{"id":"https://openalex.org/W7163193433","doi":"https://doi.org/10.1093/biomtc/ujag083","title":"Integrative learning of individualized treatment rules from multiple studies with partially overlapping treatments","display_name":"Integrative learning of individualized treatment rules from multiple studies with partially overlapping treatments","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7163193433","doi":"https://doi.org/10.1093/biomtc/ujag083","pmid":"https://pubmed.ncbi.nlm.nih.gov/42227819","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13227520"},"language":"en","primary_location":{"id":"doi:10.1093/biomtc/ujag083","doi":"https://doi.org/10.1093/biomtc/ujag083","is_oa":false,"landing_page_url":"https://doi.org/10.1093/biomtc/ujag083","pdf_url":null,"source":{"id":"https://openalex.org/S8265502","display_name":"Biometrics","issn_l":"0006-341X","issn":["0006-341X","1541-0420"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","dongbi-b","doyens","jufo-2","ki-jl-2","medline","norway-2","poland-100","russia-white-list-1","vabb-shw"],"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":"Biometrics","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["arxiv","crossref","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2604.10712","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yuan Bian","orcid":"https://orcid.org/0000-0003-1879-5887","observed_orcids":["https://orcid.org/0000-0003-1879-5887"]},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuan Bian","raw_affiliation_strings":["Columbia University Department of Biostatistics, , New York, NY 10032 ,"],"raw_orcid":"https://orcid.org/0000-0003-1879-5887","affiliations":[{"raw_affiliation_string":"Columbia University Department of Biostatistics, , New York, NY 10032 ,","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128266795","display_name":"Donglin Zeng","orcid":"https://orcid.org/0000-0003-0843-9280","observed_orcids":["https://orcid.org/0000-0003-0843-9280"]},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Donglin Zeng","raw_affiliation_strings":["University of Michigan Department of Biostatistics, , Ann Arbor, MI 48109 ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan Department of Biostatistics, , Ann Arbor, MI 48109 ,","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066146387","display_name":"Hyun\u2010Joon Yang","orcid":"https://orcid.org/0000-0003-4424-2514","observed_orcids":["https://orcid.org/0000-0003-4424-2514"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hyun-Joon Yang","raw_affiliation_strings":["Stanford University Department of Psychiatry and Behavioral Sciences, , Stanford, CA 94305 ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University Department of Psychiatry and Behavioral Sciences, , Stanford, CA 94305 ,","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083848316","display_name":"Leanne Maree Williams","orcid":"https://orcid.org/0000-0001-9987-7360","observed_orcids":["https://orcid.org/0000-0001-9987-7360"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leanne M Williams","raw_affiliation_strings":["Stanford University Department of Psychiatry and Behavioral Sciences, , Stanford, CA 94305 ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University Department of Psychiatry and Behavioral Sciences, , Stanford, CA 94305 ,","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5133573881","display_name":"Yuanjia Wang","orcid":"https://orcid.org/0000-0002-1510-3315","observed_orcids":["https://orcid.org/0000-0002-1510-3315"]},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yuanjia Wang","raw_affiliation_strings":["Columbia University Department of Biostatistics, , New York, NY 10032 ,","Columbia University Department of Psychiatry, , New York, NY 10032 ,"],"raw_orcid":"https://orcid.org/0000-0002-1510-3315","affiliations":[{"raw_affiliation_string":"Columbia University Department of Biostatistics, , New York, NY 10032 ,","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Columbia University Department of Psychiatry, , New York, NY 10032 ,","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5133573881"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":{"value":3780,"currency":"USD","value_usd":3780},"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39386133,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"82","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9297000169754028,"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":0.9297000169754028,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.06109999865293503,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.0007999999797903001,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/individualized-treatment-rules","display_name":"individualized treatment rules","score":0.996999979019165},{"id":"https://openalex.org/keywords/integrative-learning","display_name":"integrative learning","score":0.8090000152587891},{"id":"https://openalex.org/keywords/heterogeneous-treatment-effect","display_name":"heterogeneous treatment effect","score":0.5920000076293945},{"id":"https://openalex.org/keywords/excess-risk","display_name":"excess