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J Zhejiang Univ (Med Sci)  2020, Vol. 49 Issue (3): 375-382    DOI: 10.3785/j.issn.1008-9292.2020.06.04
    
Prediction model of mid-term fatality risk after radical resection in patients with hepatocellular carcinoma based on ALBI-grade
WANG Xiaobo1(),ZHANG Zhaohui2,WU Zhangqiang3,SUN Yuezong4,ZHANG Yili5,GONG Ming6,JI Feng1,*()
1. Department of Gastroenterology, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
2. Department of Hepatobiliary and Pancreatic Surgery, Jinhua Hospital of Zhejiang University, Jinhua 321000, Zhejiang Province, China
3. Gastrointestinal Surgery, Jinhua Guangfu Hospital, Jinhua 321000, Zhejiang Province, China
4. Jinhua Hospital of Traditional Chinese Medicine, Jinhua 321000, Zhejiang Province, China
5. Physical Examination Center, Jinhua Hospital of Zhejiang University, Jinhua 321000, Zhejiang Province, China
6. Department of Traditional Chinese Medicine, Jinhua People's Hospital, Jinhua 321000, Zhejiang Province, China
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Abstract  

Objective: To establish a clinical prediction model of the mid-term fatality risk after radical resection in patients with primary hepatocellular carcinoma (HCC) based on the albumin-bilirubin (ALBI) grade and to assess its prediction value. Methods: Clinical data of 533 patients who received HCC radical resection in Jinhua Hospital of Zhejiang University, Jinhua People's Hospital, Jinhua Hospital of Traditional Chinese Medicine and Jinhua Guangfu Hospital from January 2010 to August 2016 were retrospectively reviewed. In the training group (n=407), Cox model was used to screen the clinical risk factors of postoperative death, and a predictive model based on ALBI grade was established and then examined in the validation group (n=126). The value of the prediction model was assessed by ROC curve and calibration curve; the prediction results of the model were visualized by the nomogram for the convenience of clinical use. Results: Cox model showed that ALT ≥ 80 U/L, tumor maximum diameter ≥ 5 cm, portal vein tumor thrombus and ALBI grade 2 were independent risk factors for the prognosis of patients with HCC radical resection. The prognosis index (PI) was 0.550×ALT+0.512×ALBI grade+0.872×maximum tumor diameter+1.377×portal vein tumor thrombus. The AUCs for predicting the risk of death in 12, 36 and 60 months were 0.872, 0.814 and 0.810, respectively (all P < 0.01), and the goodness of fit (r2) of the established model were 0.953, 0.976 and 0.994. AUC of the established model for predicting risk of death in 36 months after resection was 0.814, which was higher than those of ALBI (AUC=0.683), BCLC (AUC=0.713), CLIP (AUC=0.689), Child-Pugh (AUC=0.645), TNM (AUC=0.612) (P < 0.05 or P < 0.01). Conclusion: ALT ≥ 80 U/L, maximum tumor diameter ≥ 5 cm, portal vein tumor thrombus and ALBI grade 2 are independent risk factors of patients after HCC resection, and ALBI grade-based prediction model is satisfactory in prediction of mid-term death risk of the patients.



Key wordsCarcinoma, hepatocellular      Radical resection      Survival rate      Forecasting      Albumin-bilirubin grade     
Received: 01 April 2020      Published: 24 July 2020
CLC:  R735.7  
Corresponding Authors: JI Feng     E-mail: wxb2310@163.com;jifeng@zju.edu.cn
Cite this article:

WANG Xiaobo,ZHANG Zhaohui,WU Zhangqiang,SUN Yuezong,ZHANG Yili,GONG Ming,JI Feng. Prediction model of mid-term fatality risk after radical resection in patients with hepatocellular carcinoma based on ALBI-grade. J Zhejiang Univ (Med Sci), 2020, 49(3): 375-382.

