Estimating Additive Interaction in Two-Stage Individual Participant Data Meta-Analysis.
The researchers aimed to describe how the Relative Excess Risk due to Interaction (RERI) and other measures of additive interaction or effect modification can be validly estimated within two-stage individual participant data (IPD) meta-analysis. They proposed a three-step procedure to estimate additive interaction, and illustrate this procedure by investigating interaction between depression and smoking and risk of smoking-related cancers incidence during follow-up, and used IPD of six cohorts, including CARTaGENE.
Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis
Researchers determined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Data were used from 22 cohorts, including the Ontario Health Study, Atlantic Partnership for Tomorrow’s Health, and CARTaGENE. After exploring 744 combinations of psychosocial factors, the researchers found no evidence that psychosocial factors interacted with or modified health behaviors related to cancer incidence.