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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Surgical Oncology
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1414083

Development and Validation of a Prognostic Nomogram to Predict the Recurrence of AFPnegative and DCP-positive Hepatocellular Carcinoma after curative resection

Provisionally accepted
  • 1 Beijing Ditan Hospital, Capital Medical University, Beijing, China
  • 2 Donghai County People's Hospital, Lianyungang, Jiangsu Province, China
  • 3 Beijing Institute of Hepatology, Beijing You'an Hospital, Capital Medical University, Beijing, China
  • 4 Beijing Youan Hospital, Capital Medical University, Beijing, Shaanxi Province, China

The final, formatted version of the article will be published soon.

    Purpose: Approximately one-third of hepatocellular carcinoma (HCC) cases are characterized by alphafetoprotein (AFP) negativity (AFP-NHCC. Among these patients, around 60% exhibit des-gammacarboxyprothrombin (DCP) positivity, and DCP-positive patients have a poorer prognosis. As a curative treatment, recurrence after liver resection poses significant challenges to the prognosis of HCC patients. Therefore, it is necessary to determine the relevant risk factors of these patients and provide timely treatment options. Methods: This study included 540 patients who underwent resection at Beijing You'an Hospital. 292 patients from 2014 to 2018 constituted the training cohort, while 248 patients from 2018 to 2020 constituted the validation cohort. All patients underwent routine follow-ups until December 2023. Variables were identified through Cox regression, and a nomogram was developed. The nomogram was evaluated using time-dependent receiver operating characteristic curves (ROC), calibration curves, Decision curve analysis (DCA), and Kaplan-Meier (KM) curve analysis Results: We found that age, tumor number, tumor size, γ-glutamyl transpeptidase (γ-GT), and prothrombin time (PT) are independent risk factors for HCC recurrence, and a nomogram was developed and validated based on this result to predict recurrence-free survival (RFS) at 1, 2, and 3 years. The performance of the nomogram was further confirmed by the ROC curve, calibration curve, and DCA, all of which showed favorable results. The KM curve analysis clearly distinguishes between two groups of people with different risks in terms of prognosis in both the training and validation sets. Conclusion: In summary, we established and validated a novel nomogram by multivariate Cox regression analysis to predict recurrence in DCP-positive patients with AFP-NHCC after resection. The nomogram, including age, tumor number, tumor size, γ-GT, and PT, demonstrates better predictive ability for AFP-NHCC patients with DCP positive.

    Keywords: Hepatocellular Carcinoma, AFP negative, DCP positive, resection, Recurrence RFS: recurrence-free survival DCA: Decision curve analysis ROC: Receiver Operating Characteristic Curve AUC: Area Under Curve BCLC: Barcelona Clinic Liver Cancer

    Received: 08 Apr 2024; Accepted: 22 Jul 2024.

    Copyright: © 2024 Li, Wang, Yan, Sun, Zhang, Li and Jin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Guangming Li, Beijing Youan Hospital, Capital Medical University, Beijing, 100069, Shaanxi Province, China
    Ronghua Jin, Beijing Ditan Hospital, Capital Medical University, Beijing, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.