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Validation Strategy for Biomarker-Guided Precision/Personalized Medicine
Published in Wei Zhang, Fangrong Yan, Feng Chen, Shein-Chung Chow, Advanced Statistics in Regulatory Critical Clinical Initiatives, 2022
A typical example for this design comes from a US-based phase III trial testing cetuximab in addition to infusional fluorouracil, leucovorin and oxaliplatin as adjuvant therapy in metastatic colon cancer (Amado et al. 2008). While the trial has been amended to accrue patients only with KRAS–wild-type tumors, approximately 800 patients with KRAS mutant tumors have already been enrolled. The primary analysis in this study was performed at the prespecified 0.05 level in the patients with wild-type KRAS. A sample size of 1,035 patients with wild-type KRAS per arm would result in 515 total events, providing 90% power to detect an HR of 1.33 for this comparison using a two-sided log-rank test at a significance level of 0.05. If this subset analysis is statistically significant at significance level, then the efficacy of the regimen in the entire population will also be tested at 0.05 level, as this is a closed testing procedure. This comparison using all 2,910 patients will have 90% power to detect an HR of 1.27 comparing the two treatment arms, based on a total of 735 events.
A Framework for Testing Biomarker Subgroups in Confirmatory Trials
Published in Nusrat Rabbee, Biomarker Analysis in Clinical Trials with R, 2020
In cases of testing BM+, BM−, and overall populations, it is more often that we will test the hypothesis as a union–intersection test [6]. This means that we will consider a win if any of the hypothesis is rejected (or at least one is rejected). We have a closed testing procedure for , . This procedure rejects the intersection hypothesis at an adjusted alpha level and, if rejected, tests the other hypotheses at level α. This amounts to testing the most significant P value or the maximal t statistics against the adjusted α level or critical value.
Multiplicity
Published in Shein-Chung Chow, Innovative Statistics in Regulatory Science, 2019
In clinical trials involving multiple comparisons, as an alternative, the use of closed testing procedure has become very popular since introduced by Marcus et al. (1976). The closed testing procedure can be described as follows. First, form all intersections of elementary hypothesis , then test all intersections using non-multiplicity adjusted tests. An elementary hypothesis is then declared significant if all intersections that include the elementary hypothesis as a component of the intersection are significant. More specifically, suppose there is a family of hypotheses, denoted by Let where is rejected if and only if every is rejected for all assuming that an α-level test for each hypothesis is available. Marcus et al. (1976) showed that this testing procedure controls the FWER.
A Phase 2, Double-Blind, Randomized, Dose-Ranging Trial Of Reldesemtiv In Patients With ALS
Published in Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 2021
Jeremy M. Shefner, Jinsy A. Andrews, Angela Genge, Carlayne Jackson, Noah Lechtzin, Timothy M. Miller, Bettina M. Cockroft, Lisa Meng, Jenny Wei, Andrew A. Wolff, Fady I. Malik, Cynthia Bodkin, Benjamin R. Brooks, James Caress, Annie Dionne, Dominic Fee, Stephen A. Goutman, Namita A. Goyal, Orla Hardiman, Ghazala Hayat, Terry Heiman-Patterson, Daragh Heitzman, Robert D. Henderson, Wendy Johnston, Chafic Karam, Matthew C. Kiernan, Stephen J. Kolb, Lawrence Korngut, Shafeeq Ladha, Genevieve Matte, Jesus S. Mora, Merrilee Needham, Bjorn Oskarsson, Gary L. Pattee, Erik P. Pioro, Michael Pulley, Dianna Quan, Kourosh Rezania, Kerri L. Schellenberg, David Schultz, Christen Shoesmith, Zachary Simmons, Jeffrey Statland, Shumaila Sultan, Andrea Swenson, Leonard H. Van Den Berg, Tuan Vu, Steve Vucic, Michael Weiss, Ashley Whyte-Rayson, James Wymer, Lorne Zinman, Stacy A. Rudnicki
The global null hypothesis for the primary and secondary efficacy endpoints were tested in a pre-specified order (as listed above) using a closed testing procedure, and maintained the family-wise error rate at two-sided significance level of 0.05 for all hypotheses tested. No adjustment for multiplicity was made for analyses of all reldesemtiv groups pooled versus placebo, and subgroups defined by patient characteristics that were post hoc exploratory; all p values of statistical significance are nominal. An estimated 445 patients had to be randomized to provide 90% power to detect a 2.75, 5.5, and 5.5 percentage point advantage over placebo for the 150 mg bid, 300 mg bid, and 450 mg bid reldesemtiv dose groups, respectively, in change from baseline of percent predicted SVC, at the end of the double-blind period (week 12). This calculation was based on a two-sided test with α set at 0.05 and an assumed common standard deviation of 14%.
NTCP model validation method for DAHANCA patient selection of protons versus photons in head and neck cancer radiotherapy
Published in Acta Oncologica, 2019
C. R. Hansen, J. Friborg, K. Jensen, E. Samsøe, L. Johnsen, R. Zukauskaite, C. Grau, C. Maare, J. Johansen, H. Primdahl, Å. Bratland, C. A. Kristensen, M Andersen, J. G. Eriksen, J. Overgaard
When performing an external validation only part of the whole data information, i.e. data from original model development and validation data, is used. A more appealing approach is the use of combined data, since this potentially leads to a stronger and more generalizable model. However, there is a range of obstacles in this approach [19], which often does not allow for data pulling. The closed testing procedure allows for most of the prior knowledge to be maintained and hence to transfer this knowledge to the clinical setting [17]. The intercept and slope update preserve most of the prior information, while a refitting will lose the prior knowledge of the balance between predictors and thus only maintain the predictor selection knowledge. There is no attempt of selecting new predictors in the closed testing procedure, which would require parameter selection tools and both internal and external validation on its own.
A closed testing procedure for comparison between successive variances
Published in Journal of Applied Statistics, 2020
Navdeep Singh, Parminder Singh
The proposed closed testing procedure rejects the null hypothesis of a particular pair of successive population’s iff all the hypotheses containing it and the particular hypothesis are rejected. The results of the proposed test procedure for the given set of data at 6.