Literature DB >> 26435269

Model free audit methodology for bias evaluation of tumour progression in oncology.

Andrew Stone1, Euan Macpherson1, Ann Smith1, Christopher Jennison2.   

Abstract

Many oncology studies incorporate a blinded independent central review (BICR) to make an assessment of the integrity of the primary endpoint, progression free survival. Recently, it has been suggested that, in order to assess the potential for bias amongst investigators, a BICR amongst only a sample of patients could be performed; if evidence of bias is detected, according to a predefined threshold, the BICR is then assessed in all patients, otherwise, it is concluded that the sample was sufficient to rule out meaningful levels of bias. In this paper, we present an approach that adapts a method originally created for defining futility bounds in group sequential designs. The hazard ratio ratio, the ratio of the hazard ratio (HR) for the treatment effect estimated from the BICR to the corresponding HR for the investigator assessments, is used as the metric to define bias. The approach is simple to implement and ensures a high probability that a substantial true bias will be detected. In the absence of bias, there is a high probability of accepting the accuracy of local evaluations based on the sample, in which case an expensive BICR of all patients is avoided. The properties of the approach are demonstrated by retrospective application to a completed Phase III trial in colorectal cancer. The same approach could easily be adapted for other disease settings, and for test statistics other than the hazard ratio.
Copyright © 2015 John Wiley & Sons, Ltd.

Entities:  

Keywords:  independent review; oncology; progression; sample

Mesh:

Year:  2015        PMID: 26435269     DOI: 10.1002/pst.1707

Source DB:  PubMed          Journal:  Pharm Stat        ISSN: 1539-1604            Impact factor:   1.894


  1 in total

1.  Selumetinib Plus Docetaxel Compared With Docetaxel Alone and Progression-Free Survival in Patients With KRAS-Mutant Advanced Non-Small Cell Lung Cancer: The SELECT-1 Randomized Clinical Trial.

Authors:  Pasi A Jänne; Michel M van den Heuvel; Fabrice Barlesi; Manuel Cobo; Julien Mazieres; Lucio Crinò; Sergey Orlov; Fiona Blackhall; Juergen Wolf; Pilar Garrido; Artem Poltoratskiy; Gabriella Mariani; Dana Ghiorghiu; Elaine Kilgour; Paul Smith; Alexander Kohlmann; David J Carlile; David Lawrence; Karin Bowen; Johan Vansteenkiste
Journal:  JAMA       Date:  2017-05-09       Impact factor: 56.272

  1 in total

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