{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T12:45:57Z","timestamp":1788871557006,"version":"build-2803163510"},"reference-count":32,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["MR\/W021102\/1"],"award-info":[{"award-number":["MR\/W021102\/1"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Res. synth. methods"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>A growing number of oncology treatments, such as bevacizumab, are used across multiple indications. However, in health technology assessment (HTA), their clinical and cost-effectiveness are typically appraised within a single target indication. This approach excludes a broader evidence base across other indications. To address this, we explored multi-indication meta-analysis methods that share evidence across indications.<\/jats:p>\n                  <jats:p>We conducted a simulation study to evaluate alternative multi-indication synthesis models. This included univariate (mixture and non-mixture) methods synthesizing overall survival (OS) data and bivariate surrogacy models jointly modeling treatment effects on progression-free survival (PFS) and OS, pooling surrogacy parameters across indications. Simulated datasets were generated using a multistate disease progression model under various scenarios, including different levels of heterogeneity within and between indications, outlier indications, and varying data on OS for the target indication. We evaluated the performance of the synthesis models applied to the simulated datasets in terms of their ability to predict OS in a target indication.<\/jats:p>\n                  <jats:p>The results showed univariate multi-indication methods could reduce uncertainty without increasing bias, particularly when OS data were available in the target indication. Compared with univariate methods, mixture models did not significantly improve performance and are not recommended for HTA. In scenarios where OS data in the target indication is absent and there are also outlier indications, bivariate surrogacy models showed promise in correcting bias relative to univariate models, though further research under realistic conditions is needed.<\/jats:p>\n                  <jats:p>Multi-indication methods are more complex than traditional approaches but can potentially reduce uncertainty in HTA decisions.<\/jats:p>","DOI":"10.1017\/rsm.2025.10037","type":"journal-article","created":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T05:33:32Z","timestamp":1759296812000},"page":"93-110","source":"Crossref","is-referenced-by-count":1,"title":["Methods of multi-indication meta-analysis for health technology assessment: A simulation study"],"prefix":"10.1017","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0989-1984","authenticated-orcid":false,"given":"David","family":"Glynn","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03bea9k73","id-type":"ROR","asserted-by":"publisher"}],"name":"University of Galway"},{"id":[{"id":"https:\/\/ror.org\/03bea9k73","id-type":"ROR","asserted-by":"publisher"}],"name":"University of Galway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9063-8590","authenticated-orcid":false,"given":"Pedro","family":"Saramago","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04m01e293","id-type":"ROR","asserted-by":"publisher"}],"name":"University of York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Janharpreet","family":"Singh","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04h699437","id-type":"ROR","asserted-by":"publisher"}],"name":"University of Leicester"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3003-9403","authenticated-orcid":false,"given":"Sylwia","family":"Bujkiewicz","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04h699437","id-type":"ROR","asserted-by":"publisher"}],"name":"University of Leicester"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2172-0221","authenticated-orcid":false,"given":"Sofia","family":"Dias","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04m01e293","id-type":"ROR","asserted-by":"publisher"}],"name":"University of York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steve","family":"Palmer","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04m01e293","id-type":"ROR","asserted-by":"publisher"}],"name":"University of York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1579-8513","authenticated-orcid":false,"given":"Marta Ferreira Oliveira","family":"Soares","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04m01e293","id-type":"ROR","asserted-by":"publisher"}],"name":"University of York"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2025,10,1]]},"reference":[{"key":"S1759287925100379_r31","first-page":"1","article-title":"NICE DSU technical support document 26: expert elicitation for long-term survival outcomes","author":"Oakley","year":"2025","journal-title":"NICE Decision Support Unit Technical Support Document Series"},{"key":"S1759287925100379_r11","doi-asserted-by":"publisher","DOI":"10.1002\/sim.7991"},{"key":"S1759287925100379_r14","unstructured":"[14] R Package \u2018gsDesign\u2019. Version 3.6.5. 