{"id":"https://openalex.org/W4417035735","doi":"https://doi.org/10.1093/jamia/ocaf204","title":"Scalable confounding adjustment in real-world evidence: benchmarking data-adaptive and investigator-specified strategies in a large-scale trial emulation study","display_name":"Scalable confounding adjustment in real-world evidence: benchmarking data-adaptive and investigator-specified strategies in a large-scale trial emulation study","publication_year":2025,"publication_date":"2025-11-12","ids":{"openalex":"https://openalex.org/W4417035735","doi":"https://doi.org/10.1093/jamia/ocaf204","pmid":"https://pubmed.ncbi.nlm.nih.gov/41338229"},"language":"en","primary_location":{"id":"doi:10.1093/jamia/ocaf204","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocaf204","pdf_url":null,"source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090947431","display_name":"Andrew R. Weckstein","orcid":"https://orcid.org/0000-0002-6227-6796"},"institutions":[{"id":"https://openalex.org/I1283280774","display_name":"Brigham and Women's Hospital","ror":"https://ror.org/04b6nzv94","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283280774","https://openalex.org/I48633490"]},{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andrew R Weckstein","raw_affiliation_strings":["Department of Epidemiology, Harvard T.H. Chan School of Public Health , Boston, MA 02115,","Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, MA 02120,","Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, United States","Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States"],"raw_orcid":"https://orcid.org/0000-0002-6227-6796","affiliations":[{"raw_affiliation_string":"Department of Epidemiology, Harvard T.H. Chan School of Public Health , Boston, MA 02115,","institution_ids":["https://openalex.org/I136199984"]},{"raw_affiliation_string":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, MA 02120,","institution_ids":["https://openalex.org/I1283280774"]},{"raw_affiliation_string":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, United States","institution_ids":["https://openalex.org/I1283280774"]},{"raw_affiliation_string":"Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041217714","display_name":"Shirley Wang","orcid":"https://orcid.org/0000-0001-7761-7090"},"institutions":[{"id":"https://openalex.org/I1283280774","display_name":"Brigham and Women's Hospital","ror":"https://ror.org/04b6nzv94","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283280774","https://openalex.org/I48633490"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shirley V Wang","raw_affiliation_strings":["Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, MA 02120,","Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, United States"],"raw_orcid":"https://orcid.org/0000-0001-7761-7090","affiliations":[{"raw_affiliation_string":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, MA 02120,","institution_ids":["https://openalex.org/I1283280774"]},{"raw_affiliation_string":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, United States","institution_ids":["https://openalex.org/I1283280774"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022053891","display_name":"Richard Wyss","orcid":null},"institutions":[{"id":"https://openalex.org/I1283280774","display_name":"Brigham and Women's Hospital","ror":"https://ror.org/04b6nzv94","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283280774","https://openalex.org/I48633490"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Richard Wyss","raw_affiliation_strings":["Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, MA 02120,","Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, MA 02120,","institution_ids":["https://openalex.org/I1283280774"]},{"raw_affiliation_string":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, United States","institution_ids":["https://openalex.org/I1283280774"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004416630","display_name":"Sebastian Schneewei\u00df","orcid":"https://orcid.org/0000-0003-2575-467X"},"institutions":[{"id":"https://openalex.org/I1283280774","display_name":"Brigham and Women's Hospital","ror":"https://ror.org/04b6nzv94","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283280774","https://openalex.org/I48633490"]},{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sebastian Schneeweiss","raw_affiliation_strings":["Department of Epidemiology, Harvard T.H. Chan School of Public Health , Boston, MA 02115,","Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, MA 02120,","Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States","Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Epidemiology, Harvard