Using Systemic Inflammatory Markers to Predict Microvascular Invasion Before Surgery in Patients With Hepatocellular Carcinoma
Copyright © 2022 Li, Zeng, Liang, Long, Liu, Xiao and Sun..
Background: Mounting studies reveal the relationship between inflammatory markers and post-therapy prognosis. Yet, the role of the systemic inflammatory indices in preoperative microvascular invasion (MVI) prediction for hepatocellular carcinoma (HCC) remains unclear.
Patients and Methods: In this study, data of 1,058 cases of patients with HCC treated in the First Affiliated Hospital of Sun Yat-sen University from February 2002 to May 2018 were collected. Inflammatory factors related to MVI diagnosis in patients with HCC were selected by least absolute shrinkage and selection operator (LASSO) regression analysis and were integrated into an "Inflammatory Score." A prognostic nomogram model was established by combining the inflammatory score and other independent factors determined by multivariate logistic regression analysis. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to evaluate the predictive efficacy of the model.
Results: Sixteen inflammatory factors, including neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, etc., were selected by LASSO regression analysis to establish an inflammatory score. Multivariate logistic regression analysis showed that inflammatory score (OR = 2.14, 95% CI: 1.63-2.88, p < 0.001), alpha fetoprotein (OR = 2.02, 95% CI: 1.46-2.82, p < 0.001), and tumor size (OR = 2.37, 95% CI: 1.70-3.30, p < 0.001) were independent factors for MVI. These three factors were then used to establish a nomogram for MVI prediction. The AUC for the training and validation group was 0.72 (95% CI: 0.68-0.76) and 0.72 (95% CI: 0.66-0.78), respectively.
Conclusion: These findings indicated that the model drawn in this study has a high predictive value which is capable to assist the diagnosis of MVI in patients with HCC.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:9 |
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| Enthalten in: |
Frontiers in surgery - 9(2022) vom: 01., Seite 833779 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Li, Shumin [VerfasserIn] |
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| Links: |
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| Themen: |
Hepatocellular carcinoma (HCC) |
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| Anmerkungen: |
Date Revised 22.03.2022 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.3389/fsurg.2022.833779 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM338409521 |
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| 520 | |a Copyright © 2022 Li, Zeng, Liang, Long, Liu, Xiao and Sun. | ||
| 520 | |a Background: Mounting studies reveal the relationship between inflammatory markers and post-therapy prognosis. Yet, the role of the systemic inflammatory indices in preoperative microvascular invasion (MVI) prediction for hepatocellular carcinoma (HCC) remains unclear | ||
| 520 | |a Patients and Methods: In this study, data of 1,058 cases of patients with HCC treated in the First Affiliated Hospital of Sun Yat-sen University from February 2002 to May 2018 were collected. Inflammatory factors related to MVI diagnosis in patients with HCC were selected by least absolute shrinkage and selection operator (LASSO) regression analysis and were integrated into an "Inflammatory Score." A prognostic nomogram model was established by combining the inflammatory score and other independent factors determined by multivariate logistic regression analysis. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to evaluate the predictive efficacy of the model | ||
| 520 | |a Results: Sixteen inflammatory factors, including neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, etc., were selected by LASSO regression analysis to establish an inflammatory score. Multivariate logistic regression analysis showed that inflammatory score (OR = 2.14, 95% CI: 1.63-2.88, p < 0.001), alpha fetoprotein (OR = 2.02, 95% CI: 1.46-2.82, p < 0.001), and tumor size (OR = 2.37, 95% CI: 1.70-3.30, p < 0.001) were independent factors for MVI. These three factors were then used to establish a nomogram for MVI prediction. The AUC for the training and validation group was 0.72 (95% CI: 0.68-0.76) and 0.72 (95% CI: 0.66-0.78), respectively | ||
| 520 | |a Conclusion: These findings indicated that the model drawn in this study has a high predictive value which is capable to assist the diagnosis of MVI in patients with HCC | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a hepatocellular carcinoma (HCC) | |
| 650 | 4 | |a inflammatory markers | |
| 650 | 4 | |a microvascular invasion (MVI) | |
| 650 | 4 | |a predictive model | |
| 650 | 4 | |a surgery | |
| 700 | 1 | |a Zeng, Qianwen |e verfasserin |4 aut | |
| 700 | 1 | |a Liang, Ruiming |e verfasserin |4 aut | |
| 700 | 1 | |a Long, Jianyan |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Yihao |e verfasserin |4 aut | |
| 700 | 1 | |a Xiao, Han |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Kaiyu |e verfasserin |4 aut | |
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