KuLGaP: A Selective Measure for Assessing Therapy Response in Patient-Derived Xenografts

Abstract

Quantifying response to drug treatment in mouse models of human cancer is important for treatment development and assignment, and yet remains a challenging task. A preferred measure to quantify this response should take into account as much of the experimental data as possible, i.e. both tumor size over time and the variation among replicates. We propose a theoretically grounded measure, KuLGaP, to compute the difference between the treatment and control arms. KuLGaP is more selective than currently existing measures, reduces the risk of false positive calls and improves translation of the lab results to clinical practice.

CombPDX: a unified statistical framework for evaluating drug synergism in patient-derived xenografts

“…For combination experiments, we expect that the mean relative tumor volumes of the treatment groups , and are less than the control tumor volume , which results in , and located between 0 and 1. While this has been widely used as the tumor growth inhibition (TGI) with predetermined cutoffs of declaring an antitumor activity 49 – 51 , we incorporate statistical inferential procedures by constructing 95% confidence intervals. The lower bound of a one-sided 100(1- confidence interval for a combination index can be calculated using the Delta method, where , , and is the ( -th quantile of standard normal distribution (Section S3.2 ).…”

CombPDX: a unified statistical framework for evaluating drug synergism in patient-derived xenografts

“…For combination experiments, we expect that the mean relative tumor volumes of the treatment groups μ A , μ B and μ AB are less than the control tumor volume μ C , which results in δ A , δ B and δ AB located between 0 and 1. While this has been widely used as the tumor growth inhibition (TGI) with predetermined cutoffs of declaring an antitumor activity [46][47][48] , we incorporate statistical inferential procedures by constructing 95% confidence intervals. The lower bound of a one-sided 100(1-α)% confidence interval for a combination index can be calculated using the Delta method, δ ̂g − z 1−α se ̂(δ ̂g)…”

CombPDX: a unified statistical framework for evaluating drug synergism in patient-derived xenografts

“…, which results in 𝛿 , , 𝛿 -and 𝛿 ,-located between 0 and 1. While this has been widely used as the tumor growth inhibition (TGI) with predetermined cutoffs of declaring an antitumor activity (Houghton, et al, 2007;Mer, et al, 2019;Ortmann, et al, 2020), we incorporate statistical inferential procedures by constructing 95% confidence intervals. The lower bound of a one-sided 100(1-𝛼)% confidence interval for a combination index can be calculated using the Delta method,…”