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For: Graf AC, Posch M, Koenig F. Adaptive designs for subpopulation analysis optimizing utility functions. Biom J 2015;57:76-89. [PMID: 25399844 DOI: 10.1002/bimj.201300257] [Cited by in Crossref: 35] [Cited by in F6Publishing: 25] [Article Influence: 4.4] [Reference Citation Analysis]
Number Citing Articles
1 Chiu YD, Koenig F, Posch M, Jaki T. Design and estimation in clinical trials with subpopulation selection. Stat Med 2018;37:4335-52. [PMID: 30088280 DOI: 10.1002/sim.7925] [Cited by in Crossref: 9] [Cited by in F6Publishing: 8] [Article Influence: 2.3] [Reference Citation Analysis]
2 Su S, Li X, Zhao Y, Chan ISF. Population-Enrichment Adaptive Design Strategy for an Event-Driven Vaccine Efficacy Trial. Stat Biosci 2018;10:357-70. [DOI: 10.1007/s12561-017-9202-3] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.2] [Reference Citation Analysis]
3 Uozumi R, Hamada C. Utility-Based Interim Decision Rule Planning in Adaptive Population Selection Designs With Survival Endpoints. Statistics in Biopharmaceutical Research 2020;12:360-8. [DOI: 10.1080/19466315.2019.1689844] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]
4 Graf AC, Magirr D, Dmitrienko A, Posch M. Optimized multiple testing procedures for nested sub-populations based on a continuous biomarker. Stat Methods Med Res 2020;29:2945-57. [PMID: 32223528 DOI: 10.1177/0962280220913071] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Sugitani T, Posch M, Bretz F, Koenig F. Flexible alpha allocation strategies for confirmatory adaptive enrichment clinical trials with a prespecified subgroup. Stat Med 2018;37:3387-402. [PMID: 29945304 DOI: 10.1002/sim.7851] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
6 Johnston SE, Lipkovich I, Dmitrienko A, Zhao YD. A two-stage adaptive clinical trial design with data-driven subgroup identification at interim analysis. Pharm Stat 2022. [PMID: 35322520 DOI: 10.1002/pst.2208] [Reference Citation Analysis]
7 Ondra T, Jobjörnsson S, Beckman RA, Burman CF, König F, Stallard N, Posch M. Optimizing Trial Designs for Targeted Therapies. PLoS One 2016;11:e0163726. [PMID: 27684573 DOI: 10.1371/journal.pone.0163726] [Cited by in Crossref: 14] [Cited by in F6Publishing: 14] [Article Influence: 2.3] [Reference Citation Analysis]
8 Hee SW, Hamborg T, Day S, Madan J, Miller F, Posch M, Zohar S, Stallard N. Decision-theoretic designs for small trials and pilot studies: A review. Stat Methods Med Res 2016;25:1022-38. [PMID: 26048902 DOI: 10.1177/0962280215588245] [Cited by in Crossref: 13] [Cited by in F6Publishing: 12] [Article Influence: 1.9] [Reference Citation Analysis]
9 Hamasaki T, Bretz F, Lavange LM, Müller P, Pennello G, Pinheiro JC. Editorial: Roles of Hypothesis Testing, p -Values and Decision Making in Biopharmaceutical Research. Statistics in Biopharmaceutical Research 2021;13:1-5. [DOI: 10.1080/19466315.2021.1874803] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
10 Ballarini NM, Burnett T, Jaki T, Jennison C, König F, Posch M. Optimizing subgroup selection in two-stage adaptive enrichment and umbrella designs. Stat Med 2021;40:2939-56. [PMID: 33783020 DOI: 10.1002/sim.8949] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
11 Takahashi F, Morita S. Optimal dose selection accounting for patient subpopulations in a randomized Phase II trial to maximize the success probability of a subsequent Phase III trial. J Biopharm Stat 2018;28:870-83. [PMID: 29420118 DOI: 10.1080/10543406.2018.1428614] [Reference Citation Analysis]
12 Collignon O, Koenig F, Koch A, Hemmings RJ, Pétavy F, Saint-Raymond A, Papaluca-Amati M, Posch M. Adaptive designs in clinical trials: from scientific advice to marketing authorisation to the European Medicine Agency. Trials 2018;19:642. [PMID: 30454061 DOI: 10.1186/s13063-018-3012-x] [Cited by in Crossref: 15] [Cited by in F6Publishing: 14] [Article Influence: 3.8] [Reference Citation Analysis]
13 Krisam J, Kieser M. Optimal decision rules for biomarker-based subgroup selection for a targeted therapy in oncology. Int J Mol Sci 2015;16:10354-75. [PMID: 25961947 DOI: 10.3390/ijms160510354] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 1.1] [Reference Citation Analysis]
14 Ondra T, Dmitrienko A, Friede T, Graf A, Miller F, Stallard N, Posch M. Methods for identification and confirmation of targeted subgroups in clinical trials: A systematic review. J Biopharm Stat 2016;26:99-119. [PMID: 26378339 DOI: 10.1080/10543406.2015.1092034] [Cited by in Crossref: 71] [Cited by in F6Publishing: 55] [Article Influence: 11.8] [Reference Citation Analysis]
15 Placzek M, Friede T. A conditional error function approach for adaptive enrichment designs with continuous endpoints. Stat Med 2019;38:3105-22. [PMID: 31066093 DOI: 10.1002/sim.8154] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
