Download e-book for iPad: Advances in Clinical Trial Biostatistics by Nancy L. Geller

By Nancy L. Geller

ISBN-10: 0824790324

ISBN-13: 9780824790325

From facets of early trials to advanced modeling difficulties, Advances in scientific Trial Biostatistics summarizes present methodologies utilized in the layout and research of medical trials. Its chapters, contributed by means of the world over well known methodologists skilled in scientific trials, deal with issues that come with Bayesian equipment for section I medical 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 review, and statistical matters rising from scientific trials in HIV infection.

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Journal of Clinical Oncology 15:853–859. , Zacks, S. (1998). Cancer phase I clinical trials: Efficient dose escalation with overdose control. Statistics in Medicine 17:1103–1120. Babb, J. , Rogatko, A. (2001). Patient specific dosing in a cancer phase I clinical trial. Statistics in Medicine 20:2079–2090. , Larntz, K. (1989). Optimal Bayesian design applied to logistic regression experiments. Journal of Planning and Inference 21:191–208. Chevret, S. (1993). The continual reassessment method in cancer phase I clinical trials: A simulation study.

Thus, after k patients have been observed, the posterior expected loss associated with dose x 2 S is Z ELk ðxÞ ¼ Lðx; uÞ C kðuÞdu H and the next patient would receive the dose xkþ1 ¼ arg minfELk ðxÞg: x2S Copyright n 2004 by Marcel Dekker, Inc. All Rights Reserved. Bayesian Methods for Cancer Phase I Clinical Trials 19 For example, the dose for each patient might be chosen to minimize the posterior expected loss with respect to the loss function L(x, N) = d{u, p(x, N)} or L(x, N) = m(x, g) for some choice of metrics d and m defined on the unit square and S Â G, respectively.

Candidate estimators would include the mean, median, and mode of the marginal posterior distribution of the MTD. Consideration should be given to asymmetric loss functions since under- and overestimation of the MTD would have very different consequences. To reflect the often substantial difference in the characteristics of the phase I and II patient populations, estimation of the MTD can be based on a different prior distribution or loss function than was used to design the phase I trial (Tsutakawa, 1972, 1975).

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Advances in Clinical Trial Biostatistics by Nancy L. Geller

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