Literature DB >> 23569307

Modified toxicity probability interval design: a safer and more reliable method than the 3 + 3 design for practical phase I trials.

Yuan Ji1, Sue-Jane Wang.   

Abstract

The 3 + 3 design is the most common choice among clinicians for phase I dose-escalation oncology trials. In recent reviews, more than 95% of phase I trials have been based on the 3 + 3 design. Given that it is intuitive and its implementation does not require a computer program, clinicians can conduct 3 + 3 dose escalations in practice with virtually no logistic cost, and trial protocols based on the 3 + 3 design pass institutional review board and biostatistics reviews quickly. However, the performance of the 3 + 3 design has rarely been compared with model-based designs in simulation studies with matched sample sizes. In the vast majority of statistical literature, the 3 + 3 design has been shown to be inferior in identifying true maximum-tolerated doses (MTDs), although the sample size required by the 3 + 3 design is often orders-of-magnitude smaller than model-based designs. In this article, through comparative simulation studies with matched sample sizes, we demonstrate that the 3 + 3 design has higher risks of exposing patients to toxic doses above the MTD than the modified toxicity probability interval (mTPI) design, a newly developed adaptive method. In addition, compared with the mTPI design, the 3 + 3 design does not yield higher probabilities in identifying the correct MTD, even when the sample size is matched. Given that the mTPI design is equally transparent, costless to implement with free software, and more flexible in practical situations, we highly encourage its adoption in early dose-escalation studies whenever the 3 + 3 design is also considered. We provide free software to allow direct comparisons of the 3 + 3 design with other model-based designs in simulation studies with matched sample sizes.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23569307      PMCID: PMC3641699          DOI: 10.1200/JCO.2012.45.7903

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  19 in total

1.  Statistical properties of the traditional algorithm-based designs for phase I cancer clinical trials.

Authors:  Y Lin; W J Shih
Journal:  Biostatistics       Date:  2001-06       Impact factor: 5.899

2.  A Bayesian adaptive design for multi-dose, randomized, placebo-controlled phase I/II trials.

Authors:  Fang Xie; Yuan Ji; Lothar Tremmel
Journal:  Contemp Clin Trials       Date:  2012-03-09       Impact factor: 2.226

3.  Phase I clinical and pharmacokinetic study of the Novel Raf kinase and vascular endothelial growth factor receptor inhibitor BAY 43-9006 in patients with advanced refractory solid tumors.

Authors:  Dirk Strumberg; Heike Richly; Ralf A Hilger; Norbert Schleucher; Sonke Korfee; Mitra Tewes; Markus Faghih; Erich Brendel; Dimitris Voliotis; Claus G Haase; Brian Schwartz; Ahmad Awada; Rudolf Voigtmann; Max E Scheulen; Siegfried Seeber
Journal:  J Clin Oncol       Date:  2004-12-21       Impact factor: 44.544

4.  Translation of innovative designs into phase I trials.

Authors:  André Rogatko; David Schoeneck; William Jonas; Mourad Tighiouart; Fadlo R Khuri; Alan Porter
Journal:  J Clin Oncol       Date:  2007-11-01       Impact factor: 44.544

5.  Some notable properties of the standard oncology Phase I design.

Authors:  Gregory J Hather; Howard Mackey
Journal:  J Biopharm Stat       Date:  2009       Impact factor: 1.051

6.  Design and analysis of phase I clinical trials.

Authors:  B E Storer
Journal:  Biometrics       Date:  1989-09       Impact factor: 2.571

7.  Phase I and pharmacokinetic study of ABI-007, a Cremophor-free, protein-stabilized, nanoparticle formulation of paclitaxel.

Authors:  Nuhad K Ibrahim; Neil Desai; Sewa Legha; Patrick Soon-Shiong; Richard L Theriault; Edgardo Rivera; Bita Esmaeli; Sigrid E Ring; Agop Bedikian; Gabriel N Hortobagyi; Julie A Ellerhorst
Journal:  Clin Cancer Res       Date:  2002-05       Impact factor: 12.531

8.  Some practical improvements in the continual reassessment method for phase I studies.

Authors:  S N Goodman; M L Zahurak; S Piantadosi
Journal:  Stat Med       Date:  1995-06-15       Impact factor: 2.373

9.  A comparison of two phase I trial designs.

Authors:  E L Korn; D Midthune; T T Chen; L V Rubinstein; M C Christian; R M Simon
Journal:  Stat Med       Date:  1994-09-30       Impact factor: 2.373

Review 10.  Dose escalation methods in phase I cancer clinical trials.

