The reciprocal relationship between alliance and early treatment symptoms: A two-stage individual participant data meta-analysis.

2020 ◽  
Vol 88 (9) ◽  
pp. 829-843 ◽  
Author(s):  
Christoph Flückiger ◽  
Julian Rubel ◽  
A. C. Del Re ◽  
Adam O. Horvath ◽  
Bruce E. Wampold ◽  
...  
Keyword(s):  
Early Treatment ◽  
Meta Analysis ◽  
Reciprocal Relationship ◽  
Individual Participant Data ◽  
Two Stage ◽  
Individual Participant

Therapeutische Allianz: Welche Rolle spielen die ersten Sitzungen?

2020 ◽  
Vol 21 (04) ◽  
pp. 6-6
Keyword(s):  
Early Treatment ◽  
Meta Analysis ◽  
Reciprocal Relationship ◽  
Individual Participant Data ◽  
Consult Clin Psychol ◽  
Two Stage ◽  
Individual Participant ◽  
Therapeutische Allianz

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.

scholarly journals Multilevel Meta-Analysis of Individual Participant Data of Single-Case Experimental Designs: One-Stage versus Two-Stage Methods

2020 ◽  
pp. 1-20
Author(s):  
Lies Declercq ◽  
Laleh Jamshidi ◽  
Belén Fernández Castilla ◽  
Mariola Moeyaert ◽  
S. Natasha Beretvas ◽  
...  
Keyword(s):  
Single Case ◽  
Meta Analysis ◽  
Experimental Designs ◽  
Individual Participant Data ◽  
Stage Versus ◽  
Two Stage ◽  
One Stage ◽  
Individual Participant

scholarly journals Individual Participant Data Meta-Analysis for a Binary Outcome: One-Stage or Two-Stage?

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
Keyword(s):  
Meta Analysis ◽  
Individual Participant Data ◽  
Binary Outcome ◽  
Two Stage ◽  
One Stage ◽  
Individual Participant

scholarly journals A Primer on Two-Stage Meta-Analysis with Individual Participant Data Obtained from Complex Sampling Surveys

2021 ◽  
Author(s):  
Diego Campos ◽  
Mike W.-L. Cheung ◽  
Ronny Scherer
Keyword(s):  
Meta Analysis ◽  
Sample Selection ◽  
Target Population ◽  
Primary Data ◽  
Complex Nature ◽  
Individual Participant Data ◽  
Two Stage ◽  
Complex Surveys ◽  
Complex Sampling ◽  
Individual Participant

The increasing availability of individual participant data (IPD) in the social sciences offers new possibilities to synthesize research evidence across primary studies. Two-stage IPD meta-analysis represents a framework that can utilize these possibilities. While most of the methodological research on two-stage IPD meta-analysis focused on its performance compared with other approaches, dealing with the complexities of the primary data has received little attention, particularly when IPD are drawn from complex sampling surveys. Complex sampling surveys often feature clustering, stratification, disproportionate sampling, and multiple stages of sample selection to obtain nationally or internationally representative data from a target population. Furthermore, IPD from these studies are likely to provide more than one effect size. To address the complexities of the primary and meta-analytic data obtained from complex surveys, we propose a two-stage IPD meta-analytic approach and illustrate its utility. To aid meta-analysts who wish to utilize complex survey data, we present a sequence of steps and discuss the methodological decisions and options within. Given its flexibility and ability to deal with the complex nature of the primary data, the proposed two-stage approach opens up new analytical possibilities for synthesizing knowledge meta-analytically.

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 ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Disease Activity ◽  
Treatment Response ◽  
Meta Analysis ◽  
Baseline Risk ◽  
Risk Scores ◽  
Individual Participant Data ◽  
Two Stage ◽  
Individual Participant ◽  
Predict Treatment Response

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).

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