{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["17(18)"],"submitter":["Shimizu H"],"pubmed_abstract":["<b>Background</b>: Blood-based comprehensive genomic profiling (CGP), a form of liquid biopsy, is often used for biliary tract cancer (BTC) when tissue-based CGP (tissue CGP) is unavailable, despite lower detection rates. This study explored factors linked to detecting actionable genomic alterations to optimize its use. <b>Methods</b>: We retrospectively analyzed BTC cases in Japan's C-CAT (June 2019-January 2025), restricting panel comparisons to FoundationOne<sup>®</sup> CDx (F1; n = 5019) and FoundationOne<sup>®</sup> Liquid CDx (F1L; n = 1550). Missing covariates were handled by multiple imputations (m = 20). Between-panel balance used 1:1 propensity-score matching (caliper 0.2). Outcomes were modeled with logistic regression. Targets included MSI-H, TMB-H, <i>FGFR2</i>/<i>RET</i>/<i>N"],"journal":["Cancers"],"pagination":["3071"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12468581"],"repository":["biostudies-literature"],"pubmed_title":["Factors Associated with the Detection of Actionable Genomic Alterations Using Liquid Biopsy in Biliary Tract Cancer."],"pmcid":["PMC12468581"],"pubmed_authors":["Ohira R","Suzuki R","Ohira H","Asama H","Shimizu H","Osawa K","Sato K","Kudo K","Sugimoto M"],"additional_accession":[]},"is_claimable":false,"name":"Factors Associated with the Detection of Actionable Genomic Alterations Using Liquid Biopsy in Biliary Tract Cancer.","description":"<b>Background</b>: Blood-based comprehensive genomic profiling (CGP), a form of liquid biopsy, is often used for biliary tract cancer (BTC) when tissue-based CGP (tissue CGP) is unavailable, despite lower detection rates. This study explored factors linked to detecting actionable genomic alterations to optimize its use. <b>Methods</b>: We retrospectively analyzed BTC cases in Japan's C-CAT (June 2019-January 2025), restricting panel comparisons to FoundationOne<sup>®</sup> CDx (F1; n = 5019) and FoundationOne<sup>®</sup> Liquid CDx (F1L; n = 1550). Missing covariates were handled by multiple imputations (m = 20). Between-panel balance used 1:1 propensity-score matching (caliper 0.2). Outcomes were modeled with logistic regression. Targets included MSI-H, TMB-H, <i>FGFR2</i>/<i>RET</i>/<i>N","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Sep","modification":"2026-05-02T03:10:25.072Z","creation":"2026-05-02T03:07:38.207Z"},"accession":"S-EPMC12468581","cross_references":{"pubmed":["41008912"],"doi":["10.3390/cancers17183071"]}}