16 Trusheim MR, Shrier AA, Antonijevic Z, Beckman RA, Campbell RK, Chen C, Flaherty KT, Loewy J, Lacombe D, Madhavan S, Selker HP, Esserman LJ. PIPELINEs: Creating Comparable Clinical Knowledge Efficiently by Linking Trial Platforms. Clin Pharmacol Ther 2016;100:713-29. [PMID: 27643536 DOI: 10.1002/cpt.514] [Cited by in Crossref: 23] [Cited by in F6Publishing: 17] [Article Influence: 3.8] [Reference Citation Analysis]
17 Wilhelm-Benartzi CS, Mt-Isa S, Fiorentino F, Brown R, Ashby D. Challenges and methodology in the incorporation of biomarkers in cancer clinical trials. Crit Rev Oncol Hematol 2017;110:49-61. [PMID: 28109405 DOI: 10.1016/j.critrevonc.2016.12.008] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
18 Xu Y, Müller P, Tsimberidou AM, Berry D. A nonparametric Bayesian basket trial design. Biom J 2019;61:1160-74. [PMID: 29808479 DOI: 10.1002/bimj.201700162] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 0.8] [Reference Citation Analysis]
19 Bauer P, Bretz F, Dragalin V, König F, Wassmer G. Twenty-five years of confirmatory adaptive designs: opportunities and pitfalls. Stat Med 2016;35:325-47. [PMID: 25778935 DOI: 10.1002/sim.6472] [Cited by in Crossref: 105] [Cited by in F6Publishing: 84] [Article Influence: 15.0] [Reference Citation Analysis]
20 Dmitrienko A, Paux G, Pulkstenis E, Zhang J. Tradeoff-based optimization criteria in clinical trials with multiple objectives and adaptive designs. J Biopharm Stat 2016;26:120-40. [PMID: 26391238 DOI: 10.1080/10543406.2015.1092032] [Cited by in Crossref: 5] [Article Influence: 0.7] [Reference Citation Analysis]
21 Simon N, Simon R. Using Bayesian modeling in frequentist adaptive enrichment designs. Biostatistics 2018;19:27-41. [PMID: 28520893 DOI: 10.1093/biostatistics/kxw054] [Cited by in Crossref: 15] [Cited by in F6Publishing: 9] [Article Influence: 5.0] [Reference Citation Analysis]
22 Wang Z, Wang F, Wang C, Zhang J, Wang H, Shi L, Tang Z, Rosner GL. A Bayesian Decision-Theoretic Design for Simultaneous Biomarker-Based Subgroup Selection and Efficacy Evaluation. Statistics in Biopharmaceutical Research. [DOI: 10.1080/19466315.2021.1873843] [Reference Citation Analysis]
23 Ondra T, Jobjörnsson S, Beckman RA, Burman CF, König F, Stallard N, Posch M. Optimized adaptive enrichment designs. Stat Methods Med Res 2019;28:2096-111. [PMID: 29254436 DOI: 10.1177/0962280217747312] [Cited by in Crossref: 16] [Cited by in F6Publishing: 11] [Article Influence: 3.2] [Reference Citation Analysis]
24 Miller F, Zohar S, Stallard N, Madan J, Posch M, Hee SW, Pearce M, Vågerö M, Day S. Approaches to sample size calculation for clinical trials in rare diseases. Pharm Stat 2018;17:214-30. [PMID: 29322632 DOI: 10.1002/pst.1848] [Cited by in Crossref: 12] [Cited by in F6Publishing: 9] [Article Influence: 3.0] [Reference Citation Analysis]
25 Jörgens S, Wassmer G, König F, Posch M. Nested combination tests with a time-to-event endpoint using a short-term endpoint for design adaptations. Pharm Stat 2019;18:329-50. [PMID: 30652401 DOI: 10.1002/pst.1926] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
26 Takazawa A, Morita S. Optimal Decision Criteria for the Study Design and Sample Size of a Biomarker-Driven Phase III Trial. Ther Innov Regul Sci 2020;54:1018-34. [PMID: 31989540 DOI: 10.1007/s43441-020-00119-1] [Reference Citation Analysis]
27 Rosenblum M, Fang EX, Liu H. Optimal, two-stage, adaptive enrichment designs for randomized trials, using sparse linear programming. J R Stat Soc B 2020;82:749-72. [DOI: 10.1111/rssb.12366] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
28 Renfro LA, Mallick H, An MW, Sargent DJ, Mandrekar SJ. Clinical trial designs incorporating predictive biomarkers. Cancer Treat Rev 2016;43:74-82. [PMID: 26827695 DOI: 10.1016/j.ctrv.2015.12.008] [Cited by in Crossref: 39] [Cited by in F6Publishing: 32] [Article Influence: 6.5] [Reference Citation Analysis]
29 Friede T, Posch M, Zohar S, Alberti C, Benda N, Comets E, Day S, Dmitrienko A, Graf A, Günhan BK, Hee SW, Lentz F, Madan J, Miller F, Ondra T, Pearce M, Röver C, Toumazi A, Unkel S, Ursino M, Wassmer G, Stallard N. Recent advances in methodology for clinical trials in small populations: the InSPiRe project. Orphanet J Rare Dis 2018;13:186. [PMID: 30359266 DOI: 10.1186/s13023-018-0919-y] [Cited by in Crossref: 17] [Cited by in F6Publishing: 16] [Article Influence: 4.3] [Reference Citation Analysis]
30 Morita S, Müller P, Abe H. A semiparametric Bayesian approach to population finding with time-to-event and toxicity data in a randomized clinical trial. Biometrics 2021;77:634-48. [PMID: 32339262 DOI: 10.1111/biom.13289] [Reference Citation Analysis]
31 Vivot A, Li J, Zeitoun JD, Mourah S, Crequit P, Ravaud P, Porcher R. Pharmacogenomic biomarkers as inclusion criteria in clinical trials of oncology-targeted drugs: a mapping of ClinicalTrials.gov. Genet Med 2016;18:796-805. [PMID: 26681315 DOI: 10.1038/gim.2015.165] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 0.7] [Reference Citation Analysis]