Please use this identifier to cite or link to this item: http://dora.health.qld.gov.au/qldresearchjspui/handle/1/1541
Title: 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
Authors: Degeling, Koen
Wong, Hui-Li
Koffijberg, Hendrik
Jalali, Azim
Shapiro, Jeremy
Kosmider, Suzanne
Wong, Rachel
Lee, Belinda
Burge, Matthew
Tie, Jeanne
Yip, Desmond
Nott, Louise
Khattak, Adnan
Lim, Stephanie
Caird, Susan 
Gibbs, Peter
IJzerman, Maarten
Issue Date: Nov-2020
Publisher: Springer
Source: 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. 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. Pharmacoeconomics. 2020 Nov;38(11):1263-1275. doi: 10.1007/s40273-020-00951-1
Journal: PharmacoEconomics
Abstract: 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. 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. 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. 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.
DOI: 10.1007/s40273-020-00951-1
Type: Article
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