Metaforest Algorithm Insights: Predictors of Nocebo Response in ADHD

Background: Predicting the nocebo response in randomized controlled trials (RCTs) is crucial as it can help minimize its influence and improve the evaluation of the side effects of interventions for ADHD. The aim of this study is to determine the effect of covariates related to study design, intervention, and patients’ characteristics on the nocebo response in patients with Attention Deficit Hyperactivity Disorder (ADHD) using Metaforest, and, ultimately, to investigate Metaforest’s performance in predicting nocebo response in ADHD RCTs. Methods: This study is a secondary analysis of a previously published systematic review. Nocebo response was defined as the proportion of patients experiencing at least one AE while receiving a placebo. We used Metaforest for investigating patient, intervention, and study design-related nocebo response moderators in ADHD RCTs. Results: One hundred and five studies were included. Overall, 55.4% of patients experienced at least one AE while receiving placebo. However, between-study variability on nocebo response was very high, with nocebo response ranging from 4.2% to 90.2%, leading to high statistical heterogeneity (I2 = 88.3%). Older patients showed a higher nocebo response. The moderating effects of the year of publication, treatment length and gender were also significant. The predictive performance of the model was low-moderate (2 test = 0. 1922; MSE = 0. 0408). Conclusion: Age was the most important nocebo response modifier, followed by year of publication, treatment length and gender. Metaforest lacked the capability to predict nocebo responses in future studies.