scholarly journals Predicting personalised absolute treatment effects in individual participant data meta‐analysis: an introduction to splines

2022 ◽  
Author(s):  
Michail Belias ◽  
Maroeska M. Rovers ◽  
Jeroen Hoogland ◽  
Johannes B. Reitsma ◽  
Thomas P. A. Debray ◽  
...  
Keyword(s):  
Treatment Effects ◽  
Meta Analysis ◽  
Individual Participant Data ◽  
Individual Participant

An overview of methods for network meta-analysis using individual participant data: when do benefits arise?

2016 ◽  
Vol 27 (5) ◽  
pp. 1351-1364 ◽  
Author(s):  
Thomas PA Debray ◽  
Ewoud Schuit ◽  
Orestis Efthimiou ◽  
Johannes B Reitsma ◽  
John PA Ioannidis ◽  
...  
Keyword(s):  
Treatment Effects ◽  
Evidence Synthesis ◽  
Meta Analysis ◽  
Drop Out ◽  
Individual Participant Data ◽  
Missing Response ◽  
Response Data ◽  
Study Heterogeneity ◽  
Individual Participant ◽  
Network Consistency

Network meta-analysis (NMA) is a common approach to summarizing relative treatment effects from randomized trials with different treatment comparisons. Most NMAs are based on published aggregate data (AD) and have limited possibilities for investigating the extent of network consistency and between-study heterogeneity. Given that individual participant data (IPD) are considered the gold standard in evidence synthesis, we explored statistical methods for IPD-NMA and investigated their potential advantages and limitations, compared with AD-NMA. We discuss several one-stage random-effects NMA models that account for within-trial imbalances, treatment effect modifiers, missing response data and longitudinal responses. We illustrate all models in a case study of 18 antidepressant trials with a continuous endpoint (the Hamilton Depression Score). All trials suffered from drop-out; missingness of longitudinal responses ranged from 21 to 41% after 6 weeks follow-up. Our results indicate that NMA based on IPD may lead to increased precision of estimated treatment effects. Furthermore, it can help to improve network consistency and explain between-study heterogeneity by adjusting for participant-level effect modifiers and adopting more advanced models for dealing with missing response data. We conclude that implementation of IPD-NMA should be considered when trials are affected by substantial drop-out rate, and when treatment effects are potentially influenced by participant-level covariates.

scholarly journals Long working hours and alcohol use: systematic review and meta-analysis of published studies and unpublished individual participant data

BMJ ◽  
2015 ◽  
Vol 350 (jan12 13) ◽  
pp. g7772-g7772 ◽  
Author(s):  
M. Virtanen ◽  
M. Jokela ◽  
S. T. Nyberg ◽  
I. E. H. Madsen ◽  
T. Lallukka ◽  
...  
Keyword(s):  
Systematic Review ◽  
Alcohol Use ◽  
Meta Analysis ◽  
Working Hours ◽  
Individual Participant Data ◽  
Long Working Hours ◽  
Individual Participant

scholarly journals Diet and physical activity in pregnancy to prevent gestational diabetes: a protocol for an individual participant data (IPD) meta-analysis on the differential effects of interventions with economic evaluation

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e048119
Author(s):  
Dyuti Coomar ◽  
Jonathan M Hazlehurst ◽  
Frances Austin ◽  
Charlie Foster ◽  
Graham A Hitman ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cost Effectiveness ◽  
Gestational Diabetes ◽  
Systematic Reviews ◽  
Meta Analysis ◽  
Individual Participant Data ◽  
Randomised Trials ◽  
Diet And Physical Activity ◽  
Individual Participant ◽  
In Pregnancy

IntroductionMothers with gestational diabetes mellitus (GDM) are at increased risk of pregnancy-related complications and developing type 2 diabetes after delivery. Diet and physical activity-based interventions may prevent GDM, but variations in populations, interventions and outcomes in primary trials have limited the translation of available evidence into practice. We plan to undertake an individual participant data (IPD) meta-analysis of randomised trials to assess the differential effects and cost-effectiveness of diet and physical activity-based interventions in preventing GDM and its complications.MethodsThe International Weight Management in Pregnancy Collaborative Network database is a living repository of IPD from randomised trials on diet and physical activity in pregnancy identified through a systematic literature search. We shall update our existing search on MEDLINE, Embase, BIOSIS, LILACS, Pascal, Science Citation Index, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects and Health Technology Assessment Database without language restriction to identify relevant trials until March 2021. Primary researchers will be invited to join the Network and share their IPD. Trials including women with GDM at baseline will be excluded. We shall perform a one and two stage random-effect meta-analysis for each intervention type (all interventions, diet-based, physical activity-based and mixed approach) to obtain summary intervention effects on GDM with 95% CIs and summary treatment–covariate interactions. Heterogeneity will be summarised using I2 and tau2 statistics with 95% prediction intervals. Publication and availability bias will be assessed by examining small study effects. Study quality of included trials will be assessed by the Cochrane Risk of Bias tool, and the Grading of Recommendations, Assessment, Development and Evaluations approach will be used to grade the evidence in the results. A model-based economic analysis will be carried out to assess the cost-effectiveness of interventions to prevent GDM and its complications compared with usual care.Ethics and disseminationEthics approval is not required. The study is registered on the International Prospective Register of Systematic Reviews (CRD42020212884). Results will be submitted for publication in peer-reviewed journals.

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