Statistics in medicine
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Traditional designs for phase I clinical trials assign the same dose to patients in the same cohort. In this paper, we present a new class of designs for cancer phase I trials which initially rapidly escalate by allowing multiple doses (usually 3) to be assigned to each cohort of patients. ⋯ Three designs (slow, moderate and fast) are derived based on different dose-escalation restrictions. Simulation results show that moderate and fast LMH-CRM combine the advantages of the CRM with one patient per cohort and three patients per cohort: it accurately estimates the MTD; controls overall toxicity rates; and is time efficient.
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Statistics in medicine · May 2008
Adaptive dose finding based on t-statistic for dose-response trials.
The goals of phase II dose-response studies are to prove that the treatment is effective and to choose the dose for further development. Randomized designs with equal allocation to either a high dose and placebo or to each of several doses and placebo are typically used. ⋯ We propose an adaptive design for dose-response trials that concentrates the allocation of subjects in one or more areas of interest, for example, near a minimum clinically important effect level, or near some maximal effect level, and also allows for the possibility to stop the trial early if needed. The proposed adaptive design yields higher power to detect a dose-response relationship, higher power in comparison with placebo, and selects the correct dose more frequently compared with a corresponding randomized design with equal allocation to doses.
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We consider evaluation and comparison of the diagnostic accuracy of biomarkers with continuous test outcomes, possibly correlated due to repeated measurements. We develop nonparametric group sequential testing procedures to evaluate and compare the area of biomarkers under their receiver operating characteristic curves, with either independent or paired test outcomes. These procedures rely on the construction of a two-dimensional statistic of Whitehead (Statist. Med. 1999; 18:2271-2286) so that design methods based on Brownian motion can be applied.
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Statistics in medicine · Feb 2008
Sample size calculation for the Wilcoxon-Mann-Whitney test adjusting for ties.
In this paper we study sample size calculation methods for the asymptotic Wilcoxon-Mann-Whitney test for data with or without ties. The existing methods are applicable either to data with ties or to data without ties but not to both cases. ⋯ In addition, the new method can be applied to both data with or without ties. Simulations have demonstrated that the new sample size formula performs very well as the corresponding actual powers are close to the nominal powers.
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Statistics in medicine · Dec 2007
The analysis of continuous outcomes in multi-centre trials with small centre sizes.
The standard analysis of clinical trials stratified by centre is to include centres as fixed effects, but if many centres contribute small numbers of patients, this approach results in a loss of power. Assuming no treatment by centre interaction, we used simulation to examine power and coverage of confidence intervals from three approaches to the analysis of continuous outcome in multi-centre trials: ignoring centres, including centres as fixed effects, and including them as random effects. The simulation incorporated eight sizes of centre effects; randomization in blocks of size 2 or 4; and two sample sizes, namely 100 and 200 patients per treatment arm in a parallel groups design. ⋯ Fixed effects analysis was less powerful, particularly when centre effects were small. Incorporating block randomization with larger block size increased non-orthogonality in the design, contributing to loss of power. Where centre effects are small and recruitment in many centres is low, the approaches of ignoring centres or incorporating them as random effects have better performance than the traditional fixed effects analysis.