{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T09:43:13Z","timestamp":1784799793771,"version":"3.55.0"},"reference-count":22,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T00:00:00Z","timestamp":1767916800000},"content-version":"vor","delay-in-days":8,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":["Cancer Medicine"],"published-print":{"date-parts":[[2026,1]]},"abstract":"ABSTRACT<\/jats:title>\n \n Background<\/jats:title>\n \n In the\n PROSELICA<\/jats:styled-content>\n , a randomized controlled trial (\n RCT<\/jats:styled-content>\n ) comparing cabazitaxel 20\u2009mg\/m\n 2<\/jats:sup>\n (\n C20<\/jats:styled-content>\n ) versus 25\u2009mg\/m\n 2<\/jats:sup>\n (\n C25<\/jats:styled-content>\n ) in metastatic castration\u2010resistant prostate cancer (\n mCRPC<\/jats:styled-content>\n ), one\u2010variable\u2010at\u2010a\u2010time subgroup analysis suggested possible heterogeneity in treatment effect (\n HTE<\/jats:styled-content>\n ) of\n C25<\/jats:styled-content>\n versus\n C20<\/jats:styled-content>\n among study participants. Novel predictive\n HTE<\/jats:styled-content>\n analysis approaches may provide an in\u2010depth understanding of such results.\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n We analyzed patient\u2010level data from 1200 patients with mCRPC who were randomized in the PROSELICA trial. Outcomes included overall survival (OS) and progression\u2010free survival (PFS). Using baseline characteristics, patients were stratified into quartiles based on either quantitative baseline risk of poor outcome (risk modeling) or predicted individualized treatment effect (ITE) using a causal survival forest algorithm (effect modeling). Treatment effects were measured as differences in restricted mean survival time (RMST).<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n For risk modeling, the\n OS<\/jats:styled-content>\n effect of\n C25<\/jats:styled-content>\n increased with risk quartiles: \u22120.07\u2009months (95%\n CI<\/jats:styled-content>\n , \u22121.60 to 1.46) in the lowest risk quartile and 1.67\u2009months (95%\n CI<\/jats:styled-content>\n , 0.25 to 3.10) in the highest risk quartile. For effect modeling, the\n OS<\/jats:styled-content>\n effect ranged from \u22120.17\u2009months (95%\n CI<\/jats:styled-content>\n , \u22123.01 to 2.68) in the lowest\n ITE<\/jats:styled-content>\n quartile to 0.57\u2009months (95%\n CI<\/jats:styled-content>\n , \u22122.27 to 3.41) in the highest\n ITE<\/jats:styled-content>\n quartile. Both approaches demonstrated greater\n C25<\/jats:styled-content>\n benefit in patients with extensive previous treatment and baseline disease burden.\n PFS<\/jats:styled-content>\n effects remained consistent across all quartiles.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n The OS effect of C25 versus C20 may vary based on baseline characteristics in post\u2010docetaxel mCRPC. Patients with extensive treatment history and disease burden may benefit more from C25.<\/jats:p>\n <\/jats:sec>","DOI":"10.1002\/cam4.71507","type":"journal-article","created":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T03:35:42Z","timestamp":1768016142000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Heterogeneity in Treatment Effects of Reduced Versus Standard Dose of Cabazitaxel in Metastatic Castration\u2010Resistant Prostate Cancer"],"prefix":"10.1002","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1044-912X","authenticated-orcid":false,"given":"Wataru","family":"Fukuokaya","sequence":"first","affiliation":[{"name":"Department of Clinical Biostatistics Institute of Science Tokyo Tokyo Japan"},{"name":"Department of Urology The Jikei University School of Medicine Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keiichiro","family":"Mori","sequence":"additional","affiliation":[{"name":"Department of Urology The Jikei University School of Medicine Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takafumi","family":"Yanagisawa","sequence":"additional","affiliation":[{"name":"Department of Urology The Jikei University School of Medicine Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kagenori","family":"Ito","sequence":"additional","affiliation":[{"name":"Department of Urology The Jikei University School of Medicine Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2599-8183","authenticated-orcid":false,"given":"Fumihiko","family":"Urabe","sequence":"additional","affiliation":[{"name":"Department of Urology The Jikei University School of Medicine Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pawel","family":"Rajwa","sequence":"additional","affiliation":[{"name":"Department of Urology Medical University of Silesia Zabrze Poland"},{"name":"Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria"},{"name":"Division of Surgery and Interventional Science University College London London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shahrokh F.","family":"Shariat","sequence":"additional","affiliation":[{"name":"Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria"},{"name":"Department of Urology University of Texas Southwestern Medical Center Dallas Texas USA"},{"name":"Department of Urology, Second Faculty of Medicine Charles University Prague Czech Republic"},{"name":"Department of Urology Weill Cornell Medical College New York New York USA"},{"name":"Karl Landsteiner Institute of Urology and Andrology Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takahiro","family":"Kimura","sequence":"additional","affiliation":[{"name":"Department of Urology The Jikei University School of Medicine Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Akihiro","family":"Hirakawa","sequence":"additional","affiliation":[{"name":"Department of Clinical Biostatistics Institute of Science Tokyo Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,1,9]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41391-023-00725-8"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(10)61389-X"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2016.72.1076"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(05)17709-5"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(00)02039-0"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.3310\/hta5330"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2003.08.009"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/1745-6215-11-85"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.298.10.1209"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.k4245"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.7326\/M18-3667"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2007.11.008"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.7326\/M18-3668"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1097\/EDE.0b013e3181c30fb2"},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1093\/jrsssb\/qkac001"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2017.1319839"},{"key":"e_1_2_11_18_1","doi-asserted-by":"crossref","unstructured":"V.Chernozhukov M.Demirer E.Duflo andI.Fern\u00e1ndez\u2010Val \u201cGeneric Machine Learning Inference on Heterogeneous Treatment Effects in Randomized Experiments With an Application to Immunization in India. National Bureau of Economic Research \u201d(2018) https:\/\/doi.org\/10.3386\/w24678.","DOI":"10.3386\/w24678"},{"key":"e_1_2_11_19_1","unstructured":"Uroweb\u2014European Association of Urology \u201cProstate Cancer \u201d(2025) https:\/\/uroweb.org\/guidelines\/prostate\u2010cancer."},{"key":"e_1_2_11_20_1","unstructured":"\u201cAdvanced Prostate Cancer: AUA\/SUO Guideline\u2014American Urological Association \u201d(2025) https:\/\/www.auanet.org\/guidelines\u2010and\u2010quality\/guidelines\/advanced\u2010prostate\u2010cancer."},{"key":"e_1_2_11_21_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2020.38.15_suppl.12024"},{"issue":"6","key":"e_1_2_11_22_1","first-page":"2075","article-title":"Risk and Treatment Effect Heterogeneity: Re\u2010Analysis of Individual Participant Data From 32 Large Clinical Trials","volume":"45","author":"Kent D. 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