{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T12:07:56Z","timestamp":1791461276886,"version":"4.3.4"},"reference-count":33,"publisher":"Wiley","issue":"6-7","license":[{"start":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T00:00:00Z","timestamp":1772496000000},"content-version":"vor","delay-in-days":2,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>The ability to retrieve pseudo\u2010individual patient data (IPD) from published survival study results is important to facilitate meta\u2010analysis, evidence synthesis or secondary data analyses for the purpose of decision modeling for cost effectiveness analysis. While established methods exist for retrieving pseudo\u2010IPD from Kaplan\u2013Meier plots, these algorithms are not easily extendable to other types of survival data, nor do they allow all available information to be incorporated. An optimization\u2010based approach is proposed where the task of reconstructing the IPD is formulated as a quadratic program (QP) with linear constraints. The method easily allows auxiliary information such as marked censoring times. Moreover, the same approach can be used to reconstruct patient\u2010level competing risks survival data from published cumulative incidence functions. In simulation, the QP\u2010based method is shown to outperform existing algorithms particularly when data on numbers at risk and marked censoring times are available. The methods are illustrated through reconstruction of data from a published study on patients with advanced stage follicular lymphoma.<\/jats:p>","DOI":"10.1002\/sim.70474","type":"journal-article","created":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T04:12:31Z","timestamp":1773029551000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Using Quadratic Programming to Reconstruct Data From Published Survival and Competing Risks Analyses"],"prefix":"10.1002","volume":"45","author":[{"given":"Andrew C.","family":"Titman","sequence":"first","affiliation":[{"name":"School of Mathematical Sciences Lancaster University  Lancaster Lancashire UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,3,3]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.c221"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0258(19981230)17:24<2815::AID-SIM110>3.0.CO;2-8"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1186\/1745-6215-8-16"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1186\/2046-4053-3-151"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2288-11-139"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2288-12-9"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12874-021-01308-8"},{"key":"e_1_2_10_9_1","doi-asserted-by":"crossref","unstructured":"N.LiuandJ. 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