{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T08:10:28Z","timestamp":1790151028391,"version":"4.0.1"},"reference-count":42,"publisher":"Wiley","issue":"20-22","license":[{"start":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T00:00:00Z","timestamp":1788652800000},"content-version":"vor","delay-in-days":5,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20241363"],"award-info":[{"award-number":["BK20241363"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12501407"],"award-info":[{"award-number":["12501407"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82373682"],"award-info":[{"award-number":["82373682"]}],"id":[{"id":"10.13039\/501100001809","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":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>With the rapid advancement of high\u2010throughput technologies, feature screening methods have attracted increasing attention for analyzing ultra\u2010high\u2010dimensional data. Motivated by the widespread availability of meaningful grouping structures in biomedical applications, such as brain imaging and gene expression studies, we propose a novel group\u2010structure\u2010guided (GSG) feature screening method for survival outcomes. The proposed approach incorporates prior grouping information among predictors and accommodates both disjoint and overlapping group structures. Furthermore, a combined GSG (C\u2010GSG) extension is developed to integrate multiple grouping schemes. We establish the sure screening properties of the proposed procedures and demonstrate through extensive simulation studies that incorporating informative group structures can improve screening performance, particularly under challenging censoring scenarios. The proposed method is further applied to a TCGA breast cancer dataset, where pathway information is utilized to identify genes associated with patient survival outcomes.<\/jats:p>","DOI":"10.1002\/sim.70725","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T03:07:10Z","timestamp":1788750430000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Group Structure Guided Ultra\u2010High Dimensional Feature Screening for Survival Outcome"],"prefix":"10.1002","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6261-5487","authenticated-orcid":false,"given":"Jie","family":"He","sequence":"first","affiliation":[{"name":"School of Mathematics Nanjing University of Aeronautics and Astronautics  Nanjing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiyu","family":"Li","sequence":"additional","affiliation":[{"name":"Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences  Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3658-8147","authenticated-orcid":false,"given":"Yan","family":"Hou","sequence":"additional","affiliation":[{"name":"Department of Biostatistics School of Public Health, Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,6]]},"reference":[{"key":"e_1_2_13_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"e_1_2_13_3_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214501753382273"},{"key":"e_1_2_13_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2005.00503.x"},{"key":"e_1_2_13_5_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214506000000735"},{"key":"e_1_2_13_6_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/asm037"},{"key":"e_1_2_13_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2008.00674.x"},{"key":"e_1_2_13_8_1","first-page":"2013","article-title":"Ultrahigh Dimensional Feature Selection: Beyond the Linear Model","volume":"10","author":"Fan J.","year":"2009","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_2_13_9_1","doi-asserted-by":"publisher","DOI":"10.1214\/10-AOS798"},{"key":"e_1_2_13_10_1","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2011.tm09779"},{"key":"e_1_2_13_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmva.2011.08.002"},{"key":"e_1_2_13_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2012.01039.x"},{"key":"e_1_2_13_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2015.1092974"},{"key":"e_1_2_13_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10985-016-9387-7"},{"key":"e_1_2_13_15_1","first-page":"799","article-title":"Censored Rank Independence Screening for High\u2010Dimensional Survival Data","volume":"4","author":"Rui S.","year":"2014","journal-title":"Biometrika"},{"key":"e_1_2_13_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-016-9664-z"},{"key":"e_1_2_13_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2016.11.005"},{"key":"e_1_2_13_18_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2014.920256"},{"key":"e_1_2_13_19_1","doi-asserted-by":"publisher","DOI":"10.1111\/rssb.12127"},{"key":"e_1_2_13_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2018.09.001"},{"key":"e_1_2_13_21_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/asx052"},{"key":"e_1_2_13_22_1","doi-asserted-by":"publisher","DOI":"10.1080\/24754269.2019.1633763"},{"key":"e_1_2_13_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2019.106894"},{"key":"e_1_2_13_24_1","doi-asserted-by":"publisher","DOI":"10.1080\/03610918.2019.1691223"},{"key":"e_1_2_13_25_1","doi-asserted-by":"publisher","DOI":"10.1080\/00949655.2021.1981901"},{"key":"e_1_2_13_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmva.2024.105360"},{"key":"e_1_2_13_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2021.107369"},{"issue":"4","key":"e_1_2_13_28_1","first-page":"2095","article-title":"Prior Knowledge Guided Ultra\u2010High Dimensional Variable Screening With Application to Neuroimaging Data","volume":"32","author":"He J.","year":"2022","journal-title":"Statistica Sinica"},{"key":"e_1_2_13_29_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMsr1501341"},{"key":"e_1_2_13_30_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2014.57.1414"},{"key":"e_1_2_13_31_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.569"},{"key":"e_1_2_13_32_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng1902"},{"key":"e_1_2_13_33_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature06337"},{"key":"e_1_2_13_34_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrm3047"},{"issue":"11","key":"e_1_2_13_35_1","first-page":"1200","article-title":"DNA\u2010Repair Genetic Polymorphisms and Breast Cancer Risk","volume":"12","author":"Smith T. R.","year":"2003","journal-title":"Cancer Epidemiology, Biomarkers & Prevention"},{"key":"e_1_2_13_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mam.2007.04.005"},{"key":"e_1_2_13_37_1","doi-asserted-by":"publisher","DOI":"10.1038\/ncb2897"},{"key":"e_1_2_13_38_1","doi-asserted-by":"publisher","DOI":"10.1017\/S1462399408000744"},{"key":"e_1_2_13_39_1","doi-asserted-by":"publisher","DOI":"10.1038\/ni1102-991"},{"key":"e_1_2_13_40_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrc2483"},{"key":"e_1_2_13_41_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamaoncol.2015.1428"},{"key":"e_1_2_13_42_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrc3181"},{"key":"e_1_2_13_43_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.2563"}],"container-title":["Statistics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/sim.70725","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/sim.70725","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/sim.70725","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T07:44:31Z","timestamp":1790149471000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/sim.70725"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":42,"journal-issue":{"issue":"20-22","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["10.1002\/sim.70725"],"URL":"https:\/\/doi.org\/10.1002\/sim.70725","archive":["Portico"],"relation":{},"ISSN":["0277-6715","1097-0258"],"issn-type":[{"value":"0277-6715","type":"print"},{"value":"1097-0258","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"2025-11-21","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-18","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-09-06","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70725"}}