URL:

http://www.zjujournals.com/med/10.3785/j.issn.1008-9292.2020.06.04     OR     http://www.zjujournals.com/med/Y2020/V49/I3/375


基于白蛋白胆红素指数的肝细胞癌根治性手术患者中期死亡风险预测模型评估

目的: 构建基于白蛋白胆红素指数(ALBI)的原发性肝细胞癌(HCC)根治性手术患者中期死亡风险的临床预测模型并验证其预测能力。方法: 采用回顾性队列研究方法,纳入2010年1月至2016年8月于浙江大学金华医院、金华市人民医院、金华市中医医院、金华市广福医院接受HCC根治性手术的533例患者,提取术后生存情况等资料。训练组纳入407例患者,验证组纳入126例患者,两组间基线资料差异无统计学意义(均P>0.05)。训练组样本采用Cox比例风险模型筛选影响HCC患者术后死亡风险的临床危险因素,建立基于ALBI分级的预测模型后在验证组进行验证;使用ROC曲线和预测模型校准图评估预测模型的价值;使用列线图展示模型,方便临床使用。结果: Cox比例风险模型结果显示,丙氨酸转氨酶80 U/L及以上、肿瘤最大径5 cm及以上、门静脉癌栓形成、ALBI分级2级为HCC根治性手术患者预后的独立危险因子。据此建立预测模型,预后指数(PI)=0.550×ALT+0.512×ALBI分级+0.872×肿瘤最大径+1.377×门静脉癌栓。利用验证组样本评价模型预测能力,该模型预测患者术后12、36、60个月死亡风险的AUC分别为0.872、0.814、0.810(均P < 0.01),预测结果的拟合优度(r2)分别为0.953、0.976、0.994。以36个月死亡风险区分能力与经典HCC分期模型比较,基于ALBI的预测模型的AUC为0.814,优于ALBI(AUC=0.683)、巴塞罗那临床肝癌分期(AUC=0.713)、意大利肝癌计划评分(AUC=0.689)、肝功能Child-Pugh分级(AUC=0.645)、肿瘤TNM分期(AUC=0.612)(P < 0.05或P < 0.01)。结论: 丙氨酸转氨酶80 U/L及以上、肿瘤最大径5 cm及以上、门静脉癌栓形成、ALBI分级2级为HCC根治性手术患者死亡风险的独立危险因子,基于ALBI分级构建的预测模型对HCC根治性手术患者中期死亡风险有较高的预测价值。


