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Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients

BACKGROUND: Microvascular invasion (MVI) is a significant hazard factor that influences the recurrence and survival of hepatocellular carcinoma (HCC) patients after undergoing hepatectomy. This study aimed to develop and validate a nomogram that combines hematological and imaging features of HCC pat...

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Autores principales: Zhou, Qiang, Zhou, Chenhao, Yin, Yirui, Chen, Wanyong, Liu, Chunxiao, Atyah, Manar, Weng, Jialei, Shen, Yinghao, Yi, Yong, Ren, Ning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8033313/
https://www.ncbi.nlm.nih.gov/pubmed/33842623
http://dx.doi.org/10.21037/atm-20-4695
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author Zhou, Qiang
Zhou, Chenhao
Yin, Yirui
Chen, Wanyong
Liu, Chunxiao
Atyah, Manar
Weng, Jialei
Shen, Yinghao
Yi, Yong
Ren, Ning
author_facet Zhou, Qiang
Zhou, Chenhao
Yin, Yirui
Chen, Wanyong
Liu, Chunxiao
Atyah, Manar
Weng, Jialei
Shen, Yinghao
Yi, Yong
Ren, Ning
author_sort Zhou, Qiang
collection PubMed
description BACKGROUND: Microvascular invasion (MVI) is a significant hazard factor that influences the recurrence and survival of hepatocellular carcinoma (HCC) patients after undergoing hepatectomy. This study aimed to develop and validate a nomogram that combines hematological and imaging features of HCC patients to preoperatively predict MVI, and investigate the effect of wide resection margin (≥1 cm) on the prognosis of MVI-positive HCC patients. METHODS: A total of 709 HCC patients who underwent hepatectomy at the Liver Cancer Institute of Zhongshan Hospital, Fudan University between June 1, 2015 and December 30, 2016 were included in this study and divided into training (496 patients) and validation cohort (213 patients). Least absolute shrinkage and selection operator (Lasso) regression and multivariable logistic regression were used for variables’ selection and development of the predictive model. The model was presented as a nomogram, and its performance was assessed in terms of discrimination, calibration and clinical usefulness. RESULTS: Independent prognostic factors such as alkaline phosphatase (ALP, >125 U/L), alpha-fetoprotein (AFP, within 20–400 or >400 ng/mL), protein induced by vitamin K absence-II (PVIKA-II, within 40–400 or >400 mAU/mL), tumor number, diameter, pseudo-capsule, tumor growth pattern and intratumor hemorrhage were incorporated in the nomogram. The model showed good discrimination and calibration, with a concordance index (0.82, 95% CI, 0.782–0.857) in the training cohort and C-index (0.80, 95% CI, 0.772–0.837) in the validation cohort. Decision curve analysis (DCA) also showed that this model is clinically useful. Moreover, HCC patients with wide resection margin had a significantly lower 3-year recurrence rate than those with narrower resection margin (0.5–1 cm). CONCLUSIONS: This study presents an optimal model for preoperative prediction of MVI and shows that wide resection margin for MVI-positive HCC patients has a better prognosis. This model can help surgeons choose the best treatment options for HCC patients before and after the operation.
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spelling pubmed-80333132021-04-09 Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients Zhou, Qiang Zhou, Chenhao Yin, Yirui Chen, Wanyong Liu, Chunxiao Atyah, Manar Weng, Jialei Shen, Yinghao Yi, Yong Ren, Ning Ann Transl Med Original Article BACKGROUND: Microvascular invasion (MVI) is a significant hazard factor that influences the recurrence and survival of hepatocellular carcinoma (HCC) patients after undergoing hepatectomy. This study aimed to develop and validate a nomogram that combines hematological and imaging features of HCC patients to preoperatively predict MVI, and investigate the effect of wide resection margin (≥1 cm) on the prognosis of MVI-positive HCC patients. METHODS: A total of 709 HCC patients who underwent hepatectomy at the Liver Cancer Institute of Zhongshan Hospital, Fudan University between June 1, 2015 and December 30, 2016 were included in this study and divided into training (496 patients) and validation cohort (213 patients). Least absolute shrinkage and selection operator (Lasso) regression and multivariable logistic regression were used for variables’ selection and development of the predictive model. The model was presented as a nomogram, and its performance was assessed in terms of discrimination, calibration and clinical usefulness. RESULTS: Independent prognostic factors such as alkaline phosphatase (ALP, >125 U/L), alpha-fetoprotein (AFP, within 20–400 or >400 ng/mL), protein induced by vitamin K absence-II (PVIKA-II, within 40–400 or >400 mAU/mL), tumor number, diameter, pseudo-capsule, tumor growth pattern and intratumor hemorrhage were incorporated in the nomogram. The model showed good discrimination and calibration, with a concordance index (0.82, 95% CI, 0.782–0.857) in the training cohort and C-index (0.80, 95% CI, 0.772–0.837) in the validation cohort. Decision curve analysis (DCA) also showed that this model is clinically useful. Moreover, HCC patients with wide resection margin had a significantly lower 3-year recurrence rate than those with narrower resection margin (0.5–1 cm). CONCLUSIONS: This study presents an optimal model for preoperative prediction of MVI and shows that wide resection margin for MVI-positive HCC patients has a better prognosis. This model can help surgeons choose the best treatment options for HCC patients before and after the operation. AME Publishing Company 2021-03 /pmc/articles/PMC8033313/ /pubmed/33842623 http://dx.doi.org/10.21037/atm-20-4695 Text en 2021 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Zhou, Qiang
Zhou, Chenhao
Yin, Yirui
Chen, Wanyong
Liu, Chunxiao
Atyah, Manar
Weng, Jialei
Shen, Yinghao
Yi, Yong
Ren, Ning
Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients
title Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients
title_full Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients
title_fullStr Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients
title_full_unstemmed Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients
title_short Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients
title_sort development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8033313/
https://www.ncbi.nlm.nih.gov/pubmed/33842623
http://dx.doi.org/10.21037/atm-20-4695
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