Thresholding of a Companion Diagnostic Test Confident of Efficacy in Targeted Population
Jason C Hsu, The Ohio State University & Eli Lilly and Company Eloise Kaizar, Ohio State University Ying Grace Li, Eli Lilly & Company Yi Liu, Millennium: The Takeda Oncology Company Michael Man, Eli Lilly & Company Stephen J. Ruberg, Eli Lilly & Company *Szu-Yu Tang, Ventana Medical Systems, Inc. Keywords: Biomarker, Thresholding, subgroup, companion diagnostics In personalized medicine, continuous biomarker values are often dichotomized to classify patients into target and non-target populations. Cast in the setting of normally distributed responses that are modeled linearly (such as diabetes and psychiatry), this article provides a method of inferring which thresholds correspond to target populations that benefit from the treatment. By providing simultaneous confidence intervals for efficacy corresponding to all candidate thresholds, our method allows for flexible decision-making, taking into consideration marketing potential based on both the size of the target population and efficacy in the target population. Under the assumption of the general linear model (GLM), advantages of our approach over the Jiang, Freidlin, Simon (2007) approach are that (1) formulation is clinically more meaningful, (2) imbalance in the data would not lead to misleading inference, (3) simultaneous confidence intervals are provided, (4) error rate and confidence level computations are precise, (5) simple SAS codes are available.
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Key Dates
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April 30 - May 22, 2013
Invited Abstract Submission Open -
June 4, 2013
Online Registration Opens -
August 9 - August 23, 2013
Invited Abstract Editing -
August 23, 2013
Short Course materials due from Instructors -
August 26, 2013
Housing Deadline -
September 9, 2013
Cancellation Deadline and Registration Closes @ 11:59 pm EDT -
September 16 - September 18, 2013
Marriott Wardman Park, Washington, DC