Literature DB >> 26960536

The performance of model-based versus rule-based phase I clinical trials in oncology : A quantitative comparison of the performance of model-based versus rule-based phase I trials with molecularly targeted anticancer drugs over the last 2 years.

E M J van Brummelen1, A D R Huitema2, E van Werkhoven3, J H Beijnen2,4, J H M Schellens5,6.   

Abstract

Phase I studies with anticancer drugs are used to evaluate safety and tolerability and to choose a recommended phase II dose (RP2D). Traditionally, phase I trial designs are rule-based, but for several years there is a trend towards model-based designs. Simulations have shown that model-based designs perform better, faster and are safer to establish the RP2D than rule-based designs. However, the superiority of model-based designs has never been confirmed based on true trial performance in practice. To aid evidence-based decisions for designing phase I trials, we compared publications of model-based and rule-based phase I trials in oncology. We reviewed 172 trials that have been published in the last 2 years and assessed the following operating characteristics: efficiency (trial duration, population size, dose-levels), patient safety (dose-limiting toxicities (DLTs)) and treatment optimality (percentage of patients treated below and at or above the recommended phase 2 dose). Our results showed a non-significant but clinically relevant difference in trial duration. Model-based trials needed 10 months less than rule-based trials (26 versus 36 months; p = 0.25). Additionally, fewer patients were treated at dose-levels below the RP2D (31 % versus 40 %; p = 0.73) while safety was preserved (13 % DLTs versus 14 % DLTs). In this review, we provide evidence to encourage the use of model-based designs for future phase I studies, based on a median of 10 months of time gain, acceptable toxicity rates and minimization of suboptimal treatment.

Entities:  

Keywords:  Clinical trial design; Dose-escalation trials; Model-based trials; Rule-based trials; Trial duration; Trial performance

Mesh:

Substances:

Year:  2016        PMID: 26960536     DOI: 10.1007/s10928-016-9466-0

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  11 in total

1.  Phase I clinical trial design in cancer drug development.

Authors:  E A Eisenhauer; P J O'Dwyer; M Christian; J S Humphrey
Journal:  J Clin Oncol       Date:  2000-02       Impact factor: 44.544

Review 2.  Choice of designs and doses for early phase trials.

Authors:  Yinghui Zhou
Journal:  Fundam Clin Pharmacol       Date:  2004-06       Impact factor: 2.748

3.  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

4.  Dose-finding trial designs for combination therapies in oncology.

Authors:  Sumithra J Mandrekar
Journal:  J Clin Oncol       Date:  2013-12-09       Impact factor: 44.544

Review 5.  Adaptive dose-finding studies: a review of model-guided phase I clinical trials.

Authors:  Alexia Iasonos; John O'Quigley
Journal:  J Clin Oncol       Date:  2014-06-30       Impact factor: 44.544

6.  Continual reassessment method: a practical design for phase 1 clinical trials in cancer.

Authors:  J O'Quigley; M Pepe; L Fisher
Journal:  Biometrics       Date:  1990-03       Impact factor: 2.571

7.  First-in-human phase I dose-escalation study of the HSP90 inhibitor AUY922 in patients with advanced solid tumors.

Authors:  Cristiana Sessa; Geoffrey I Shapiro; Kapil N Bhalla; Carolyn Britten; Karen S Jacks; Monica Mita; Vali Papadimitrakopoulou; Tim Pluard; Thomas A Samuel; Mikhail Akimov; Cornelia Quadt; Cristina Fernandez-Ibarra; Hong Lu; Stuart Bailey; Sandra Chica; Udai Banerji
Journal:  Clin Cancer Res       Date:  2013-06-11       Impact factor: 12.531

Review 8.  Adaptive designs for dual-agent phase I dose-escalation studies.

Authors:  Jennifer A Harrington; Graham M Wheeler; Michael J Sweeting; Adrian P Mander; Duncan I Jodrell
Journal:  Nat Rev Clin Oncol       Date:  2013-03-19       Impact factor: 66.675

9.  Efficiency of new dose escalation designs in dose-finding phase I trials of molecularly targeted agents.

Authors:  Christophe Le Tourneau; Hui K Gan; Albiruni R A Razak; Xavier Paoletti
Journal:  PLoS One       Date:  2012-12-12       Impact factor: 3.240

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

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  16 in total

Review 1.  Individualized dosing of oral targeted therapies in oncology is crucial in the era of precision medicine.

Authors:  Stefanie L Groenland; Ron H J Mathijssen; Jos H Beijnen; Alwin D R Huitema; Neeltje Steeghs
Journal:  Eur J Clin Pharmacol       Date:  2019-06-07       Impact factor: 2.953

2.  Model-Based Adaptive Optimal Design (MBAOD) Improves Combination Dose Finding Designs: an Example in Oncology.

Authors:  Philippe B Pierrillas; Sylvain Fouliard; Marylore Chenel; Andrew C Hooker; Lena E Friberg; Mats O Karlsson
Journal:  AAPS J       Date:  2018-03-07       Impact factor: 4.009

3.  Keyboard: A Novel Bayesian Toxicity Probability Interval Design for Phase I Clinical Trials.

Authors:  Fangrong Yan; Sumithra J Mandrekar; Ying Yuan
Journal:  Clin Cancer Res       Date:  2017-05-25       Impact factor: 12.531

4.  Precision Dosing of Targeted Therapies Is Ready for Prime Time.

Authors:  Neeltje Steeghs; Alwin D R Huitema; Stefanie L Groenland; Remy B Verheijen; Markus Joerger; Ron H J Mathijssen; Alex Sparreboom; Jos H Beijnen; Jan H Beumer
Journal:  Clin Cancer Res       Date:  2021-09-21       Impact factor: 12.531

5.  Proportion of Patients in Phase I Oncology Trials Receiving Treatments That Are Ultimately Approved.

Authors:  Sean X Zhang; Dean Fergusson; Jonathan Kimmelman
Journal:  J Natl Cancer Inst       Date:  2020-09-01       Impact factor: 13.506

Review 6.  Embracing model-based designs for dose-finding trials.

Authors:  Sharon B Love; Sarah Brown; Christopher J Weir; Chris Harbron; Christina Yap; Birgit Gaschler-Markefski; James Matcham; Louise Caffrey; Christopher McKevitt; Sally Clive; Charlie Craddock; James Spicer; Victoria Cornelius
Journal:  Br J Cancer       Date:  2017-06-29       Impact factor: 7.640

7.  Challenges in implementing model-based phase I designs in a grant-funded clinical trials unit.

Authors:  Eleni Frangou; Jane Holmes; Sharon Love; Naomi McGregor; Maria Hawkins
Journal:  Trials       Date:  2017-12-28       Impact factor: 2.279

8.  Designing and evaluating dose-escalation studies made easy: The MoDEsT web app.

Authors:  Philip Pallmann; Fang Wan; Adrian P Mander; Graham M Wheeler; Christina Yap; Sally Clive; Lisa V Hampson; Thomas Jaki
Journal:  Clin Trials       Date:  2019-12-19       Impact factor: 2.486

9.  Comparison between continuous and discrete doses for model based designs in cancer dose finding.

Authors:  Márcio Augusto Diniz; Mourad Tighiouart; André Rogatko
Journal:  PLoS One       Date:  2019-01-09       Impact factor: 3.240

10.  Would the Recommended Dose Have Been Different Using Novel Dose-Finding Designs? Comparing Dose-Finding Designs in Published Trials.

Authors:  Rebecca B Silva; Christina Yap; Richard Carvajal; Shing M Lee
Journal:  JCO Precis Oncol       Date:  2021-06-15
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