{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T11:04:21Z","timestamp":1788519861160,"version":"build-2803163510"},"reference-count":31,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2023,11,6]],"date-time":"2023-11-06T00:00:00Z","timestamp":1699228800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000272","name":"National Institute for Health and Care Research","doi-asserted-by":"publisher","award":["NIHR300984"],"award-info":[{"award-number":["NIHR300984"]}],"id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2024,1,15]]},"abstract":"<jats:p>Multi\u2010state survival models are used to represent the natural history of a disease, forming the basis of a health technology assessment comparing a novel treatment to current practice. Constructing such models for rare diseases is problematic, since evidence sources are typically much sparser and more heterogeneous. This simulation study investigated different one\u2010stage and two\u2010stage approaches to meta\u2010analyzing individual patient data (IPD) in a multi\u2010state survival setting when the number and size of studies being meta\u2010analyzed are small. The objective was to assess methods of different complexity to see when they are accurate, when they are inaccurate and when they struggle to converge due to the sparsity of data. Biologically plausible multi\u2010state IPD were simulated from study\u2010 and transition\u2010specific hazard functions. One\u2010stage frailty and two\u2010stage stratified models were estimated, and compared to a base case model that did not account for study heterogeneity. Convergence and the bias\/coverage of population\u2010level transition probabilities to, and lengths of stay in, each state were used to assess model performance. A real\u2010world application to Duchenne Muscular Dystrophy, a neuromuscular rare disease, was conducted, and a software demonstration is provided. Models not accounting for study heterogeneity were consistently out\u2010performed by two\u2010stage models. Frailty models struggled to converge, particularly in scenarios of low heterogeneity, and predictions from models that did converge were also subject to bias. Stratified models may be better suited to meta\u2010analyzing disparate sources of IPD in rare disease natural history\/economic modeling, as they converge more consistently and produce less biased predictions of lengths of stay.<\/jats:p>","DOI":"10.1002\/sim.9949","type":"journal-article","created":{"date-parts":[[2023,11,7]],"date-time":"2023-11-07T04:28:59Z","timestamp":1699331339000},"page":"184-200","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Modeling the multi\u2010state natural history of rare diseases with heterogeneous individual patient data: A simulation study"],"prefix":"10.1002","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1846-2150","authenticated-orcid":false,"given":"Jonathan","family":"Broomfield","sequence":"first","affiliation":[{"name":"Biostatistics Research Group, Department of Population Health Sciences University of Leicester  Leicester UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keith R.","family":"Abrams","sequence":"additional","affiliation":[{"name":"Department of Statistics University of Warwick  Coventry UK"},{"name":"Centre for Health Economics University of York  York UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suzanne","family":"Freeman","sequence":"additional","affiliation":[{"name":"Biostatistics Research Group, Department of Population Health Sciences University of Leicester  Leicester UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicholas","family":"Latimer","sequence":"additional","affiliation":[{"name":"School of Health and Related Research (ScHARR) University of Sheffield  Sheffield UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark J.","family":"Rutherford","sequence":"additional","affiliation":[{"name":"Biostatistics Research Group, Department of Population Health Sciences University of Leicester  Leicester UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael J.","family":"Crowther","sequence":"additional","affiliation":[{"name":"Red Door Analytics  Stockholm Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"Project HERCULES, the Cooperative International Neuromuscular Research Group investigators and Duchenne Regulatory Science Consortium members","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,11,6]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1532-5415.2010.02760.x"},{"key":"e_1_2_10_3_1","article-title":"NICE DSU technical support document 5: evidence synthesis in the baseline natural history model","author":"Dias S","year":"2011","journal-title":"Natl Inst Health Care Excell"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1177\/0962280209359862"},{"key":"e_1_2_10_5_1","unstructured":"LairdA HubbardR InoueL.Multi\u2010state models for natural history of disease. UW Biostatistics Working Paper Series.2013Working Paper 399."},{"issue":"8","key":"e_1_2_10_6_1","first-page":"IV3","article-title":"Overview of the SEER\u2010medicare data: content, research applications, and generalizability to the United States elderly population","volume":"40","author":"Warren J","year":"2002","journal-title":"Med Care"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1470-2045(11)70250-9"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1177\/1758835920932674"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1177\/0272989X13509406"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1177\/107327480701400209"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1177\/0962280220921889"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1214\/088342304000000305"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1177\/0962280211424665"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.2050"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2288-12-34"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.4054\/DemRes.2014.30.58"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.6191"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12913-020-05294-3"},{"issue":"2","key":"e_1_2_10_19_1","first-page":"1","article-title":"Nonparametric analysis of nonhomogeneous multistate processes with clustered observations","volume":"77","author":"Bakoyannis G","year":"2020","journal-title":"Biometrics"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.8663"},{"key":"e_1_2_10_21_1","first-page":"96","article-title":"Multilevel models for survival analysis with random effects","volume":"57","author":"Yau K","year":"2001","journal-title":"Biom J"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1177\/1536867X20976311"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.2147\/CEOR.S135445"},{"key":"e_1_2_10_24_1","unstructured":"C\u2010Path.Duchenne Regulatory Science Consortium.https:\/\/c\u2010path.org\/programs\/d\u2010rsc\/2017."},{"key":"e_1_2_10_25_1","first-page":"783","article-title":"The six\u2010minute walk test","volume":"48","author":"Enright P","year":"2003","journal-title":"Resp Care"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000012910"},{"key":"e_1_2_10_27_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.8086"},{"key":"e_1_2_10_28_1","doi-asserted-by":"publisher","DOI":"10.5435\/00124635-200203000-00009"},{"key":"e_1_2_10_29_1","doi-asserted-by":"publisher","DOI":"10.1002\/ana.25101"},{"key":"e_1_2_10_30_1","doi-asserted-by":"publisher","DOI":"10.1177\/1536867X221083853"},{"key":"e_1_2_10_31_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.7448"},{"key":"e_1_2_10_32_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4172"}],"container-title":["Statistics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/sim.9949","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,3]],"date-time":"2024-01-03T09:39:20Z","timestamp":1704274760000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/sim.9949"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,6]]},"references-count":31,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1,15]]}},"alternative-id":["10.1002\/sim.9949"],"URL":"https:\/\/doi.org\/10.1002\/sim.9949","archive":["Portico"],"relation":{},"ISSN":["0277-6715","1097-0258"],"issn-type":[{"value":"0277-6715","type":"print"},{"value":"1097-0258","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,6]]},"assertion":[{"value":"2023-03-13","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-10-16","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-11-06","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}