Advances in Clinical Trial Biostatistics by Nancy L. Geller

By Nancy L. Geller

From facets of early trials to advanced modeling difficulties, Advances in scientific Trial Biostatistics summarizes present methodologies utilized in the layout and research of scientific trials. Its chapters, contributed via across the world popular methodologists skilled in scientific trials, deal with themes that come with Bayesian equipment for part I scientific trials, adaptive two-stage scientific trials, and the layout and research of cluster randomization trials, trials with a number of endpoints, and healing equivalence trials. different discussions discover Bayesian reporting, tools incorporating compliance in remedy overview, and statistical concerns rising from scientific trials in HIV infection.

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In such contexts, independent phase I trials can be designed for each patient group according to the methods outlined above. Alternatively, a single trial might be conducted with relevant patient information directly incorporated into the trial design. Thus, the dose-toxicity relationship is modeled as a function of patient attributes represented by the vector c of covariate measurements. For exposition, we consider the case where a single covariate observation c is obtained for each patient. The relationship between dose and response might then be characterized as pðx; cÞ ¼ expða þ hx þ ycÞ 1 þ expða þ hx þ ycÞ ð13Þ where pðx; cÞ u Prob½DLTjDose ¼ x; Covariate ¼ cŠ: The overall design of the trial will depend in part on whether or not the observation c can be obtained for each patient prior to the onset of treatment.

This can be accomplished by administering to each patient the dose level corresponding to the a-fractile of the marginal posterior cumulative distribution function (CDF) of the Copyright n 2004 by Marcel Dekker, Inc. All Rights Reserved. Bayesian Methods for Cancer Phase I Clinical Trials 21 MTD. Specifically, after k patients have been observed, the dose for the next patient accrued to the trial is xkþ1 ¼ FkÀ1 ðaÞ ð11Þ where Z xZ Fk ðxÞ ¼ 0 Y X k ðg; NÞ dN dg ð12Þ is the marginal posterior CDF of the MTD given Dk.

Instead of minimizing the posterior expected loss, dose levels can be chosen so as to minimize the loss function after substituting an estimate for N. Consequently, given the data from k patients, one might estimate N as Nˆ k and administer to the next patient the dose xkþ1 ¼ arg minfLðx; Nˆ k Þg: xeS In the remainder of this section we describe various loss functions that have been discussed in the literature concerning cancer phase I clinical trials. Since the primary statistical aim of a phase I clinical trial is to determine the MTD, designs have been presented which seek to maximize the efficiency with which the MTD is estimated.

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