Literature DB >> 23280944

Designing exploratory cancer trials using change in tumour size as primary endpoint.

Thomas Jaki1, Valérie André, Ting-Li Su, John Whitehead.   

Abstract

In phase III cancer clinical trials, overall survival is commonly used as the definitive endpoint. In phase II clinical trials, however, more immediate endpoints such as incidence of complete or partial response within 1 or 2 months or progression-free survival (PFS) are generally used. Because of the limited ability to detect change in overall survival with response, the inherent variability of PFS and the long wait for progression to be observed, more informative and immediate alternatives to overall survival are desirable in exploratory phase II trials. In this paper, we show how comparative trials can be designed and analysed using change in tumour size as the primary endpoint. The test developed is based on the framework of score statistics and will formally incorporate the information of whether patients survive until the time at which change in tumour size is assessed. Using an example in non-small cell lung cancer, we show that the sample size requirements for a trial based on change in tumour size are favourable compared with alternative randomized trials and demonstrate that these conclusions are robust to our assumptions.
Copyright © 2012 John Wiley & Sons, Ltd.

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Year:  2012        PMID: 23280944     DOI: 10.1002/sim.5716

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  11 in total

1.  Evaluating Continuous Tumor Measurement-Based Metrics as Phase II Endpoints for Predicting Overall Survival.

Authors:  Ming-Wen An; Xinxin Dong; Jeffrey Meyers; Yu Han; Axel Grothey; Jan Bogaerts; Daniel J Sargent; Sumithra J Mandrekar
Journal:  J Natl Cancer Inst       Date:  2015-08-21       Impact factor: 13.506

2.  Resampling the N9741 trial to compare tumor dynamic versus conventional end points in randomized phase II trials.

Authors:  Manish R Sharma; Elizabeth Gray; Richard M Goldberg; Daniel J Sargent; Theodore G Karrison
Journal:  J Clin Oncol       Date:  2014-10-27       Impact factor: 44.544

3.  The power of phase II end-points for different possible mechanisms of action of an experimental treatment.

Authors:  J M S Wason; A Dentamaro; T G Eisen
Journal:  Eur J Cancer       Date:  2015-03-31       Impact factor: 9.162

4.  Clinical Utility of Metrics Based on Tumor Measurements in Phase II Trials to Predict Overall Survival Outcomes in Phase III Trials by Using Resampling Methods.

Authors:  Ming-Wen An; Yu Han; Jeffrey P Meyers; Jan Bogaerts; Daniel J Sargent; Sumithra J Mandrekar
Journal:  J Clin Oncol       Date:  2015-10-26       Impact factor: 44.544

5.  Are tumor size changes predictive of survival for checkpoint blockade based immunotherapy in metastatic melanoma?

Authors:  Meihua Wang; Cong Chen; Thomas Jemielita; James Anderson; Xiaoyun Nicole Li; Chen Hu; S Peter Kang; Nageatte Ibrahim; Scot Ebbinghaus
Journal:  J Immunother Cancer       Date:  2019-02-08       Impact factor: 13.751

6.  A response-adaptive randomization procedure for multi-armed clinical trials with normally distributed outcomes.

Authors:  S Faye Williamson; Sofía S Villar
Journal:  Biometrics       Date:  2019-09-19       Impact factor: 2.571

7.  Efficient analysis of time-to-event endpoints when the event involves a continuous variable crossing a threshold.

Authors:  Chien-Ju Lin; James M S Wason
Journal:  J Stat Plan Inference       Date:  2020-09       Impact factor: 1.111

8.  Missing tumor measurement (TM) data in the search for alternative TM-based endpoints in cancer clinical trials.

Authors:  Ming-Wen An; Jun Tang; Axel Grothey; Daniel J Sargent; Fang-Shu Ou; Sumithra J Mandrekar
Journal:  Contemp Clin Trials Commun       Date:  2019-11-22

9.  Using continuous data on tumour measurements to improve inference in phase II cancer studies.

Authors:  James M S Wason; Shaun R Seaman
Journal:  Stat Med       Date:  2013-06-18       Impact factor: 2.373

10.  Improving phase II oncology trials using best observed RECIST response as an endpoint by modelling continuous tumour measurements.

Authors:  Chien-Ju Lin; James M S Wason
Journal:  Stat Med       Date:  2017-08-28       Impact factor: 2.373

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