Precision of Treatment Hierarchy: A Metric for Quantifying Certainty in Treatment Hierarchies From Network Meta‐Analysis

作者：Augustine Wigle, Audrey Béliveau, Georgia Salanti, Gerta Rücker, Guido Schwarzer, Dimitris Mavridis, Adriani Nikolakopoulou · 发表于：Statistics in Medicine · 年份：2025 · DOI：10.1002/sim.70176 · 被引用次数：3 · 研究领域：Meta-analysis and systematic reviews、scientometrics and bibliometrics research、Statistical Methods in Clinical Trials

Network meta-analysis (NMA) is an extension of pairwise meta-analysis that facilitates the estimation of relative effects for multiple competing treatments. A hierarchy of treatments is a useful output of an NMA. Treatment hierarchies are produced using ranking metrics. Common ranking metrics include the Surface Under the Cumulative RAnking curve (SUCRA) and P-scores, which are the frequentist analogue to SUCRAs. Both metrics consider the size and uncertainty of the estimated treatment effects, with larger values indicating a more preferred treatment. Although SUCRAs and P-scores themselves consider uncertainty, treatment hierarchies produced by these ranking metrics are typically reported without a measure of certainty, which might be misleading to practitioners. We propose a new metric, Precision of Treatment Hierarchy (POTH), which quantifies the certainty in producing a treatment hierarchy from SUCRAs or P-scores. The metric connects three statistical quantities: The variance of the SUCRA values, the variance of the mean rank of each treatment, and the average variance of the distribution of individual ranks for each treatment. POTH provides a single, interpretable value that quantifies the extent of certainty in producing a treatment hierarchy. We show how the metric can be adapted to apply to subsets of treatments in a network, for example, to quantify the certainty in the hierarchy of the top three treatments. We calculate POTH for a database of NMAs to investigate its...