Anatomical sites (Takasaki's segmentation) predicts the recurrence-free survival of hepatocellular carcinoma.

Background: Until now, several classification staging system and treatment algorithm for hepatocelluar carcinoma (HCC) has been presented. However, anatomical location is not taken into account in these staging systems. The aim of this study is to investigate whether anatomical sites could predict t...

Descripción completa

Detalles Bibliográficos
Publicado en:BMC Surgery Vol. 21; no. 1; pp. 1 - 11
Autores principales: Qin, Wei, Wang, Li, Hu, Beiyuan, Tian, Huan, Xiao, Cuicui, Luo, Huanxian, Yang, Yang
Formato: research tables/charts Journal Article
Publicado: BioMed Central 6/3/2021
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=150668980&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 150668980
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        14712482
        1CIN
      jtl: BMC Surgery
      issn: 14712482
      maglogo: N
    pubinfo:
      dt: 6/3/2021
      vid: 21
      iid: 1
      pid: 24147
      pub: BioMed Central
    artinfo:
      ui:
        150668980
        150668980
        NLM34082743
        150668980
        10.1186/s12893-021-01275-3
        NLM34082743
        150668980
      ppf: 1
      ppct: 10
      formats:
      tig:
        atl: Anatomical sites (Takasaki's segmentation) predicts the recurrence-free survival of hepatocellular carcinoma.
      aug:
        au:
          Qin, Wei
          Wang, Li
          Hu, Beiyuan
          Tian, Huan
          Xiao, Cuicui
          Luo, Huanxian
          Yang, Yang
        affil: Department of Hepatic Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, 510630, Guangzhou, China
      sug:
        subj:
          Liver Neoplasms Surgery
          Carcinoma, Hepatocellular Surgery
          Carcinoma, Hepatocellular Pathology
          Liver Neoplasms Pathology
          Prognosis
          Neoplasm Staging
          Neoplasm Recurrence, Local Epidemiology
          Hepatectomy
          Retrospective Design
          Human
          Funding Source
      ab: Background: Until now, several classification staging system and treatment algorithm for hepatocelluar carcinoma (HCC) has been presented. However, anatomical location is not taken into account in these staging systems. The aim of this study is to investigate whether anatomical sites could predict the postoperative recurrence of HCC patients.Methods: 294 HCC patients were enrolled in this retrospective study. A novel score classification based on anatomical sites was established by a Cox regression model and validated in the internal validation cohort.Results: HCC patients were stratified according to the novel score classification into three groups (score 0, score 1-3 and score 4-6). The predictive accuracy of the novel recurrence score for HCC patients as determined by the area under the receiver operating characteristic curves (AUCs) at 1, 3, and 5 years (AUCs 0.703, 0.706, and 0.605) was greater than that of the other representative classification systems. These findings were supported by the internal validation cohort. For patients with Barcelona Clinic Liver Cancer (BCLC) 0 and A stage, our data demonstrated that there was no significant difference in recurrence-free survival (RFS) between patients with score 0 and liver transplantation recipients. Additionally, we introduced this novel classification system to guide anatomical liver resection for centrally located liver tumors.Conclusion: The novel score classification may provide a reliable and objective model to predict the RFS of HCC after hepatic resection.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N