Mavridis Dimitris, Nikolakopoulou Adriani, Moustaki Irini, Chaimani Anna, Porcher Raphaël, Boutron Isabelle, Ravaud Philippe
Department of Primary Education, University of Ioannina, Ioannina, Greece.
Institute for Medical Biometry and Statistics, University of Freiburg, Faculty of Medicine and Medical Center, Freiburg, Germany.
J Clin Epidemiol. 2023 Feb;154:188-196. doi: 10.1016/j.jclinepi.2022.12.025. Epub 2022 Dec 27.
Ranking metrics in network meta-analysis (NMA) are computed separately for each outcome. Our aim is to 1) present graphical ways to group competing interventions considering multiple outcomes and 2) use conjoint analysis for placing weights on the various outcomes based on the stakeholders' preferences.
We used multidimensional scaling (MDS) and hierarchical tree clustering to visualize the extent of similarity of interventions in terms of the relative effects they produce through a random effect NMA. We reanalyzed a published network of 212 psychosis trials taking three outcomes into account as follows: reduction in symptoms of schizophrenia, all-cause treatment discontinuation, and weight gain.
Conjoint analysis provides a mathematical method to transform judgements into weights that can be subsequently used to visually represent interventions on a two-dimensional plane or through a dendrogram. These plots provide insightful information about the clustering of interventions.
Grouping interventions can help decision makers not only to identify the optimal ones in terms of benefit-risk balance but also choose one from the best cluster based on other grounds, such as cost, implementation etc. Placing weights on outcomes allows considering patient profile or preferences.
网络荟萃分析（NMA）中的排序指标是针对每个结局分别计算的。我们的目标是：1）提出基于多个结局对相互竞争的干预措施进行分组的图形化方法；2）使用联合分析，根据利益相关者的偏好为各种结局赋予权重。
我们使用多维标度法（MDS）和层次树聚类法，通过随机效应NMA，根据干预措施产生的相对效应来直观呈现它们的相似程度。我们重新分析了一个已发表的包含212项精神病试验的网络，考虑了以下三个结局：精神分裂症症状减轻、全因治疗中断和体重增加。
联合分析提供了一种数学方法，可将判断转化为权重，随后可用于在二维平面上或通过树状图直观呈现干预措施。这些图表提供了有关干预措施聚类的有价值信息。
对干预措施进行分组不仅有助于决策者根据效益-风险平衡确定最佳干预措施，还能基于其他因素（如成本、实施情况等）从最佳聚类中选择一项。对结局赋予权重能够考虑患者情况或偏好。
