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Preoperative Serum Markers and Risk Classification in Intrahepatic Cholangiocarcinoma: A Multicenter Retrospective Study.
Kaibori, Masaki; Yoshii, Kengo; Kosaka, Hisashi; Ota, Masato; Komeda, Koji; Ueno, Masaki; Hokutou, Daisuke; Iida, Hiroya; Matsui, Kosuke; Sekimoto, Mitsugu.
Afiliação
  • Kaibori M; Department of Surgery, Kansai Medical University, Osaka 573-1191, Japan.
  • Yoshii K; Department of Mathematics and Statistics in Medical Sciences, Kyoto Prefectural University of Medicine, Kyoto 602-8566, Japan.
  • Kosaka H; Department of Surgery, Kansai Medical University, Osaka 573-1191, Japan.
  • Ota M; Department of General and Gastroenterological Surgery, Osaka Medical College, Takatsuki 569-8686, Japan.
  • Komeda K; Department of General and Gastroenterological Surgery, Osaka Medical College, Takatsuki 569-8686, Japan.
  • Ueno M; Second Department of Surgery, Wakayama Medical University, Wakayama 641-8509, Japan.
  • Hokutou D; Department of Surgery, Nara Medical University, Kashihara 634-8521, Japan.
  • Iida H; Department of Surgery, Shiga University of Medical Science, Otsu 520-2192, Japan.
  • Matsui K; Department of Surgery, Kansai Medical University, Osaka 573-1191, Japan.
  • Sekimoto M; Department of Surgery, Kansai Medical University, Osaka 573-1191, Japan.
Cancers (Basel) ; 14(21)2022 Nov 07.
Article em En | MEDLINE | ID: mdl-36358877
ABSTRACT
Accurate risk stratification selects patients who are expected to benefit most from surgery. This retrospective study enrolled 225 Japanese patients with intrahepatic cholangiocellular carcinoma (ICC) who underwent hepatectomy between January 2009 and December 2020 and identified preoperative blood test biomarkers to formulate a classification system that predicted prognosis. The optimal cut-off values of blood test parameters were determined by ROC curve analysis, with Cox univariate and multivariate analyses identifying prognostic factors. Risk classifications were established using classification and regression tree (CART) analysis. CART analysis revealed decision trees for recurrence-free survival (RFS) and overall survival (OS) and created three risk classifications based on machine learning of preoperative serum markers. Five-year rates differed significantly (p < 0.001) between groups 60.4% (low-risk), 22.8% (moderate-risk), and 4.1% (high-risk) for RFS and 69.2% (low-risk), 32.3% (moderate-risk), and 9.2% (high-risk) for OS. No difference in OS was observed between patients in the low-risk group with or without postoperative adjuvant chemotherapy, although OS improved in the moderate group and was prolonged significantly in the high-risk group receiving chemotherapy. Stratification of patients with ICC who underwent hepatectomy into three risk groups for RFS and OS identified preoperative prognostic factors that predicted prognosis and were easy to understand and apply clinically.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article