40 citations · 68 across the 3 of their papers we have counts for
5 papers
Combining randomized and non-randomized data to predict heterogeneous effects of competing treatments
Konstantina Chalkou, Tasnim Hamza, Pascal Benkert +7
Some patients benefit from a treatment while others may do so less or do not benefit at all. We have previously developed a two-stage network meta-regression prediction model that…
Synthesizing cross-design evidence and cross-format data using network meta-regression
Tasnim Hamza, Konstantina Chalkou, Fabio Pellegrini +9
In network meta-analysis (NMA), we synthesize all relevant evidence about health outcomes with competing treatments. The evidence may come from randomized controlled trials (RCT) o…
Decision curve analysis for personalized treatment choice between multiple options
Konstantina Chalkou, Andrew J. Vickers, Fabio Pellegrini +2
Decision curve analysis can be used to determine whether a personalized model for treatment benefit would lead to better clinical decisions. Decision curve analysis methods have be…
Development, validation and clinical usefulness of a prognostic model for relapse in relapsing-remitting multiple sclerosis
Konstantina Chalkou, Ewout Steyerberg, Patrick Bossuyt +7
Prognosis on the occurrence of relapses in individuals with Relapsing-Remitting Multiple Sclerosis (RRMS), the most common subtype of Multiple Sclerosis (MS), could support individ…
A two-stage prediction model for heterogeneous effects of many treatment options: application to drugs for Multiple Sclerosis
Konstantina Chalkou, Ewout Steyerberg, Matthias Egger +3
Treatment effects vary across different patients and estimation of this variability is important for clinical decisions. The aim is to develop a model to estimate the benefit of al…