ABSTRACT To date there are a number of FDA-approved companion diagnostics for use with specific corresponding therapeutic products. Hence, opportunities exist for device manufacturers to develop follow-on companion diagnostic devices. A follow-on companion diagnostic is intended to be used with the therapeutic product in the indicated patient population, as in the labeling of the comparator companion diagnostic. Thus, information provided by a follow-on companion diagnostic device is essential for the safe and effective use of the corresponding therapeutic product in the comparator companion diagnostic. However, the manufacturer of a follow-on companion diagnostic device may not have a therapeutic partner to conduct a new clinical trial, or there may lack the patient samples from the original clinical trial, where the comparator and therapeutic product were evaluated. As such, an external concordance study is conducted to assess the concordance between the comparator and the follow-on device. Difficulty and challenges arise on how to evaluate the follow-on device’s clinical performance based the agreements from an external concordance study. In this article, we will discuss the challenges and issues for the clinical validation of follow-on devices and we aim to provide some statistical methods on how to support clinical validation of follow-on companion diagnostic devices for its proposed indications for use via an external concordance study.
[1]
Bradley Efron,et al.
Missing Data, Imputation, and the Bootstrap
,
1994
.
[2]
M. Pepe,et al.
Comparing the predictive values of diagnostic tests: sample size and analysis for paired study designs
,
2006,
Clinical trials.
[3]
Tinghui Yu,et al.
The impact of companion diagnostic device measurement performance on clinical validation of personalized medicine
,
2015,
Statistics in medicine.
[4]
Novel Approach for Clinical Validation of the cobas KRAS Mutation Test in Advanced Colorectal Cancer
,
2016,
Molecular Diagnosis & Therapy.
[5]
Meijuan Li.
Statistical Consideration and Challenges in Bridging Study of Personalized Medicine
,
2015,
Journal of biopharmaceutical statistics.
[6]
M. Pepe,et al.
Comparisons of Predictive Values of Binary Medical Diagnostic Tests for Paired Designs
,
2000,
Biometrics.
[7]
R G Newcombe,et al.
Improved confidence intervals for the difference between binomial proportions based on paired data.
,
1998,
Statistics in medicine.