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.

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.

journal_name

Pharmacoeconomics

journal_title

PharmacoEconomics

authors

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

doi

10.1007/s40273-020-00951-1

subject

Has Abstract

pub_date

2020-11-01 00:00:00

pages

1263-1275

issue

11

eissn

1170-7690

issn

1179-2027

pii

10.1007/s40273-020-00951-1

journal_volume

38

pub_type

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