{"id":"https://openalex.org/W4405375153","doi":"https://doi.org/10.1038/s42256-024-00932-5","title":"Stable Cox regression for survival analysis under distribution shifts","display_name":"Stable Cox regression for survival analysis under distribution shifts","publication_year":2024,"publication_date":"2024-12-13","ids":{"openalex":"https://openalex.org/W4405375153","doi":"https://doi.org/10.1038/s42256-024-00932-5"},"language":"en","primary_location":{"id":"doi:10.1038/s42256-024-00932-5","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s42256-024-00932-5","pdf_url":null,"source":{"id":"https://openalex.org/S2912241403","display_name":"Nature Machine Intelligence","issn_l":"2522-5839","issn":["2522-5839"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nature Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1038/s42256-024-00932-5","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028965727","display_name":"Shaohua Fan","orcid":"https://orcid.org/0000-0002-1224-4243"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohua Fan","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061888153","display_name":"Renzhe Xu","orcid":"https://orcid.org/0000-0001-8418-0034"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renzhe Xu","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8418-0034","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102003332","display_name":"Qian Dong","orcid":"https://orcid.org/0000-0002-1038-2116"},"institutions":[{"id":"https://openalex.org/I4210149540","display_name":"Beijing Proteome Research Center","ror":"https://ror.org/05pp5b412","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210149540"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Dong","raw_affiliation_strings":["State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China","institution_ids":["https://openalex.org/I4210149540"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101790420","display_name":"Yue He","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue He","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041872254","display_name":"Cheng Chang","orcid":"https://orcid.org/0000-0002-0361-2438"},"institutions":[{"id":"https://openalex.org/I4210149540","display_name":"Beijing Proteome Research Center","ror":"https://ror.org/05pp5b412","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210149540"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Cheng Chang","raw_affiliation_strings":["State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0361-2438","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China","institution_ids":["https://openalex.org/I4210149540"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009228005","display_name":"Peng Cui","orcid":"https://orcid.org/0000-0003-2957-8511"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peng Cui","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2957-8511","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5009228005","https://openalex.org/A5041872254"],"corresponding_institution_ids":["https://openalex.org/I4210149540","https://openalex.org/I99065089"],"apc_list":{"value":9750,"currency":"EUR","value_usd":11690},"apc_paid":{"value":9750,"currency":"EUR","value_usd":11690},"fwci":10.7811,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.98993929,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"6","issue":"12","first_page":"1525","last_page":"1541"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11829","display_name":"Mathematical Biology Tumor Growth","score":0.9081000089645386,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.6193907856941223},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.5725276470184326},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5716136693954468},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5643901824951172},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.49561870098114014},{"id":"https://openalex.org/keywords/survival-analysis","display_name":"Survival analysis","score":0.41201069951057434},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29218626022338867},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.05367898941040039}],"concepts":[{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.6193907856941223},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.5725276470184326},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5716136693954468},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5643901824951172},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.49561870098114014},{"id":"https://openalex.org/C10515644","wikidata":"https://www.wikidata.org/wiki/Q543310","display_name":"Survival analysis","level":2,"score":0.41201069951057434},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29218626022338867},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.05367898941040039}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1038/s42256-024-00932-5","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s42256-024-00932-5","pdf_url":null,"source":{"id":"https://openalex.org/S2912241403","display_name":"Nature Machine Intelligence","issn_l":"2522-5839","issn":["2522-5839"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nature