2020/04/30 by Konstantina Chalkou, Ewout Steyerberg, Ewout W. Steyerberg +4 · 31 citations
Decision Sciences · Mathematics · Medicine · #Baseline (sea) #Disease #Glatiramer acetate #Intensive care medicine #Internal medicine #Medicine #Meta-analysis #Meta-analysis and systematic reviews #Multiple Sclerosis Research Studies #Mycobacterium research and diagnosis #Natalizumab #Oncology #Randomized controlled trial #Stage (stratigraphy) #stat.AP #stat.ME
paper · pdf · doi:10.1002/sim.9034
published in Statistics in Medicine 40(20), 4362-4375 (Wiley)
openalex publication_date 2021/05/27 · arxiv created 2022/02/07 · arxiv updated 2022/02/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
Treatment effects vary across different patients, and estimation of this variability is essential for clinical decision-making. We aimed to develop a model estimating the benefit of alternative treatment options for individual patients, extending a risk modeling approach in a network meta-analysis framework. We propose a two-stage prediction model for heterogeneous treatment effects by combining prognosis research and network meta-analysis methods where individual patient data are available. In the first stage, a prognostic model to predict the baseline risk of the outcome. In the second stage, we use the baseline risk score from the first stage as a single prognostic factor and effect modifier in a network meta-regression model. We apply the approach to a network meta-analysis of three randomized clinical trials comparing the relapses in Natalizumab, Glatiramer Acetate, and Dimethyl Fumarate, including 3590 patients diagnosed with relapsing-remitting multiple sclerosis. We find that the baseline risk score modifies the relative and absolute treatment effects. Several patient characteristics, such as age and disability status, impact the baseline risk of relapse, which in turn moderates the benefit expected for each of the treatments. For high-risk patients, the treatment that minimizes the risk of relapse in 2 years is Natalizumab, whereas Dimethyl Fumarate might be a better option for low-risk patients. Our approach can be easily extended to all outcomes of interest and has the potential to inform a personalized treatment approach.