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dc.contributor.authorKamphues, Carsten
dc.contributor.authorAndreatos, Nikolaos
dc.contributor.authorKruppa, Jochen
dc.contributor.authorBuettner, Stefan
dc.contributor.authorWang, Jaeyun
dc.contributor.authorSasaki, Kazunari
dc.contributor.authorWagner, Doris
dc.contributor.authorMorioka, Daisuke
dc.contributor.authorFitschek, Fabian
dc.contributor.authorLøes, Inger Marie
dc.contributor.authorImai, Katsunori
dc.contributor.authorSun, Jinger
dc.contributor.authorPoultsides, George
dc.contributor.authorKaczirek, Klaus
dc.contributor.authorLønning, Per Eystein
dc.contributor.authorEndo, Itaru
dc.contributor.authorBaba, Hideo
dc.contributor.authorKornprat, Peter
dc.contributor.authorAucejo, Federico N.
dc.contributor.authorWolfgang, Christopher L.
dc.contributor.authorKreis, Martin E.
dc.contributor.authorWeiss, Matthew J.
dc.contributor.authorMargonis, Georgios Antonios
dc.description.abstractBackground and Objectives Despite the long-standing consensus on the importance of tumor size, tumor number and carcinoembryonic antigen (CEA) levels as predictors of long-term outcomes among patients with colorectal liver metastases (CRLM), optimal prognostic cut-offs for these variables have not been established. Methods Patients who underwent curative-intent resection of CRLM and had available data on at least one of the three variables of interest above were selected from a multi-institutional dataset of patients with known KRAS mutational status. The resulting cohort was randomly split into training and testing datasets and recursive partitioning analysis was employed to determine optimal cut-offs. The concordance probability estimates (CPEs) for these optimal cut offs were calculated and compared to CPEs for the most widely used cut-offs in the surgical literature. Results A total of 1643 patients who met eligibility criteria were identified. Following recursive partitioning analysis in the training dataset, the following cut-offs were identified: 2.95 cm for tumor size, 1.5 for tumor number and 6.15 ng/ml for CEA levels. In the entire dataset, the calculated CPEs for the new tumor size (0.52), tumor number (0.56) and CEA (0.53) cut offs exceeded CPEs for other commonly employed cut-offs. Conclusion The current study was able to identify optimal cut-offs for the three most commonly employed prognostic factors in CRLM. While the per variable gains in discriminatory power are modest, these novel cut-offs may help produce appreciable increases in prognostic performance when combined in the context of future risk scores.en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.titleThe optimal cut-off values for tumor size, number of lesions, and CEA levels in patients with surgically treated colorectal cancer liver metastases: An international, multi-institutional studyen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.rights.holderCopyright 2021 The Author(s)en_US
dc.source.journalJournal of Surgical Oncologyen_US
dc.identifier.citationJournal of Surgical Oncology. 2021, 123 (4), 939-948.en_US

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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal