The nomogram based on preoperative inflammatory biomarkers used for predicting the prognosis of HCC patients treated with transcatheter arterial chemoembolization:its construction and validation
10.3969/j.issn.1008-794X.2024.03.005
- VernacularTitle:基于术前炎症指标构建和验证肝癌患者TACE治疗预后的列线图
- Author:
Dongxu ZHAO
1
;
Binyan ZHONG
;
Zhongheng HOU
;
Yi ZHAN
;
Caifang NI
Author Information
1. 215006 江苏苏州 苏州大学附属第一医院介入科
- Keywords:
hepatocellular carcinoma;
transarterial chemoembolization;
inflammatory indicator;
prognosis;
prediction model
- From:
Journal of Interventional Radiology
2024;33(3):245-258
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct and validate a predictive model based on preoperative inflammatory biomarkers,and to evaluate its ability in predicting the prognosis of patients with unresectable hepatocellular carcinoma(HCC)after receiving transcatheter arterial chemoembolization(TACE).Methods A total of 544 patients with HCC,who received TACE as the initial treatment at six medical institutions between January 2007 and December 2020,were retrospectively collected.The patients were divided into training cohort(n=376)and validation cohort(n=168).LASSO algorithm and Cox regression analysis were used to screen out the independent influencing factors and to make modelling.The model was validated based on the discrimination,calibration and clinical applicability,and the Kaplan-Meier risk stratification curves were plotted to determine the prognostic differences between groups.The likelihood ratio chi-square value,R2 value,akaike information criterion(AIC)value,C-index and AUROC value of the model were calculated to determine its accuracy and efficiency.Results The training cohort and validation cohort had 376 participants and 168 participants respectively.Multivariate analysis indicated that BCLC,tumor size,number of tumor lesions,neutrophil and prognostic nutritional index(PNI)were the independent influencing factors for postoperative overall survival(OS),with all P being＜0.05;the BCLC grade,tumor size,number of tumor lesions,NLR,PNI and PS score were the independent influencing factors for progression-free survival(PFS),with all P being＜0.05.The C-indexes of the OS and PFS models were 0.735(95％ CI=0.708-0.762)and 0.736(95％ CI=0.711-0.761)respectively,and the external validation was 0.721(95％ CI=0.680-0.762)and 0.693(95％ CI=0.656-0.730)respectively.Ideal discrimination ability of the nomogram was exhibited in time-dependent C-index,time-dependent ROC,and time-dependent AUC.The calibration curves significantly coincided with the ideal standard lines,indicating that the model had high stability and low over-fitting level.Decision curve analysis revealed that there was a wider range of threshold probabilities and it could augment net benefits.The Kaplan-Meier curves for risk stratification indicated that the prognosis of patients varied dramatically between risk categories(P＜0.000 1).The Kaplan-Meier curves for risk stratification indicated that the prognosis of patients varied dramatically among different risk groups(P＜0.000 1).The likelihood ratio chi-square value,R2 value,AIC value,C-index and AUROC value of the model were better than those of other models commonly used in clinical practice.Conclusion The newly-developed prognostic nomogram based on preoperative inflammatory indicators has excellent accuracy as well as excellent prediction effect in predicting the prognosis of patients with unresectable HCC after receiving TACE,therefore,it can be used as an effective tool for guiding individualized treatment and for predicting prognosis.(J Intervent Radiol,2024,33:245-258)
