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. 2021 Feb 18:11:612588.
doi: 10.3389/fonc.2021.612588. eCollection 2021.

Pre- and Postoperative Models for Prediction of Recurrence in Non-B, Non-C Hepatocellular Carcinoma

Kongying Lin  1 , Qizhen Huang  2 , Lei Wang  3 , Jianxing Zeng  1 , Zongren Ding  1 , Hongzhi Liu  1 , Jun Fu  1 , Pengfei Guo  4 , Zhenwei Chen  4 , Yongyi Zeng  1 , Weiping Zhou  5 , Jingfeng Liu  1   3
Affiliations

Pre- and Postoperative Models for Prediction of Recurrence in Non-B, Non-C Hepatocellular Carcinoma

Kongying Lin et al. Front Oncol. .

Abstract

Background and aims: The incidence of non-B, non-C hepatocellular carcinoma (NBNC-HCC) is increasing. Like in hepatitis B virus (HBC)/HCV-associated HCC, treatment of NBNC-HCC after resection is challenging due to its high recurrence rate. However, few studies on the recurrence of NBNC-HCC have been published in the past decades. Hence, we aimed to investigate the risk factors for recurrence of NBNC-HCC and construct pre- and postoperative prognostic models for predicting recurrence in these patients who underwent curative resection.

Methods: We retrospectively analyzed 608 patients who underwent liver resection for NBNC-HCC. A multivariate Cox proportional hazard regression analysis was conducted to identify the independent risk factors of recurrence, based on which the prediction nomogram models were constructed and validated. The predictive performance of the models was assessed using the concordance index, time-dependent receiver operating characteristic curve, prediction error cure, and calibration curve. To facilitate clinical use, we stratified the patients into three distinct risk groups based on the score of the models. The cutoff scores of the models were determined by a survival tree analysis.

Results: Multivariable analysis identified neutrophil-to-lymphocyte ratio, alpha fetoprotein, tumor number, and tumor diameter as independent preoperative risk factors for recurrence. In addition to these variables, microvascular invasion was an independent postoperative risk factor for recurrence. The pre- and postoperative nomograms were constructed based on these variables. The C-index of the pre- and postoperative nomograms was 0.689 and 0.702 in the training cohort, 0.682 and 0.688 in the validation cohort, respectively, which were both higher than those of the conventional Barcelona Clinic Liver Cancer (BCLC) and 8th edition of the American Joint Committee on Cancer (AJCC8th) staging systems. In addition, the pre- and postoperative nomograms could also re-stratify patients with BCLC stage 0/A or AJCC8th stage IA/IB/II into distinct risk groups.

Conclusions: We constructed pre- and postoperative prognostic models for predicting recurrence in patients with NBNC-HCC who underwent curative resection. They can play a supplementary role to the traditional staging system.

Keywords: inflammation; nomogram; non-B non-C hepatocellular carcinoma; recurrence; resection.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Nomogram for preoperative prediction (A) and postoperative prediction (B) of Recurrence for NBNCHCC patients who underwent hepatectomy.
Figure 2
Figure 2
Time-dependent AUC of pre- and postoperative of nomograms in the training (A) and validation (B) cohorts; prediction error curve of pre- and postoperative nomogram models in the training (C) and validation cohorts (D).
Figure 3
Figure 3
The calibration curves for predicting the 1, 2, and 3-year Recurrence by the Pre- and postoperative nomogram in the training (A, B) and validation cohorts (C, D).
Figure 4
Figure 4
Survival tree analysis of best cut-off scores in the training cohort. (A) postoperative nomogram model; (B) preoperative nomogram model.
Figure 5
Figure 5
Kaplan-Meier plots for cumulative recurrence rate of risk subgroups defined by the nomograms model scores. (A) preoperative nomogram model, training cohort; (B) preoperative nomogram model, validation cohort; (C) postoperative nomogram model, training Cohort; (D) postoperative nomogram model, validation Cohort.
Figure 6
Figure 6
Kaplan-Meier plots for cumulative recurrence rate of risk subgroups defined by the nomograms model scores in different BCLC stage. (A) preoperative nomogram model, BCLC 0/A stage; (B) preoperative nomogram model, BCLC B stage; (C) postoperative nomogram model, BCLC 0/A stage; (D) postoperative nomogram model, BCLC B stage.
Figure 7
Figure 7
Kaplan-Meier plots for cumulative recurrence rate of risk subgroups defined by the nomograms model scores in different AJCC8th stage. (A) preoperative nomogram model, AJCC IA/IB stage; (B) preoperative nomogram model, AJCC II stage; (C) preoperative nomogram model, AJCC IIIA stage; (D) postoperative nomogram model, AJCC IA/IB stage; (E) postoperative nomogram model, AJCC II stage; (F) postoperative nomogram model, AJCC IIIA stage.
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References

    1. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA: Cancer J Clin (2015) 65(2):87–108. 10.3322/caac.21262 - DOI - PubMed
    1. Bosetti C, Levi F, Boffetta P, Lucchini F, Negri E, La Vecchia C. Trends in mortality from hepatocellular carcinoma in Europe, 1980-2004. Hepatol (Baltimore Md) (2008) 48(1):137–45. 10.1002/hep.22312 - DOI - PubMed
    1. Goh GB, Chang PE, Tan CK. Changing epidemiology of hepatocellular carcinoma in Asia. Best Pract Res Clin Gastroenterol (2015) 29(6):919–28. 10.1016/j.bpg.2015.09.007 - DOI - PubMed
    1. Utsunomiya T, Shimada M, Kudo M, Ichida T, Matsui O, Izumi N, et al. . A comparison of the surgical outcomes among patients with HBV-positive, HCV-positive, and non-B non-C hepatocellular carcinoma: a nationwide study of 11,950 patients. Ann Surg (2015) 261(3):513–20. 10.1097/SLA.0000000000000821 - DOI - PubMed
    1. Nishikawa H, Osaki Y. Non-B, non-C hepatocellular carcinoma (Review). Int J Oncol (2013) 43(5):1333–42. 10.3892/ijo.2013.2061 - DOI - PubMed

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