关键词: 癌, 肝细胞,  根治性手术,  存活率,  预测,  白蛋白胆红素指数分级 
组别n性别
(男/女)
年龄
(<45/≥45岁)
丙氨酸转氨酶
(<80/≥80 U/L)
谷氨酰转移酶
(<34.2/≥34.2 U/L)
超敏C反应蛋白
(<16/≥16 mg/L)
甲胎蛋白
(<400/≥400 μg/L)
肿瘤数目
(单个/多个)
肿瘤最大径
(<5/≥5 cm)
肿瘤包膜
(有/无)
门静脉癌栓
(有/无)
HBsAg
(阳性/阴性)
肝外转移
(是/否)
肝硬化
(有/无)
肿瘤分化程度
(低/中/高)
ALBI分级
(1级/2级)
HBsAg:乙型肝炎表面抗原;ALBI:白蛋白胆红素指数.
训练组407334/7332/375316/91228/179325/82180/227355/52243/164277/13018/389316/91108/299295/112211/134/62313/94
验证组126104/2210/11693/3371/5590/3653/73109/1776/5086/406/120101/2533/9391/3570/38/1895/31
Tab 1 Basic characteristics of patients in training group and validation group  (n)
Fig 1 Survival curves of patients in validation group and training group
危险因素BHR(95%CI)P
丙氨酸转氨酶0.5501.733(1.207~2.486)<0.01
肿瘤最大径0.8722.392(1.698~3.370)<0.01
门静脉癌栓形成1.3773.964(2.255~6.969)<0.01
白蛋白胆红素指数分级0.5121.669(1.164~2.392)<0.01
Tab 2 Multivariate analysis on the risk of death after hepatocellular carcinoma radical resection
Fig 2 ROC curves of albumin-bilirubin-based model for predicting death risks of patients in validation group at 12, 36 and 60 months after hepatocellular carcinoma radical resection
时间AUC约登指数敏感度(%)特异度(%)
术后12个月0.8720.679891.6776.32
术后36个月0.8140.607171.4389.29
术后60个月0.8100.599673.8186.15
Tab 3 Results of ROC analysis of albumin-bilirubin-based model for predicting death risks of patients in validation group at 12, 36 and 60 months after hepatocellular carcinoma radical resection
Fig 3 Calibration curves of albumin-bilirubin-based model for predicting death risks of patients at 12, 36 and 60 months after hepatocellular carcinoma radical resection
Fig 4 ROC curves of ALBI model, BCLC, CLIP, ALBI, Child-Pugh and TNM for predicting death risks of patients 36 months after hepatocellular carcinoma radical resection
Fig 5 Nomogram of ALBI-based prediction model
[1]   曾昭冲 . 肝细胞癌的立体定向放射治疗[J]. 中华肿瘤杂志, 2015, 37 (9): 650- 653
ZENG Zhaochong . Stereotactic radiotherapy for hepatocellular carcinoma[J]. Chinese Journal of Oncology, 2015, 37 (9): 650- 653
doi: 10.3760/cma.j.issn.0253-3766.2015.09.004
[2]   JIANG H T , CAO J Y . Impact of laparoscopic versus openhepatectomy on perioperative clinical outcomes of patients with primary hepatic carcinoma[J]. Chin Med Sci J, 2015, 30 (2): 80- 83
doi: 10.1016/s1001-9294(15)30016-x
[3]   栗雪峰, 李建生, 马金良 et al. 肝癌肝切除手术后肝功能恢复的影响因素分析及风险预测模型建立[J]. 中国普通外科杂志, 2017, 26 (7): 825- 830
LI Xuefeng , LI Jiansheng , MA Jinliang et al. Influential factors for liver function recovery from hepatectomy for liver cancer and risk prediction model establishment[J]. Chinese Journal of General Surgery, 2017, 26 (7): 825- 830
doi: 10.3978/j.issn.1005-6947.2017.07.003
[4]   王嘉译.单发肝癌手术切除患者预后危险因素分析及其评分体系的建立[D].上海: 第二军医大学, 2013.
WANG Jiayi. Prognostic factors associated with survival of patients with single hepatocellular carcinoma after partial hepatectomy[D]. Shanghai: The Second Military Medical University, 2013. (in Chinese)
[5]   蔡庆.145例肝细胞癌根治性切除术后复发相关因素的临床分析[D].广州: 南方医科大学, 2016. DOI: 10.7666/d.Y3116494.
CAI Qing. Clinical analysis of recurrence related factors in 145 cases of hepatocellular carcinoma after radical hepatectomy[D]. Guangzhou: Southern Medical University, 2016. DOI: 10.7666/d.Y3116494.(inChinese)
[6]   陈凯, 杨洪吉, 邓小凡 et al. 肝癌根治性切除术后早期复发危险因素分析及预测模型构建[J]. 中华肿瘤防治杂志, 2018, 25 (5): 344- 348
CHEN Kai , YANG Hongji , DENG Xiaofan et al. Risk factors of primary hepatocellular carcinoma patients early term recurrence after radical resection and prediction model establishment[J]. Chinese Journal of Cancer Prevention and Treatment, 2018, 25 (5): 344- 348
doi: 10.16073/j.cnki.cjcpt.2018.05.008
[7]   李志武, 孙凤永, 袁永胜.探讨原发性肝癌手术预后影响因素[C]//中华临床医师杂志(电子版).2016全国慢性病诊疗论坛论文集.2016: 198-199.
LI Zhiwu, SUN Fengyong, YUAN Yongsheng. Factors influencing the prognosis of primary liver cancer[C]//Chinese Journal of clinicians (Electronic Edition). Proceedings of 2016 national chronic disease diagnosis and treatment forum. 2016: 198-199. (in Chinese)