Authors:  Christophe Le Tourneau; J Jack Lee; Lillian L Siu
Journal:  J Natl Cancer Inst       Date:  2009-05-12       Impact factor: 13.506

View more
  54 in total

1.  Performance of toxicity probability interval based designs in contrast to the continual reassessment method.

Authors:  Bethany Jablonski Horton; Nolan A Wages; Mark R Conaway
Journal:  Stat Med       Date:  2016-07-19       Impact factor: 2.373

Review 2.  Do immune checkpoint inhibitors need new studies methodology?

Authors:  Roberto Ferrara; Sara Pilotto; Mario Caccese; Giulia Grizzi; Isabella Sperduti; Diana Giannarelli; Michele Milella; Benjamin Besse; Giampaolo Tortora; Emilio Bria
Journal:  J Thorac Dis       Date:  2018-05       Impact factor: 2.895

3.  American Society of Clinical Oncology policy statement update: the critical role of phase I trials in cancer research and treatment.

Authors:  Jeffrey S Weber; Laura A Levit; Peter C Adamson; Suanna Bruinooge; Howard A Burris; Michael A Carducci; Adam P Dicker; Mithat Gönen; Stephen M Keefe; Michael A Postow; Michael A Thompson; David M Waterhouse; Susan L Weiner; Lynn M Schuchter
Journal:  J Clin Oncol       Date:  2014-12-15       Impact factor: 44.544

4.  Bayesian Optimal Interval Design: A Simple and Well-Performing Design for Phase I Oncology Trials.

Authors:  Ying Yuan; Kenneth R Hess; Susan G Hilsenbeck; Mark R Gilbert
Journal:  Clin Cancer Res       Date:  2016-07-12       Impact factor: 12.531

Review 5.  Implementation of adaptive methods in early-phase clinical trials.

Authors:  Gina R Petroni; Nolan A Wages; Gautier Paux; Frédéric Dubois
Journal:  Stat Med       Date:  2016-02-29       Impact factor: 2.373

6.  Macrophage Exclusion after Radiation Therapy (MERT): A First in Human Phase I/II Trial using a CXCR4 Inhibitor in Glioblastoma.

Authors:  Reena P Thomas; Seema Nagpal; Michael Iv; Scott G Soltys; Sophie Bertrand; Judith S Pelpola; Robyn Ball; Jaden Yang; Vandana Sundaram; Jonathan Lavezo; Donald Born; Hannes Vogel; J Martin Brown; Lawrence D Recht
Journal:  Clin Cancer Res       Date:  2019-09-19       Impact factor: 12.531

7.  Phase Ib/II Study of Pembrolizumab and Pegylated-Interferon Alfa-2b in Advanced Melanoma.

Authors:  Diwakar Davar; Hong Wang; Joe-Marc Chauvin; Ornella Pagliano; Julien J Fourcade; Mignane Ka; Carmine Menna; Amy Rose; Cindy Sander; Amir A Borhani; Arivarasan Karunamurthy; Ahmad A Tarhini; Hussein A Tawbi; Qing Zhao; Blanca H Moreno; Scott Ebbinghaus; Nageatte Ibrahim; John M Kirkwood; Hassane M Zarour
Journal:  J Clin Oncol       Date:  2018-10-25       Impact factor: 44.544

Review 8.  Beyond maximum grade: modernising the assessment and reporting of adverse events in haematological malignancies.

Authors:  Gita Thanarajasingam; Lori M Minasian; Frederic Baron; Franco Cavalli; R Angelo De Claro; Amylou C Dueck; Tarec C El-Galaly; Neil Everest; Jan Geissler; Christian Gisselbrecht; John Gribben; Mary Horowitz; S Percy Ivy; Caron A Jacobson; Armand Keating; Paul G Kluetz; Aviva Krauss; Yok Lam Kwong; Richard F Little; Francois-Xavier Mahon; Matthew J Matasar; María-Victoria Mateos; Kristen McCullough; Robert S Miller; Mohamad Mohty; Philippe Moreau; Lindsay M Morton; Sumimasa Nagai; Simon Rule; Jeff Sloan; Pieter Sonneveld; Carrie A Thompson; Kyriaki Tzogani; Flora E van Leeuwen; Galina Velikova; Diego Villa; John R Wingard; Sophie Wintrich; John F Seymour; Thomas M Habermann
Journal:  Lancet Haematol       Date:  2018-06-18       Impact factor: 18.959

9.  Evaluation of irrational dose assignment definitions using the continual reassessment method.

Authors:  Nolan A Wages; Evan Bagley
Journal:  Clin Trials       Date:  2019-09-23       Impact factor: 2.486

10.  A Bayesian adaptive design for cancer phase I trials using a flexible range of doses.

Authors:  Mourad Tighiouart; Galen Cook-Wiens; André Rogatko
Journal:  J Biopharm Stat       Date:  2017-10-06       Impact factor: 1.051

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.