T.H. Chan School of Public Health , Boston, MA 02115,","institution_ids":["https://openalex.org/I136199984"]},{"raw_affiliation_string":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, MA 02120,","institution_ids":["https://openalex.org/I1283280774"]},{"raw_affiliation_string":"Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States","institution_ids":["https://openalex.org/I136199984"]},{"raw_affiliation_string":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, United States","institution_ids":["https://openalex.org/I1283280774"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5090947431"],"corresponding_institution_ids":["https://openalex.org/I1283280774","https://openalex.org/I136199984"],"apc_list":{"value":3967,"currency":"USD","value_usd":3967},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33900962,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"3","first_page":"573","last_page":"586"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.8610000014305115,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.8610000014305115,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.018400000408291817,"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/T10206","display_name":"Meta-analysis and systematic reviews","score":0.016100000590085983,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/emulation","display_name":"Emulation","score":0.8743000030517578},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.8702999949455261},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.694599986076355},{"id":"https://openalex.org/keywords/confounding","display_name":"Confounding","score":0.6230000257492065},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.4332999885082245}],"concepts":[{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.8743000030517578},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8702999949455261},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.789900004863739},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.694599986076355},{"id":"https://openalex.org/C77350462","wikidata":"https://www.wikidata.org/wiki/Q1125472","display_name":"Confounding","level":2,"score":0.6230000257492065},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49779999256134033},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.4332999885082245},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4097000062465668},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3977000117301941},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3025999963283539},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.2928999960422516},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.2515999972820282}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015986","descriptor_name":"Confounding Factors, Epidemiologic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016032","descriptor_name":"Randomized Controlled Trials as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019985","descriptor_name":"Benchmarking","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1093/jamia/ocaf204","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocaf204","pdf_url":null,"source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},{"id":"pmid:41338229","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41338229","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association : JAMIA","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2847480730","display_name":null,"funder_award_id":"ME-2022C1-25646","funder_id":"https://openalex.org/F4320308927","funder_display_name":"Patient-Centered Outcomes Research Institute"},{"id":"https://openalex.org/G6601206101","display_name":null,"funder_award_id":"R01-AR080194","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G8744103166","display_name":null,"funder_award_id":"R01-HL141505","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320308927","display_name":"Patient-Centered Outcomes Research