risk","score":0.7350000143051147},{"id":"https://openalex.org/keywords/value-function-estimation","display_name":"value function estimation","score":0.7059999704360962},{"id":"https://openalex.org/keywords/major-depressive-disorder","display_name":"major depressive disorder","score":0.8420000076293945},{"id":"https://openalex.org/keywords/antidepressant-response","display_name":"antidepressant response","score":0.843999981880188},{"id":"https://openalex.org/keywords/selective-serotonin-reuptake-inhibitors","display_name":"selective serotonin reuptake inhibitors","score":0.9129999876022339},{"id":"https://openalex.org/keywords/statistical-power","display_name":"statistical power","score":0.4410000145435333}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6338000297546387},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6227999925613403},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5292999744415283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4634000062942505},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4480000138282776},{"id":"https://openalex.org/C168563851","wikidata":"https://www.wikidata.org/wiki/Q1436668","display_name":"Randomized controlled trial","level":2,"score":0.40220001339912415},{"id":"https://openalex.org/C2780051608","wikidata":"https://www.wikidata.org/wiki/Q42844","display_name":"Major depressive disorder","level":3,"score":0.3725000023841858},{"id":"https://openalex.org/C2779177272","wikidata":"https://www.wikidata.org/wiki/Q76560","display_name":"Antidepressant","level":3,"score":0.36469998955726624},{"id":"https://openalex.org/C535046627","wikidata":"https://www.wikidata.org/wiki/Q30612","display_name":"Clinical trial","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C32220436","wikidata":"https://www.wikidata.org/wiki/Q2072214","display_name":"Personalized medicine","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C2987370644","wikidata":"https://www.wikidata.org/wiki/Q7836903","display_name":"Treatment effect","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3100000023841858},{"id":"https://openalex.org/C183905921","wikidata":"https://www.wikidata.org/wiki/Q1038757","display_name":"Multiple comparisons problem","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2816999852657318},{"id":"https://openalex.org/C2776867660","wikidata":"https://www.wikidata.org/wiki/Q1814941","display_name":"Depression (economics)","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26570001244544983},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.2517000138759613}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000096962","descriptor_name":"Treatment Effect Heterogeneity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000928","descriptor_name":"Antidepressive Agents","qualifier_ui":"Q000627","qualifier_name":"therapeutic use","is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003865","descriptor_name":"Major Depressive Disorder","qualifier_ui":"Q000188","qualifier_name":"drug therapy","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016032","descriptor_name":"Randomized Controlled Trials as Topic","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":true},{"descriptor_ui":"D057285","descriptor_name":"Precision Medicine","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.1093/biomtc/ujag083","doi":"https://doi.org/10.1093/biomtc/ujag083","is_oa":false,"landing_page_url":"https://doi.org/10.1093/biomtc/ujag083","pdf_url":null,"source":{"id":"https://openalex.org/S8265502","display_name":"Biometrics","issn_l":"0006-341X","issn":["0006-341X","1541-0420"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","dongbi-b","doyens","jufo-2","ki-jl-2","medline","norway-2","poland-100","russia-white-list-1","vabb-shw"],"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":"Biometrics","raw_type":"journal-article"},{"id":"pmid:42227819","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42227819","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,"listed_in":[],"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":"Biometrics","raw_type":"Journal Article"},{"id":"pmh:oai:arXiv.org:2604.10712","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2604.10712","pdf_url":"https://arxiv.org/pdf/2604.10712","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:pubmedcentral.nih.gov:13227520","doi":null,"is_oa":true,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42227819/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Biometrics","raw_type":"Text"},{"id":"doi:10.48550/arxiv.2604.10712","doi":"https://doi.org/10.48550/arxiv.2604.10712","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10712","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2604.10712","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2604.10712","pdf_url":"https://arxiv.org/pdf/2604.10712","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8560000061988831,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G9000101943","display_name":null,"funder_award_id":"NS073671","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G9000862394","display_name":"Statistical Methods for Integrating Mixed-type Biomarkers and Phenotypes in Neurodegenerative Disease