Yvonne Y Lau1, Wen Gu2, Yu-Yun Ho2, Ying Hong2, Xinrui Zhang2, Patrick Urban3. 1. Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA. yvonne.lau@novartis.com. 2. Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA. 3. Novartis Pharma AG, Basel, Switzerland.
Abstract
PURPOSE: Ceritinib 750 mg/day was approved for the treatment of patients with untreated anaplastic lymphoma kinase (ALK)-rearranged non-small cell lung cancer (NSCLC) based on ASCEND-4 study. The objective of this article is to introduce the use of time-dependent modeling approach in the updated exposure-efficacy analysis of ceritinib for the first-line indication. METHODS: Exposure-efficacy analyses, including data from 156 patients, were first conducted using time-independent logistic regression model for response of complete or partial response and Cox regression model for progression-free survival (PFS). The exposure measure used was average Ctrough, which is defined as the geometric mean of all evaluable Ctrough for each patient. To further investigate the impact of exposure measure on exposure-efficacy analyses, a time-dependent modeling approach was used, where exposure at different time intervals was associated with the corresponding response endpoints in a longitudinal manner. RESULTS: With exposure measure being average Ctrough, it was observed that higher exposure was associated with reduced efficacy in terms of response (odds ratio = 0.77) and PFS [hazard ratio (HR) = 1.12]. These time-independent models do not account for the impact of time-varying concentration due to dose modifications. Subsequently, a new time-dependent modeling approach was used, where exposure and efficacy were associated longitudinally in the analyses. The results showed that the odds ratio of response became 1.07, and the HR of PFS became 1.04, indicating no apparent reverse relationship between exposure and efficacy across the exposure range studied. CONCLUSION: The drug effect on efficacy in clinical trials could be better characterized using time-dependent exposure-response models.
RCT Entities:
PURPOSE:Ceritinib 750 mg/day was approved for the treatment of patients with untreated anaplastic lymphoma kinase (ALK)-rearranged non-small cell lung cancer (NSCLC) based on ASCEND-4 study. The objective of this article is to introduce the use of time-dependent modeling approach in the updated exposure-efficacy analysis of ceritinib for the first-line indication. METHODS: Exposure-efficacy analyses, including data from 156 patients, were first conducted using time-independent logistic regression model for response of complete or partial response and Cox regression model for progression-free survival (PFS). The exposure measure used was average Ctrough, which is defined as the geometric mean of all evaluable Ctrough for each patient. To further investigate the impact of exposure measure on exposure-efficacy analyses, a time-dependent modeling approach was used, where exposure at different time intervals was associated with the corresponding response endpoints in a longitudinal manner. RESULTS: With exposure measure being average Ctrough, it was observed that higher exposure was associated with reduced efficacy in terms of response (odds ratio = 0.77) and PFS [hazard ratio (HR) = 1.12]. These time-independent models do not account for the impact of time-varying concentration due to dose modifications. Subsequently, a new time-dependent modeling approach was used, where exposure and efficacy were associated longitudinally in the analyses. The results showed that the odds ratio of response became 1.07, and the HR of PFS became 1.04, indicating no apparent reverse relationship between exposure and efficacy across the exposure range studied. CONCLUSION: The drug effect on efficacy in clinical trials could be better characterized using time-dependent exposure-response models.
Authors: Neeraj Gupta; Anna Largajolli; Han Witjes; Paul M Diderichsen; Steven Zhang; Michael J Hanley; Jianchang Lin; Minal Mehta Journal: Clin Pharmacol Ther Date: 2022-05-29 Impact factor: 6.903
Authors: D Ross Camidge; Hye Ryun Kim; Myung-Ju Ahn; James C H Yang; Ji-Youn Han; Maximilian J Hochmair; Ki Hyeong Lee; Angelo Delmonte; Maria Rosario García Campelo; Dong-Wan Kim; Frank Griesinger; Enriqueta Felip; Raffaele Califano; Alexander Spira; Scott N Gettinger; Marcello Tiseo; Huamao M Lin; Neeraj Gupta; Michael J Hanley; Quanhong Ni; Pingkuan Zhang; Sanjay Popat Journal: J Clin Oncol Date: 2020-08-11 Impact factor: 44.544