University of Southampton, Southampton, UK.
Department of Biostatistics, Hospices civils de Lyon, Lyon, France.
Syst Rev. 2024 Oct 12;13(1):256. doi: 10.1186/s13643-024-02675-1.
Attention-deficit/hyperactivity disorder (ADHD) affects approximately 5% of children globally, with symptoms often persisting into adulthood. While pharmacological interventions are commonly employed for management, understanding the optimal dosing for efficacy and tolerability remains crucial. This study aims to conduct a dose-response network meta-analysis to estimate the efficacy of pharmacological treatments across different doses, aiming to inform clinical decision-making and improve treatment outcomes.
This updated systematic review will include randomized controlled trials evaluating ADHD medication efficacy in children, adolescents, and adults. An updated search from a 2018 NMA will be conducted across multiple electronic databases with no language restrictions, using specific eligibility criteria focused on randomized controlled trials. The primary outcome will assess the severity of ADHD core symptoms, while secondary outcomes will consider treatment tolerability. A dose-response Bayesian hierarchical model will be used to estimate dose-response curves for each medication, identifying optimal dosing strategies.
With this dose-response network meta-analysis, we aim to better understand the dose-response relationship of pharmacological treatment in ADHD, which could help clinician to the identification of optimal doses.
注意力缺陷多动障碍(ADHD)影响全球约 5%的儿童,其症状常持续至成年。虽然药物干预通常用于治疗,但了解疗效和耐受性的最佳剂量仍然至关重要。本研究旨在进行剂量反应网络荟萃分析,以评估不同剂量的药物治疗的疗效,旨在为临床决策提供信息并改善治疗结果。
本更新的系统评价将包括评估 ADHD 药物治疗儿童、青少年和成人疗效的随机对照试验。将对 2018 年 NMA 的更新搜索进行多电子数据库的无语言限制检索,使用特定的纳入标准,重点关注随机对照试验。主要结局将评估 ADHD 核心症状的严重程度,次要结局将考虑治疗耐受性。将使用剂量反应贝叶斯层次模型来评估每种药物的剂量反应曲线,确定最佳剂量策略。
通过这种剂量反应网络荟萃分析,我们旨在更好地了解 ADHD 药物治疗的剂量反应关系,这有助于临床医生确定最佳剂量。