By Alex Dmitrienko, Ajit C. Tamhane, Frank Bretz
Important Statistical techniques for Addressing Multiplicity IssuesIncludes functional examples from fresh trials Bringing jointly major statisticians, scientists, and clinicians from the pharmaceutical undefined, academia, and regulatory enterprises, a number of checking out difficulties in Pharmaceutical information explores the swiftly growing to be quarter of a number of comparability study with an emphasis on pharmaceutical purposes. In every one bankruptcy, the professional members describe very important multiplicity difficulties encountered in pre-clinical and scientific trial settings. The booklet starts with a vast advent from a regulatory viewpoint to forms of multiplicity difficulties that usually come up in confirmatory managed scientific trials, sooner than giving an outline of the thoughts, ideas, and methods of a number of checking out. It then offers statistical tools for studying scientific dose reaction stories that evaluate numerous dose degrees with a keep watch over in addition to statistical tools for studying a number of endpoints in scientific trials. After masking gatekeeping approaches for checking out hierarchically ordered hypotheses, the publication discusses statistical techniques for the layout and research of adaptive designs and similar confirmatory speculation trying out difficulties. the ultimate bankruptcy makes a speciality of the layout of pharmacogenomic stories in accordance with demonstrated statistical ideas. It additionally describes the research of information gathered in those reports, bearing in mind the various multiplicity concerns that ensue. This quantity explains how one can remedy severe concerns in a number of checking out encountered in pre-clinical and medical trial functions. It offers the mandatory statistical method, in addition to examples and software program code to teach the right way to use the equipment in perform.
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Extra info for Multiple Testing Problems in Pharmaceutical Statistics (Chapman & Hall CRC Biostatistics Series)
However, if this treatment eﬀect is expected to be heterogeneous, such trials may miss identifying subgroups of patients which are most likely to beneﬁt by the study treatment. Composite nature of Phase III trials with respect to patient characteristics is well-recognized. Consequently, the extent of treatment eﬃcacy of an intervention can be diﬀerent in diﬀerent subgroups of patients. For example, patients with non-fatal MI and stroke are likely to respond better to a treatment if treated early than late.
In clinical applications, the objectives can be deﬁned in terms of multiple dose levels, endpoints or subgroup analyses. Most common sources of multiplicity in clinical trials are listed below: • Multiple dose-control comparisons are commonly included in doseﬁnding studies to evaluate eﬃcacy and safety properties of a treatment compared to a control. • Multiplicity is often induced by multiple criteria for assessing the eﬃ35 © 2010 by Taylor and Francis Group, LLC 36 Multiple Testing Problems in Pharmaceutical Statistics cacy proﬁle of a treatment.
04. Non-inferiority method. Deﬁne a priori an acceptable margin for “subcomposite” and test for superiority for the main composite and test for non-inferiority for the “sub-composite”, both at the same signiﬁcance level. The weighting method. In this method, computation of the treatment eﬀect estimate and the test statistic uses pre-determined α “weights” given to the component endpoints with the sum of the weights being equal to one. For example, the weights selected for the harder endpoints could be three times larger than the weights assigned to softer endpoints.
Multiple Testing Problems in Pharmaceutical Statistics (Chapman & Hall CRC Biostatistics Series) by Alex Dmitrienko, Ajit C. Tamhane, Frank Bretz