{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T14:12:49Z","timestamp":1785420769227,"version":"3.56.0"},"reference-count":25,"publisher":"Cambridge University Press (CUP)","issue":"2","license":[{"start":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T00:00:00Z","timestamp":1762992000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000092","name":"U.S. National Library of Medicine","doi-asserted-by":"publisher","award":["R21LM014534"],"award-info":[{"award-number":["R21LM014534"]}],"id":[{"id":"10.13039\/100000092","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006545","name":"National Institute on Minority Health and Health Disparities","doi-asserted-by":"publisher","award":["U24MD020517"],"award-info":[{"award-number":["U24MD020517"]}],"id":[{"id":"10.13039\/100006545","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Res. synth. methods"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Ranking multiple interventions is a crucial task in network meta-analysis (NMA) to guide clinical and policy decisions. However, conventional ranking methods often oversimplify treatment distinctions, potentially yielding misleading conclusions due to inherent uncertainty in relative intervention effects. To address these limitations, we propose a novel Bayesian rank-clustering estimation approach, termed rank-clustering estimation (RaCE), specifically developed for NMA. Rather than identifying a single \u201cbest\u201d intervention, RaCE enables the probabilistic clustering of interventions with similar effectiveness, offering a more nuanced and parsimonious interpretation. By decoupling the clustering procedure from the NMA modeling process, RaCE is a flexible and broadly applicable approach that can accommodate different types of outcomes (binary, continuous, and survival), modeling approaches (arm-based and contrast-based), and estimation frameworks (frequentist or Bayesian). Simulation studies demonstrate that RaCE effectively captures rank-clusters even under conditions of substantial uncertainty and overlapping intervention effects, providing more reasonable result interpretation than traditional single-ranking methods. We illustrate the practical utility of RaCE through an NMA application to frontline immunochemotherapies for follicular lymphoma, revealing clinically relevant clusters among treatments previously assumed to have distinct ranks. Overall, RaCE provides a valuable tool for researchers to enhance rank estimation and interpretability, facilitating evidence-based decision-making in complex intervention landscapes.<\/jats:p>","DOI":"10.1017\/rsm.2025.10049","type":"journal-article","created":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T07:44:58Z","timestamp":1763019898000},"page":"314-331","source":"Crossref","is-referenced-by-count":2,"title":["RaCE: A rank-clustering estimation method for network meta-analysis"],"prefix":"10.1017","volume":"17","author":[{"given":"Michael","family":"Pearce","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00a6ram87","id-type":"ROR","asserted-by":"publisher"}],"name":"Reed College"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8124-5047","authenticated-orcid":false,"given":"Shouhao","family":"Zhou","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04p491231","id-type":"ROR","asserted-by":"publisher"}],"name":"Pennsylvania State University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2025,11,13]]},"reference":[{"key":"S1759287925100495_r2","first-page":"451","article-title":"Bias in identification of the best treatment in a Bayesian network meta-analysis for binary outcome: A simulation study","volume":"6","author":"Kibret","year":"2014","journal-title":"Clin Epidemiol."},{"key":"S1759287925100495_r10","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2018.02.009"},{"key":"S1759287925100495_r25","doi-asserted-by":"publisher","DOI":"10.51387\/24-NEJSDS62"},{"key":"S1759287925100495_r3","doi-asserted-by":"publisher","DOI":"10.1002\/jrsm.1454"},{"key":"S1759287925100495_r13","doi-asserted-by":"publisher","DOI":"10.1002\/sim.10253"},{"key":"S1759287925100495_r18","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-024-10555-w"},{"key":"S1759287925100495_r14","doi-asserted-by":"publisher","DOI":"10.1093\/jrsssc\/qlae038"},{"key":"S1759287925100495_r8","doi-asserted-by":"publisher","DOI":"10.7326\/M14-2385"},{"key":"S1759287925100495_r12","unstructured":"[12] Ciulei, MA , Zhou, S , Gallagher, K , et al. The effect of balanced energy-protein supplementation provided to lactating women on maternal and infant outcomes: study protocol for a prospectively planned individual patient data (IPD) meta-analysis. medRxiv 2023. 2023\u201311."},{"key":"S1759287925100495_r1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jval.2014.01.004"},{"key":"S1759287925100495_r15","doi-asserted-by":"publisher","DOI":"10.1214\/12-AOAS581"},{"key":"S1759287925100495_r23","doi-asserted-by":"publisher","DOI":"10.1201\/b16018"},{"key":"S1759287925100495_r17","doi-asserted-by":"publisher","DOI":"10.1111\/rssa.12124"},{"key":"S1759287925100495_r6","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0076654"},{"key":"S1759287925100495_r11","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-159-2-201307160-00008"},{"key":"S1759287925100495_r9","doi-asserted-by":"publisher","DOI":"10.7326\/M15-2521"},{"key":"S1759287925100495_r22","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/82.4.711"},{"key":"S1759287925100495_r4","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2010.03.016"},{"key":"S1759287925100495_r16","doi-asserted-by":"publisher","DOI":"10.1007\/s10182-014-0237-1"},{"key":"S1759287925100495_r24","doi-asserted-by":"publisher","DOI":"10.1002\/jrsm.1377"},{"key":"S1759287925100495_r7","unstructured":"[7] Higgins, JPT , Thomas, J , Chandler, J , et al. Cochrane handbook for systematic reviews of interventions version 6.5. 2024. 2024. https:\/\/www.training.cochrane.org\/handbook"},{"key":"S1759287925100495_r19","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/44.1-2.114"},{"key":"S1759287925100495_r20","doi-asserted-by":"publisher","DOI":"10.1017\/psy.2025.10014"},{"key":"S1759287925100495_r5","doi-asserted-by":"publisher","DOI":"10.1186\/s13643-017-0473-z"},{"key":"S1759287925100495_r21","doi-asserted-by":"publisher","DOI":"10.1038\/s41408-021-00598-x"}],"container-title":["Research Synthesis Methods"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S1759287925100495","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T09:20:33Z","timestamp":1770196833000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S1759287925100495\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,13]]},"references-count":25,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["S1759287925100495"],"URL":"https:\/\/doi.org\/10.1017\/rsm.2025.10049","relation":{},"ISSN":["1759-2879","1759-2887"],"issn-type":[{"value":"1759-2879","type":"print"},{"value":"1759-2887","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,13]]}}}