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Screening of Hepatocellular Carcinoma Patients with High Risk of Early Recurrence After Radical Hepatectomy Using a Nomogram Model Based on the γ-Glutamyl Transpeptidase-to-Albumin Ratio

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Journal of Gastrointestinal Surgery Aims and scope

Abstract

Background and purpose

The present study aimed to establish a γ-glutamyl transpeptidase-to-albumin ratio (GAR)-based nomogram model to predict early recurrence of hepatocellular carcinoma (HCC) after radical surgery.

Methods

Patients enrolled in this study were randomly allocated into a train and validation cohort in a ratio of 7:3. The Least Absolute Shrinkage and Selection Operator (LASSO) proportional hazards model and cox regression model were combined to identify independent risk factors related to HCC recurrence. Based on these risk factors, a predictive nomogram was constructed and validated in both inner and outer test cohorts. The performance of the nomogram was evaluated by C-index, the area under the receiver operating characteristic curve (AUC), the calibration curve and decision curve analysis.

Results

The tumor size, tumor number, BCLC stage, microvascular invasion (MVI) and GAR value were identified as independent risk factors related to HCC recurrence and used to construct the predictive nomogram. AUC of the nomogram showed satisfactory accuracy in predicting 1-, 3- and 5-year disease-free survival. The calibration curve showed agreement between the ideal and predicted values. The risk score more than 72 as calculated by the nomogram was related to early recurrence of HCC after radical surgery. DCA plots showed better clinical usability of the nomogram as compared with the BCLC staging system in all three included cohorts.

Conclusion

The nomogram based on the GAR value may provide a new option for screening of the target HCC cohort of patients who need anti-recurrence therapy after surgery.

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Data Availability

Our cohort data are available from the corresponding author (Ning Yang, email: lancet00@163.com) upon reasonable request.

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Author names in bold designate shared co-first authorship.

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Acknowledgements

None

Funding

This study was supported by the State Key Project for Liver Cancer (2012ZX10002017-004,2017ZX10203205-001-002). The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.

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Authors and Affiliations

Authors

Contributions

Shujie Pang contributed to project development, data collection, data analysis, manuscript drafting and approval of the final version.

Yang Shi contributed to manuscript drafting, data collection and analysis and approval of the final version.

Dapeng Xu contributed to analysis and interpretation data, and approval of the final version.

Zhe Sun contributed to data collection and analysis, and approval of the final version.

Yiming Chen, Yingcheng Yang and Xijun Zhao contributed to data collection and approval of the final version.

Hui Sima contributed to conception of this work, interpretation of data, revising the manuscript and approval of the final version.

Ning Yang contributed to project design, data analysis and interpretation, manuscript editing, agreement to be accountable for all aspects of this work and approval of the final version.

This work was not presented at any scientific meeting.

Corresponding authors

Correspondence to Hui Si-ma or Ning Yang.

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Conflict of Interest-Form

The authors declared that there was no conflict of interest. Conflict of interest-forms completed by all authors were submitted by Prof. Ning Yang along with the manuscript.

Ethical Standards

This retrospective study was approved by the research ethics committee of the Eastern Hepatobiliary Surgery Hospital and complied with the Declaration of Helsinki Principles. Informed consent was obtained from all patients for their data to be used in the study.

Sex Inclusive Reporting

The current study was not involved in sex selection with respect to patient inclusion.

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Supplementary Information

Fig Supplementary 1

Calibration curves and DCA plots for the validation cohorts. a Calibration curve and C-index for the validation cohort. b Calibration curve and C-index for the outer cohort. c DCA plot for the validation cohort. d DCA plot for the outer cohort (PNG 328 kb)

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Cite this article

Pang, S., Shi, Y., Xu, D. et al. Screening of Hepatocellular Carcinoma Patients with High Risk of Early Recurrence After Radical Hepatectomy Using a Nomogram Model Based on the γ-Glutamyl Transpeptidase-to-Albumin Ratio. J Gastrointest Surg 26, 1–9 (2022). https://doi.org/10.1007/s11605-022-05326-9

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