Stroke Trials

Two-stage designs offer substantial advantages for early phase II studies. The interim analysis following the first stage allows the study to be stopped for futility, or more positively, it might lead to early progression to the trials needed for late phase II and phase III. If the study is to continue to its second stage, then there is an opportunity for a revision of the total sample size. Two-stage designs have been implemented widely in oncology studies in which there is a single treatment arm and patient responses are binary. In this paper the case of two-arm comparative studies in which responses are quantitative is considered. This setting is common in therapeutic areas other than oncology. It will be assumed that observations are normally distributed, but that there is some doubt concerning their standard deviation, motivating the need for sample size review. The work reported has been motivated by a study in diabetic neuropathic pain, and the development of the design for that trial is described in detail.

Evaluation of a sequential global test of improved recovery following stroke as applied to the ICTUS trial of citicoline.

There is growing interest, especially for trials in stroke, in combining multiple endpoints in a single clinical evaluation of an experimental treatment. The endpoints might be repeated evaluations of the same characteristic or alternative measures of progress on different scales. Often they will be binary or ordinal, and those are the cases studied here. In this paper we take a direct approach to combining the univariate score statistics for comparing treatments with respect to each endpoint. The correlations between the score statistics are derived and used to allow a valid combined score test to be applied. A sample size formula is deduced and application in sequential designs is discussed. The method is compared with an alternative approach based on generalized estimating equations in an illustrative analysis and replicated simulations, and the advantages and disadvantages of the two approaches are discussed.

A combined score test for binary and ordinal endpoints from clinical trials.

A sequential trial design is an alternative for the classical trial design with a fixed sample size, that permits stopping a trial as soon as enough evidence for a treatment effect, or a lack thereof, is obtained. This study aimed to determine the difference in efficiency of time and patient number between a classical trial design and a sequential trial design. In this study we re‐analysed a previously published classically designed clinical trial according to a sequential trial design. We subsequently determined the difference in total running time and patient number. We found that the sequential analysis offered a gain in time of 38%. We conclude that the sequential trial design may in certain situations be superior to the classical design.

Alternative trial design in amyotrophic lateral sclerosis saves time and patients.

54 The use of a sample size review in a head injury trial with ordered categorical responses

While planning the GAIN International Study of gavestinel in acute stroke, a sequential triangular test was proposed but not implemented. Before the trial commenced it was agreed to evaluate the sequential design retrospectively to evaluate the differences in the resulting analyses, trial durations and sample sizes in order to assess the potential of sequential procedures for future stroke trials. This paper presents four sequential reconstructions of the GAIN study made under various scenarios. For the data as observed, the sequential design would have reduced the trial sample size by 234 patients and shortened its duration by 3 or 4 months. Had the study not achieved a recruitment rate that far exceeded expectation, the advantages of the sequential design would have been much greater. Sequential designs appear to be an attractive option for trials in stroke.

How a Sequential Design Would Have Affected the GAIN International Study of Gavestinel in Stroke

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How a Sequential Design Would Have Affected the GAIN International Study of Gavestinel in Stroke