The Dominant Component and Clinicopathological Characteristics of Combined Hepatocellular-cholangiocarcinoma After Radical Resection.

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作者:

Matsubara KKobayashi TTadokoro TNamba YFukuhara SOshita KOHonmyo NKuroda SArihiro KOhdan H

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摘要:

Combined hepatocellular cholangiocarcinoma (cHCC-CCA) is a rare subtype of primary liver carcinoma, characterized by the unequivocal presence of both hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). However, its clinicopathological characteristics have not yet been thoroughly elucidated. In particular, cholangiolocellular carcinoma (CLC) was classified as a subtype of cHCC-CCA according to the 2010 World Health Organization (WHO) classification. However, according to the 2019 WHO classification, tumors displaying histological features consistent with CLC but lacking evidence of hepatocellular differentiation should be regarded as a distinct subtype of iCCA. Nevertheless, there may be notable differences in prognosis between CLC and iCCA, indicating the necessity for refining the classification when devising clinical treatment strategies. This study aimed to determine the clinicopathological features and prognostic factors of cHCC-CCAs following radical resection. Between January 2010 and September 2020, based on the 2010 WHO classification, we retrospectively studied the clinicopathological features and prognoses of patients with cHCC-CCAs in relation to the pathological dominant classification. The patients were classified according to the pathological dominant components of cHCC-CCA as HCC-dominant (HCC-D), iCCA-dominant (iCCA-D), or CLC-dominant (CLC-D). Data of 55 patients who underwent primary radical hepatectomy for cHCC-CCA were analyzed. The prevalences of each dominant classification were HCC-D, 21 (38.2%); iCCA-D, 11 (20.0%); and CLC-D, 23 (41.8%). Multivariate analysis showed that dominant classification was an independent risk factor for recurrence and cancer-specific survival (CSS). The dominant classification of cHCC-CCA has the potential to predict recurrence and CSS.

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DOI:

10.21873/anticanres.17284

被引量:

0

年份:

2024

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