Simulating progression-free and overall survival for first-line doublet chemotherapy with or without bevacizumab in metastatic colorectal cancer patients based on real-world registry data

Degeling, K; Wong, HL; Koffijberg, H; Jalali, A; Shapiro, J; Kosmider, S; Wong, R; Lee, B; Burge, M; Tie, J; Yip, D; Nott, L; Khattak, A; Lim, S; Caird, S; Gibbs, P; IJzerman M

Author(s): Degeling, K; Wong, HL; Koffijberg, H; Jalali, A; Shapiro, J; Kosmider, S; Wong, R; Lee, B; Burge, M; Tie, J; Yip, D; Nott, L; Khattak, A; Lim, S; Caird, S; Gibbs, P; IJzerman M;
Details: Publication Year 2020-11,Volume 38,Issue #11,Page 1263-1275
Journal Title: Pharmacoeconomics
Publication Type: Journal Article
Abstract: BACKGROUND: Simulation models utilizing real-world data have potential to optimize treatment sequencing strategies for specific patient subpopulations, including when conducting clinical trials is not feasible. We aimed to develop a simulation model to estimate progression-free survival (PFS) and overall survival for first-line doublet chemotherapy with or without bevacizumab for specific subgroups of metastatic colorectal cancer (mCRC) patients based on registry data. METHODS: Data from 867 patients were used to develop two survival models and one logistic regression model that populated a discrete event simulation (DES). Discrimination and calibration were used for internal validation of these models separately and predicted and observed medians and Kaplan-Meier plots were compared for the integrated DES. Bootstrapping was performed to correct for optimism in the internal validation and to generate correlated sets of model parameters for use in a probabilistic analysis to reflect parameter uncertainty. RESULTS: The survival models showed good calibration based on the regression slopes and modified Hosmer-Lemeshow statistics at 1 and 2 years, but not for short-term predictions at 0.5 years. Modified C-statistics indicated acceptable discrimination. The simulation estimated that median first-line PFS (95% confidence interval) of 219 (25%) patients could be improved from 175 days (156-199) to 269 days (246-294) if treatment would be targeted based on the highest expected PFS. CONCLUSIONS: Extensive internal validation showed that DES accurately estimated the outcomes of treatment combination strategies for specific subpopulations, with outcomes suggesting treatment could be optimized. Although results based on real-world data are informative, they cannot replace randomized trials.
Publisher: Springer
Research Division(s): Personalised Oncology
PubMed ID: 32803720
Publisher's Version: https://doi.org/10.1007/s40273-020-00951-1
Terms of Use/Rights Notice: Refer to copyright notice on published article.

Creation Date: 2020-11-02 04:55:15

Last Modified: 2020-11-02 04:59:46