Machine Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1038/s42256-024-00932-5","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s42256-024-00932-5","pdf_url":null,"source":{"id":"https://openalex.org/S2912241403","display_name":"Nature Machine Intelligence","issn_l":"2522-5839","issn":["2522-5839"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nature Machine Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W91088564","https://openalex.org/W1986705681","https://openalex.org/W2003942385","https://openalex.org/W2005895632","https://openalex.org/W2006623746","https://openalex.org/W2009671859","https://openalex.org/W2012658469","https://openalex.org/W2020773640","https://openalex.org/W2020839350","https://openalex.org/W2042296356","https://openalex.org/W2052825782","https://openalex.org/W2093774991","https://openalex.org/W2094229819","https://openalex.org/W2095463689","https://openalex.org/W2099620796","https://openalex.org/W2106161928","https://openalex.org/W2107429737","https://openalex.org/W2108900994","https://openalex.org/W2128985829","https://openalex.org/W2129925362","https://openalex.org/W2135518010","https://openalex.org/W2136916987","https://openalex.org/W2137960802","https://openalex.org/W2149199519","https://openalex.org/W2156918287","https://openalex.org/W2157076315","https://openalex.org/W2288728207","https://openalex.org/W2299181842","https://openalex.org/W2324488473","https://openalex.org/W2324805613","https://openalex.org/W2330284382","https://openalex.org/W2395887422","https://openalex.org/W2557509406","https://openalex.org/W2603756957","https://openalex.org/W2761575992","https://openalex.org/W2767965002","https://openalex.org/W2807992610","https://openalex.org/W2809450446","https://openalex.org/W2885707361","https://openalex.org/W2893897533","https://openalex.org/W2896467275","https://openalex.org/W2912137016","https://openalex.org/W2918023653","https://openalex.org/W2951209146","https://openalex.org/W2963232127","https://openalex.org/W2977971148","https://openalex.org/W2991341799","https://openalex.org/W2997591099","https://openalex.org/W2997746169","https://openalex.org/W3041564249","https://openalex.org/W3103558512","https://openalex.org/W3122812581","https://openalex.org/W3147894994","https://openalex.org/W4213447687","https://openalex.org/W4221077687","https://openalex.org/W4241664300","https://openalex.org/W4387250121","https://openalex.org/W6967948091"],"related_works":["https://openalex.org/W2797301068","https://openalex.org/W2010631330","https://openalex.org/W2006470775","https://openalex.org/W2581226876","https://openalex.org/W4225134093","https://openalex.org/W4380269519","https://openalex.org/W3136232645","https://openalex.org/W4380448775","https://openalex.org/W1554732404","https://openalex.org/W2387623956"],"abstract_inverted_index":{"Survival":[0,149],"analysis":[1,65],"aims":[2],"to":[3,94],"estimate":[4],"the":[5,10,139,145],"impact":[6],"of":[7,141],"covariates":[8],"on":[9,79,115],"expected":[11],"time":[12],"until":[13],"an":[14,101],"event":[15],"occurs,":[16],"which":[17,98,166],"is":[18,167],"broadly":[19],"utilized":[20],"in":[21,153,170],"disciplines":[22],"such":[23],"as":[24],"life":[25],"sciences":[26],"and":[27,32,42,106,117,120,159,174],"healthcare,":[28],"substantially":[29],"influencing":[30],"decision-making":[31],"improving":[33],"survival":[34,64,189],"outcomes.":[35],"Existing":[36],"methods,":[37],"usually":[38,155],"assuming":[39],"similar":[40,164],"training":[41,158],"testing":[43],"distributions,":[44],"nevertheless":[45],"face":[46],"challenges":[47],"with":[48,91,144],"real-world":[49,118,171],"varying":[50],"data":[51,161],"sources,":[52],"creating":[53],"unpredictable":[54],"shifts":[55],"that":[56,63,157,182],"undermine":[57],"their":[58],"reliability.":[59],"This":[60],"urgently":[61],"necessitates":[62],"methods":[66],"should":[67],"utilize":[68],"stable":[69,88,96,123,178,185],"features":[70],"across":[71,131],"diverse":[72,132],"cohorts":[73],"for":[74,187],"predictions,":[75],"rather":[76],"than":[77],"relying":[78],"spurious":[80],"correlations.":[81],"To":[82],"this":[83],"end,":[84],"we":[85],"propose":[86],"a":[87,107,163,177],"Cox":[89,109,124,179],"model":[90,181],"theoretical":[92],"guarantees":[93],"identify":[95,184],"variables,":[97],"jointly":[99],"optimizes":[100],"independence-driven":[102],"sample":[103],"reweighting":[104],"module":[105],"weighted":[108],"regression":[110,180],"model.":[111],"Through":[112],"extensive":[113],"evaluation":[114],"simulated":[116],"omics":[119],"clinical":[121],"data,":[122],"not":[125,168],"only":[126],"shows":[127],"strong":[128],"generalization":[129],"ability":[130],"independent":[133],"test":[134,160],"sets":[135],"but":[136],"also":[137],"stratifies":[138],"subtype":[140],"patients":[142],"significantly":[143],"identified":[146],"biomarker":[147],"panels.":[148],"prediction":[150],"models":[151],"used":[152],"healthcare":[154],"assume":[156],"share":[162],"distribution,":[165],"true":[169],"settings.":[172],"Cui":[173],"colleagues":[175],"develop":[176],"can":[183],"variables":[186],"predicting":[188],"outcomes":[190],"under":[191],"distribution":[192],"shifts.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}