2024. https:\/\/cran.r-project.org\/web\/packages\/gsDesign\/index.html."},{"key":"S1759287925100379_r2","doi-asserted-by":"publisher","DOI":"10.1186\/s12874-021-01292-z"},{"key":"S1759287925100379_r17","first-page":"e076316","article-title":"The estimands framework: a primer on the ICH E9 (R1) addendum","volume":"384","author":"Kahan","year":"2023","journal-title":"BMJ"},{"key":"S1759287925100379_r21","doi-asserted-by":"publisher","DOI":"10.1201\/9780429258411"},{"key":"S1759287925100379_r27","doi-asserted-by":"publisher","DOI":"10.1002\/pst.1730"},{"key":"S1759287925100379_r7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jval.2020.08.2094"},{"key":"S1759287925100379_r32","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06054-z"},{"key":"S1759287925100379_r3","doi-asserted-by":"publisher","DOI":"10.1177\/0272989X241295665"},{"key":"S1759287925100379_r1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ctrv.2020.102017"},{"key":"S1759287925100379_r20","unstructured":"[20] rjags: Bayesian graphical models using MCMC. 2023. https:\/\/CRAN.R-project.org\/package=rjags."},{"key":"S1759287925100379_r4","unstructured":"[4] Bujkiewicz, S , Achana, F , Papanikos, T , Riley, R , Abrams, K. NICE DSU technical support document 20: multivariate meta-analysis of summary data for combining treatment effects on correlated outcomes and evaluating surrogate endpoints. 2019. https:\/\/www.sheffield.ac.uk\/nice-dsu\/tsds\/full-list."},{"key":"S1759287925100379_r18","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780100510"},{"key":"S1759287925100379_r9","doi-asserted-by":"publisher","DOI":"10.1002\/sim.9810"},{"key":"S1759287925100379_r5","doi-asserted-by":"publisher","DOI":"10.1002\/bimj.70017"},{"key":"S1759287925100379_r16","doi-asserted-by":"publisher","DOI":"10.1177\/00031224211004187"},{"key":"S1759287925100379_r26","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12242"},{"key":"S1759287925100379_r6","doi-asserted-by":"publisher","DOI":"10.1007\/s40258-019-00513-3"},{"key":"S1759287925100379_r22","volume-title":"Borrowing Strength Fromindirect\u2019evidence: Methods and Policy Implications for Health Technology Assessment","author":"Nikolaidis","year":"2020"},{"key":"S1759287925100379_r19","doi-asserted-by":"publisher","DOI":"10.1080\/10543406.2020.1815035"},{"key":"S1759287925100379_r15","unstructured":"[15] simIDM: simulating oncology trials using an illness-death model. 2023. https:\/\/CRAN.R-project.org\/package=simIDM."},{"key":"S1759287925100379_r10","doi-asserted-by":"publisher","DOI":"10.1002\/sim.8001"},{"key":"S1759287925100379_r25","doi-asserted-by":"publisher","DOI":"10.1177\/0272989X221117162"},{"key":"S1759287925100379_r23","doi-asserted-by":"publisher","DOI":"10.1002\/sim.8465"},{"key":"S1759287925100379_r8","doi-asserted-by":"publisher","DOI":"10.1038\/s41416-022-01904-5"},{"key":"S1759287925100379_r29","doi-asserted-by":"publisher","DOI":"10.1016\/j.jval.2023.03.1470"},{"key":"S1759287925100379_r24","doi-asserted-by":"publisher","DOI":"10.1177\/0272989X20983315"},{"key":"S1759287925100379_r13","doi-asserted-by":"publisher","DOI":"10.1002\/sim.8086"},{"key":"S1759287925100379_r12","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0258(19970915)16:17<1965::AID-SIM630>3.0.CO;2-M"},{"key":"S1759287925100379_r30","doi-asserted-by":"publisher","DOI":"10.1016\/j.jval.2020.03.010"},{"key":"S1759287925100379_r28","doi-asserted-by":"publisher","DOI":"10.1016\/j.jval.2020.10.016"}],"container-title":["Research Synthesis Methods"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S1759287925100379","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T10:30:32Z","timestamp":1767954632000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S1759287925100379\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,1]]},"references-count":32,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["S1759287925100379"],"URL":"https:\/\/doi.org\/10.1017\/rsm.2025.10037","relation":{},"ISSN":["1759-2879","1759-2887"],"issn-type":[{"value":"1759-2879","type":"print"},{"value":"1759-2887","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,1]]}}}