Institute","ror":"https://ror.org/014q65q44"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1501511408","https://openalex.org/W1601608895","https://openalex.org/W1820619467","https://openalex.org/W1967862917","https://openalex.org/W1985330842","https://openalex.org/W2002062025","https://openalex.org/W2020925091","https://openalex.org/W2095193497","https://openalex.org/W2113002312","https://openalex.org/W2119862467","https://openalex.org/W2122825543","https://openalex.org/W2134430286","https://openalex.org/W2143891888","https://openalex.org/W2159767831","https://openalex.org/W2160643831","https://openalex.org/W2168458505","https://openalex.org/W2330118189","https://openalex.org/W2330467346","https://openalex.org/W2332997882","https://openalex.org/W2460615870","https://openalex.org/W2572447560","https://openalex.org/W2591193582","https://openalex.org/W2591688362","https://openalex.org/W2763650945","https://openalex.org/W2765693998","https://openalex.org/W2768609493","https://openalex.org/W2798958557","https://openalex.org/W2808880546","https://openalex.org/W2826750344","https://openalex.org/W2831840344","https://openalex.org/W2896002881","https://openalex.org/W2935712808","https://openalex.org/W2946722168","https://openalex.org/W2973316378","https://openalex.org/W2991319174","https://openalex.org/W3004404638","https://openalex.org/W3006360868","https://openalex.org/W3093213262","https://openalex.org/W3112964578","https://openalex.org/W3121449393","https://openalex.org/W3123436326","https://openalex.org/W3129758832","https://openalex.org/W3131883061","https://openalex.org/W4200057099","https://openalex.org/W4281956449","https://openalex.org/W4295242742","https://openalex.org/W4296012301","https://openalex.org/W4310170174","https://openalex.org/W4311860694","https://openalex.org/W4361283651","https://openalex.org/W4366992020","https://openalex.org/W4386084621","https://openalex.org/W4389549989","https://openalex.org/W4391529776","https://openalex.org/W4393096466","https://openalex.org/W4401973488","https://openalex.org/W4406602151","https://openalex.org/W4407421703","https://openalex.org/W4408128063"],"related_works":[],"abstract_inverted_index":{"OBJECTIVES:":[0],"Real-world":[1],"evidence":[2,217],"(RWE)":[3],"increasingly":[4],"informs":[5],"clinical":[6],"decisions,":[7],"yet":[8],"manual":[9,182],"adjustment":[10,21,86,134,214],"for":[11,18,68,162,202,211,223,239],"confounding":[12,213],"limits":[13],"scalability.":[14],"Data-adaptive":[15,207],"(DA)":[16],"algorithms":[17,180,208],"high-dimensional":[19],"proxy":[20],"show":[22,209],"promise":[23,210],"but":[24,187],"have":[25],"not":[26],"been":[27],"systematically":[28],"compared":[29],"to":[30,45],"investigator-specified":[31,224],"(IS)":[32],"approaches":[33],"across":[34,174],"diverse":[35],"treatment":[36,152,163,204],"scenarios.":[37],"We":[38,64],"evaluated":[39],"whether":[40],"DA":[41,145,171,179],"strategies":[42,97,172,227],"perform":[43],"comparably":[44],"manually":[46,92],"curated":[47],"IS":[48,89,133,169,183],"models":[49,90,107,159,184],"using":[50,84,98],"claims-based":[51],"emulations":[52,71],"of":[53,137,141,168,198],"15":[54,69],"randomized":[55],"trials":[56],"from":[57,101],"the":[58,195,235],"RCT-DUPLICATE":[59],"initiative.":[60],"MATERIALS":[61],"AND":[62],"METHODS:":[63],"identified":[65],"new-user":[66],"cohorts":[67],"trial":[70],"in":[72,135,215],"Optum's":[73],"de-identified":[74],"Clinformatics":[75],"Data":[76],"Mart":[77],"Database":[78],"(2004-2023).":[79],"Treatment":[80],"effects":[81],"were":[82],"estimated":[83],"3":[85],"strategies:":[87],"(1)":[88],"with":[91,115,150,231],"tailored":[93],"covariates;":[94],"(2)":[95],"full-DA":[96,138],"empirical":[99,110],"features":[100],"semiautomated":[102],"pipelines;":[103],"and":[104,111,123,139,153,219],"(3)":[105],"hybrid-DA":[106,142],"incorporating":[108],"both":[109,151],"investigator-defined":[112],"covariates.":[113],"Agreement":[114],"RCT":[116],"benchmarks":[117],"was":[118],"assessed":[119],"via":[120],"binary":[121],"metrics":[122],"difference-in-differences.":[124],"RESULTS:":[125],"Outcome-adaptive":[126],"LASSO":[127],"achieved":[128],"better":[129],"RWE-RCT":[130],"agreement":[131],"than":[132],"73%":[136],"87%":[140],"emulations.":[143],"Other":[144],"methods":[146,230],"considering":[147],"feature":[148],"associations":[149],"outcome":[154],"performed":[155,165],"similarly":[156],"well,":[157],"while":[158],"tuned":[160],"solely":[161],"prediction":[164],"poorly.":[166],"Performance":[167],"vs":[170],"differed":[173],"emulated":[175],"trials.":[176],"DISCUSSION:":[177],"Top":[178],"matched":[181],"on":[185],"average,":[186],"impact":[188],"varied":[189],"by":[190],"emulation.":[191],"Case":[192],"studies":[193],"illustrate":[194],"continued":[196],"importance":[197],"subject-matter":[199],"knowledge,":[200],"particularly":[201],"complex":[203],"strategies.":[205],"CONCLUSION:":[206],"scalable":[212],"large-scale":[216],"systems":[218],"as":[220],"augmentation":[221],"tools":[222],"designs.":[225],"Hybrid":[226],"combining":[228],"algorithmic":[229],"investigator":[232],"expertise":[233],"offer":[234],"most":[236],"reliable":[237],"approach":[238],"individual":[240],"causal":[241],"questions.":[242]},"counts_by_year":[],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-12-04T00:00:00"}
