Abstract 4760: Joint modeling of longitudinal tumor dynamics and survival in non-small cell lung cancer (NSCLC) patients

• Published in: Cancer research (Chicago, Ill.) Vol. 78; no. 13_Supplement; p. 4760
• Main Authors: Tong, Xiao, Dunyak, James, Zhou, Diansong, Carlile, David, Tomkinson, Helen, Helmlinger, Gabriel, Al-Huniti, Nidal, Xu, Hongmei
• Format: Journal Article
• Language: English
• Published: 01.07.2018
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/1538-7445.AM2018-4760

Abstract Objectives: Tumor size dynamics and survival are traditionally analyzed in a 2-stage approach, without consideration of joint dependencies. The objective of this analysis was to develop a joint model which associates tumor size dynamics and progression-free survival (PFS), to predict time-to-progression. Methods: Phase 2 trial data from selumetinib (AZD6244; ARRY-142886, MEK inhibitor), in NSCLC patients (SELECT-2; NCT01750281) were used to develop a joint model for tumor size dynamics and PFS. The analysis was performed using JM package in R. Treatment arm, KRAS mutation and WHO performance status were evaluated as covariates. Model was evaluated by survival estimation based on early time (e.g., first 3 months) tumor size data. The final joint model based on SELECT-2 data was then used to predict PFS of selumetinib in SELECT-1 (NCT01933932) phase 3 trial. Results: The joint model developed on SELECT-2 data identified a significant association (p value <0.001) between the slope of the longitudinal tumor dynamic and PFS. WHO performance status was identified to be the only significant covariate. Furthermore, the model built on phase 2 data adequately predicted PFS of the SELECT-1 data, using SELECT-1 tumor size data within 4 months of treatment. Prediction confirmed no significant difference in PFS between active treatment arm and chemotherapy arm in SELECT-1 trial. Conclusions: Using selumetinib as an example, we showed that joint modeling of tumor size dynamics and PFS may provide a novel quantitative tool to predict long-term outcome in NSCLC based on early tumor size measurements. Citation Format: Xiao Tong, James Dunyak, Diansong Zhou, David Carlile, Helen Tomkinson, Gabriel Helmlinger, Nidal Al-Huniti, Hongmei Xu. Joint modeling of longitudinal tumor dynamics and survival in non-small cell lung cancer (NSCLC) patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4760.