Modeling","funder_award_id":"5r01ns073671-11","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G9000905934","display_name":"Statistical and Machine Learning Methods to Improve Dynamic Treatment Regimens Estimation Using Real World Data.","funder_award_id":"R01GM124104","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"},{"id":"https://openalex.org/G9000911450","display_name":"Machine Learning Methods for Optimizing Individualized Treatment Strategies for Precision Psychiatry","funder_award_id":"R01MH123487","funder_id":"https://openalex.org/F4320337346","funder_display_name":"National Institute of Mental Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337346","display_name":"National Institute of Mental Health","ror":"https://ror.org/04xeg9z08"},{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7163193433.pdf","grobid_xml":"https://content.openalex.org/works/W7163193433.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W24088030","https://openalex.org/W1575774178","https://openalex.org/W1828295177","https://openalex.org/W1967123102","https://openalex.org/W1994857208","https://openalex.org/W1999142409","https://openalex.org/W2001855995","https://openalex.org/W2005105933","https://openalex.org/W2043349008","https://openalex.org/W2057682568","https://openalex.org/W2066153095","https://openalex.org/W2072327382","https://openalex.org/W2122825543","https://openalex.org/W2133531206","https://openalex.org/W2135046866","https://openalex.org/W2139821383","https://openalex.org/W2162491525","https://openalex.org/W2164985671","https://openalex.org/W2240609664","https://openalex.org/W2298299786","https://openalex.org/W2466989778","https://openalex.org/W2565795563","https://openalex.org/W2599189192","https://openalex.org/W2756630952","https://openalex.org/W2807015404","https://openalex.org/W2981591182","https://openalex.org/W3179067529","https://openalex.org/W4381185928","https://openalex.org/W4396624832","https://openalex.org/W4400453930","https://openalex.org/W4402896356","https://openalex.org/W4403000153","https://openalex.org/W4415525767"],"related_works":["https://openalex.org/W4400453930","https://openalex.org/W4310428639","https://openalex.org/W4393227686","https://openalex.org/W2890265507","https://openalex.org/W6944184175","https://openalex.org/W4415310303","https://openalex.org/W4403186896","https://openalex.org/W3002610183","https://openalex.org/W3023471002","https://openalex.org/W2954459822"],"abstract_inverted_index":{"An":[0],"individualized":[1,51],"treatment":[2,23,96,201],"rule":[3],"(ITR)":[4],"tailors":[5],"treatments":[6],"to":[7,20,45,117,182],"a":[8,88,103,193,199],"patient's":[9],"specific":[10],"characteristics.":[11],"However,":[12],"randomized":[13],"controlled":[14],"trials":[15],"(RCTs)":[16],"are":[17],"often":[18],"underpowered":[19],"detect":[21],"the":[22,66,112,118,121,126,130,137,141,151,166,179,206],"effect":[24],"heterogeneity":[25],"needed":[26],"for":[27],"reliable":[28],"ITR":[29],"estimation.":[30],"To":[31],"address":[32],"this":[33,57,72],"limitation,":[34],"there":[35],"is":[36,59],"growing":[37],"interest":[38],"in":[39,56,93,174,186],"leveraging":[40],"information":[41,101],"from":[42,158],"multiple":[43,84],"studies":[44,134,161],"improve":[46,140,218],"statistical":[47],"power":[48],"and":[49,109,146,169,178,213],"support":[50],"decision-making.":[52],"A":[53],"key":[54],"challenge":[55],"context":[58],"that":[60,80,86,136,205],"available":[61],"RCTs":[62,85],"may":[63],"not":[64],"evaluate":[65],"same":[67],"set":[68],"of":[69,114,120,129,143,153,162,171,190],"treatments.":[70],"In":[71],"paper,":[73],"we":[74],"propose":[75],"an":[76],"integrative":[77,215],"learning":[78,208],"framework":[79],"synthesizes":[81],"evidence":[82],"across":[83],"share":[87],"common":[89,200],"comparator":[90],"but":[91],"differ":[92],"their":[94],"alternative":[95],"arms.":[97],"Our":[98],"method":[99,209],"integrates":[100],"through":[102],"regularized":[104],"weighted":[105],"misclassification":[106],"risk":[107,128],"function":[108],"adaptively":[110],"determines":[111],"contribution":[113],"each":[115],"study":[116,125,177],"ITRs":[119],"others.":[122],"We":[123,149,203],"rigorously":[124],"excess":[127],"resulting":[131],"estimator.":[132],"Simulation":[133],"demonstrate":[135],"proposed":[138],"approaches":[139],"estimation":[142],"both":[144,189],"value":[145],"benefit":[147],"functions.":[148],"illustrate":[150],"utility":[152],"our":[154,214],"methodology":[155],"using":[156],"data":[157],"two":[159],"landmark":[160],"major":[163],"depressive":[164],"disorder:":[165],"Establishing":[167],"Moderators":[168],"Biosignatures":[170],"Antidepressant":[172],"Response":[173],"Clinical":[175],"Care":[176],"International":[180],"Study":[181],"Predict":[183],"Optimized":[184],"Treatment":[185],"Depression":[187],"study,":[188],"which":[191],"include":[192],"selective":[194],"serotonin":[195],"reuptake":[196],"inhibitor":[197],"as":[198],"arm.":[202],"find":[204],"separate":[207],"outperforms":[210],"one-size-fits-all":[211],"methods,":[212],"methods":[216],"further":[217],"performance.":[219]},"counts_by_year":[],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2026-06-03T00:00:00"}