scholarly journals Predicting the Treatment Response of Certolizumab for Individual Adult Patients with Rheumatoid Arthritis: Protocol for An Individual Participant Data Meta-Analysis

2020 ◽  
Author(s):  
Yan Luo ◽  
Konstantina Chalkou ◽  
Ryo Yamada ◽  
Satoshi Funada ◽  
Georgia Salanti ◽  
...  

Abstract Background A model that can predict treatment response for a patient with specific baseline characteristics would help decision-making in personalized medicine. The aim of the study is to develop such a model in the treatment of rheumatoid arthritis (RA) patients who receive certolizumab (CTZ) plus methotrexate (MTX) therapy, using individual participant data meta-analysis (IPD-MA).Methods We will search Cochrane CENTRAL, PubMed, and Scopus as well as clinical trial registries, drug regulatory agency reports, and the pharmaceutical company websites from their inception onwards to obtain randomized controlled trials (RCTs) investigating CTZ plus MTX compared with MTX alone in treating RA. We will request the individual-level data of these trials from an independent platform (http://vivli.org). The primary outcome is efficacy defined as achieving either remission (based on ACR-EULAR Boolean or index-based remission definition) or low disease activity (based on either of the validated composite disease activity measures). The secondary outcomes include ACR50 (50% improvement based on ACR core set variables) and adverse events. We will use a two-stage approach to develop the prediction model. First, we will construct a risk model for the outcomes via logistic regression to estimate the baseline risk scores. We will include baseline demographic, clinical and biochemical features as covariates for this model. Next, we will develop a meta-regression model for treatment effects, in which the stage-one risk score will be used both as a prognostic factor and as an effect modifier. We will calculate the probability of having the outcome for a new patient based on the model, which will allow estimation of the absolute and relative treatment effect. We will use R for our analyses, except for the second stage which will be performed in a Bayesian setting using R2Jags.Discussion This is a study protocol for developing a model to predict treatment response for RA patients receiving CTZ plus MTX in comparison with MTX alone, using a two-stage approach based on IPD-MA. The study will use a new modeling approach, which aims at retaining the statistical power. The model may help clinicians individualize treatment for particular patients.Systematic review registration PROPSPERO registration number pending (ID#157595).

2020 ◽  
Author(s):  
Yan Luo ◽  
Konstantina Chalkou ◽  
Ryo Yamada ◽  
Satoshi Funada ◽  
Georgia Salanti ◽  
...  

Abstract Background: A model that can predict treatment response for a patient with specific baseline characteristics would help decision-making in personalized medicine. The aim of the study is to develop such a model in the treatment of rheumatoid arthritis (RA) patients who receive certolizumab (CTZ) plus methotrexate (MTX) therapy, using individual participant data meta-analysis (IPD-MA).Methods: We will search Cochrane CENTRAL, PubMed, and Scopus as well as clinical trial registries, drug regulatory agency reports, and the pharmaceutical company websites to obtain randomized controlled trials (RCTs) investigating CTZ plus MTX compared with MTX alone in treating RA. We will request the individual-level data of these trials from an independent platform (http://vivli.org). The primary outcome is efficacy defined as achieving either remission (based on ACR-EULAR Boolean or index-based remission definition) or low disease activity (based on either of the validated composite disease activity measures). The secondary outcomes include ACR50 (50% improvement based on ACR core set variables) and adverse events. We will use a two-stage approach to develop the prediction model. First, we will construct a risk model for the outcomes via logistic regression to estimate the baseline risk scores. We will include baseline demographic, clinical and biochemical features as covariates for this model. Next, we will develop a meta-regression model for treatment effects, in which the stage-one risk score will be used both as a prognostic factor and as an effect modifier. We will calculate the probability of having the outcome for a new patient based on the model, which will allow estimation of the absolute and relative treatment effect. We will use R for our analyses, except for the second stage which will be performed in a Bayesian setting using R2Jags.Discussion: This is a study protocol for developing a model to predict treatment response for RA patients receiving CTZ plus MTX in comparison with MTX alone, using a two-stage approach based on IPD-MA. The study will use a new modeling approach, which aims at retaining the statistical power. The model may help clinicians individualize treatment for particular patients.Systematic review registration: PROPSPERO: ID#157595 (Pending).


Author(s):  
Lies Declercq ◽  
Laleh Jamshidi ◽  
Belén Fernández Castilla ◽  
Mariola Moeyaert ◽  
S. Natasha Beretvas ◽  
...  

2020 ◽  
Vol 88 (9) ◽  
pp. 829-843 ◽  
Author(s):  
Christoph Flückiger ◽  
Julian Rubel ◽  
A. C. Del Re ◽  
Adam O. Horvath ◽  
Bruce E. Wampold ◽  
...  

PLoS ONE ◽  
2013 ◽  
Vol 8 (4) ◽  
pp. e60650 ◽  
Author(s):  
Thomas P. A. Debray ◽  
Karel G. M. Moons ◽  
Ghada Mohammed Abdallah Abo-Zaid ◽  
Hendrik Koffijberg ◽  
Richard David Riley

2020 ◽  
Vol 21 (04) ◽  
pp. 6-6

Flückiger C et al. The reciprocal relationship between alliance and early treatment symptoms: A two-stage individual participant data meta-analysis. J Consult Clin Psychol 2020. doi: 10.1037/ccp0000594 Die Therapeutische Allianz beschreibt die Verbindung von Behandler und Patient innerhalb des „therapeutischen Arbeitsbündnisses“ in der Psychotherapie und spielt eine wichtige Rolle für das Behandlungsergebnis. Da es bis heute unklar ist, in wieweit eine gute Allianz und frühe Symptomrückbildung zusammenhängen, legt Christoph Flückiger mit einem internationalen Expertenteam von 25 MitautorInnen nun die Ergebnisse einer 2-stufigen Primärdaten-Metaanalyse zum Thema vor.


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