Clinical features and prediction of long-term survival after surgery for perihilar cholangiocarcinoma

The treatment of perihilar Cholangiocarcinoma (pCCA) poses specific challenges not only due to its high perioperative complication rates but also due its dismal long-term prognosis with only a few long-term survivors (LTS) among the patients. Therefore, in this analysis characteristics and predictor...

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Veröffentlicht in:PloS one 2024-07, Vol.19 (7), p.e0304838
Hauptverfasser: Mantas, Anna, Otto, Carlos Constantin, Olthof, Pim B, Heise, Daniel, Hoyer, Dieter Paul, Bruners, Philipp, Dewulf, Maxim, Lang, Sven Arke, Ulmer, Tom Florian, Neumann, Ulf Peter, Bednarsch, Jan
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Sprache:eng
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Zusammenfassung:The treatment of perihilar Cholangiocarcinoma (pCCA) poses specific challenges not only due to its high perioperative complication rates but also due its dismal long-term prognosis with only a few long-term survivors (LTS) among the patients. Therefore, in this analysis characteristics and predictors of LTS in pCCA patients are investigated. In this single center analysis, patients undergoing curative-intent liver resection for pCCA between 2010 and 2022 were categorized into long-term and short-term survivors (STS) excluding perioperative mortality. Binary logistic regression was used to determine key differences between the groups and to develop a prognostic composite variable. This composite variable was subsequently tested in the whole cohort of surgically treated pCCA patients using Cox Regression analysis for cancer-specific survival (CSS). Within a cohort of 209 individuals, 27 patients were identified as LTS (median CSS = 125 months) and 55 patients as STS (median CSS = 16 months). Multivariable analysis identified preoperative portal vein infiltration (OR = 5.85, p = 0.018) and intraoperative packed red blood cell (PRBC) transfusions (OR = 10.29, p = 0.002) as key differences between the groups. A prognostic composite variable based on these two features was created and transferred into a Cox regression model of the whole cohort. Here, the composite variable (HR = 0.35, p
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0304838