{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T12:01:38Z","timestamp":1790251298833,"version":"4.1.0"},"reference-count":59,"publisher":"SAGE Publications","issue":"7","license":[{"start":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T00:00:00Z","timestamp":1784851200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72174207"],"award-info":[{"award-number":["72174207"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Postgraduate Research and Practice Innovation Program of Jiangsu Province","award":["KYCX25_1070"],"award-info":[{"award-number":["KYCX25_1070"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Med Decis Making"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives:<\/jats:title>\n                    <jats:p>To systematically evaluate how survival estimates from network meta-analyses (NMA) models affect oncology cost-effectiveness analysis (CEA) results, particularly under different proportional hazards (PH) assumptions and extrapolation strategies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>A total of 19 time-to-event NMA models were evaluated in this analysis, encompassing Cox proportional hazards (Cox-PH), fractional polynomial (FP), Royston\u2013Parmar (RP) models, piecewise exponential (PWE), generalized gamma (Gengamma), and parametric survival models (PSM), with 2 extrapolation strategies for non-PH models: a constant-tail hazard ratio (Fixed-HR) and a parametric extrapolation approach (Varying-HR). NMA model performance was assessed via relative error (RE) by comparing CEA outcomes derived from NMA-based survival estimates with those from head-to-head clinical data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Fifteen CEA models were conducted. The selection of the NMA model exerted a greater influence on CEA outcomes than traditional model parameters (ie, costs or utilities). RP models appeared to perform best, while PWE, second-order FP, and Gengamma models tended to perform comparatively worse. Fixed-HR extrapolation approaches generally yielded more accurate long-term projections than Varying-HR methods did, particularly under non-PH conditions. Violations of the PH assumption substantially increased uncertainty, especially for non-PH models. Notably, the choice of NMA model led to reversals in cost-effectiveness conclusions in up to one-third of the evaluated CEA cases.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>NMA model choice substantially influences oncology CEA outcomes. Underutilized but well-performing RP models show strong potential for broader application. Fixed-HR extrapolation was preferred in our study. These findings are context specific, and further validation is needed. When PH assumption is violated, the selection of non-PH models requires greater caution. Our findings may offer insights to support future refinements in CEA methodological guidance.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/0272989x261463230","type":"journal-article","created":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T08:25:06Z","timestamp":1784881506000},"page":"923-939","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Comparing and Selecting Network Meta-Analysis Models for Cost-Effectiveness Analysis of Anticancer Drugs"],"prefix":"10.1177","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7709-9374","authenticated-orcid":false,"given":"Mingye","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Pharmacoeconomics, School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, Jiangsu, China"},{"name":"Center for Pharmacoeconomics and Outcomes Research, China Pharmaceutical University, Nanjing, Jiangsu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taihang","family":"Shao","sequence":"additional","affiliation":[{"name":"JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanqiao","family":"Shao","sequence":"additional","affiliation":[{"name":"Department of Pharmacoeconomics, School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, Jiangsu, China"},{"name":"Center for Pharmacoeconomics and Outcomes Research, China Pharmaceutical University, Nanjing, Jiangsu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Pharmacoeconomics, School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, Jiangsu, China"},{"name":"Center for Pharmacoeconomics and Outcomes Research, China Pharmaceutical University, Nanjing, Jiangsu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenxi","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Pharmacoeconomics, School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, Jiangsu, China"},{"name":"Center for Pharmacoeconomics and Outcomes Research, China Pharmaceutical University, Nanjing, Jiangsu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,7,24]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"crossref","unstructured":"Neumann PJ Sanders GD. 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