[8]   PAPATHEODORIDIS G V , CHAN H L , HANSEN B E et al. Risk of hepatocellular carcinoma in chronic hepatitis B:assessment and modification with current antiviral therapy[J]. J Hepatol, 2015, 62 (4): 956- 967
doi: 10.1016/j.jhep.2015.01.002
[9]   EDELINE J , BLANC J F , JOHNSON P et al. A multicentre comparison between Child Pugh and Albumin-Bilirubin scores in patients treated with sorafenib for hepatocellular carcinoma[J]. Liver Int, 2016, 36 (12): 1821- 1828
doi: 10.1111/liv.13170
[10]   LIN C Y , LIN C C , WANG C C et al. The ALBI grade is a good predictive model for very late recurrence in patients with hepatocellular carcinoma undergoing primary resection[J]. World J Surg, 2020, 44 (1): 247- 257
doi: 10.1007/s00268-019-05197-3
[11]   DELONG E R , DELONG D M , CLARKE-PEARSON D L . Comparing the areas under two or more correlated receiver operating characteristic curves:a nonparametric approach[J]. Biometrics, 1988, 44 (3): 837- 845
[12]   LLOVET J M , BUSTAMANTE J , CASTELLS A et al. Natural history of untreated nonsurgical hepatocellular carcinoma:rationale for the design and evaluation of therapeutic trials[J]. Hepatology, 1999, 29 (1): 62- 67
doi: 10.1002/hep.510290145
[13]   王海鹏.原发性肝癌分期方法的比较研究[D].北京: 中国协和医科大学, 2004.
WANG Haipeng. Comparative study on staging methods of primary liver cancer[D]. Beijing: Peking Union Medical College, 2004. (in Chinese)
[14]   PUGH R N H , MYRRAY-LYON I M , DAWSON J L et al. Transection of the esophagus in bleeding oesophageal varices[J]. Br J Surg, 1973, 60 (8): 646- 649
[15]   CUCCURULLO V , MANSI L . AJCC Cancer Staging Handbook:from the AJCC Cancer Staging Manual (7th edition)[J]. Eur J Nucl Med Mol Imaging, 2011, 38 (2): 408
doi: 10.1007/s00259-010-1693-1699
[16]   ALBA A C , AGORITSAS T , WALSH M et al. Discrimination and calibration of clinical prediction models:users' guides to the medical literature[J]. JAMA, 2017, 318 (14): 1377- 1384
doi: 10.1001/jama.2017.12126
[17]   BERARDI G , MORISE Z , SPOSITO C et al. Development of a nomogram to predict outcome after liver resection for hepatocellular carcinoma in Child-Pugh B cirrhosis[J]. J Hepatol, 2020, 72 (1): 75- 84
doi: 10.1016/j.jhep.2019.08.032
[18]   HUANG J L , FU Y P , JING C Y et al. A novel and validated prognostic nomogram based on liver fibrosis and tumor burden for patients with hepatocellular carcinoma after curative resection[J]. J Surg Oncol, 2018, 117 (4): 625- 633
doi: 10.1002/jso.24895
[19]   CHAKRABARTI U , THAKUR M B . Albumin bilirubin (ALBI) score:a new and simple model to predict mortality in patients of acute on chronic liver failure[J]. J Assoc Physicians India, 2020, 68 (1): 91
[20]   ZHANG C H , NI X C , CHEN B Y et al. Combined preoperative albumin-bilirubin (ALBI) and serum γ-glutamyl transpeptidase (GGT) predicts the outcome of hepatocellular carcinoma patients following hepatic resection[J]. J Cancer, 2019, 10 (20): 4836- 4845
doi: 10.7150/jca.33877
[21]   GUI B , WEINER A A , NOSHER J et al. Assessment of the albumin-bilirubin (ALBI) grade as a prognostic indicator for hepatocellular carcinoma patients treated with radioembolization[J]. Am J Clin Oncol, 2018, 41 (9): 861- 866
doi: 10.1097/COC.0000000000000384
[22]   CHAN A W H , LEUNG H H W , CHONG C C N et al. Validating the ALBI grade:its current and future use in HCC prognostication[J]. J Hepatol, 2017, 66 (3): 661- 663
doi: 10.1016/j.jhep.2016.10.037
[23]   侯振宇, 孔银龙, 孙林 et al. 92例晚期肝细胞癌患者肝切除预后及危险因素分析[J]. 天津医科大学学报, 2018, 24 (5): 425- 428
HOU Zhenyu , KONG Yinlong , SUN Lin et al. Prognosis and survival risk factors for 92 advanced hepatocellular carcinoma patients after hepatectomy[J]. Journal of Tianjin Medical University, 2018, 24 (5): 425- 428
[24]   徐成, 李敬东, 石刚 et al. 原发性肝细胞癌行根治性肝切除术后复发的预后因素分析[J]. 中华外科杂志, 2010, 48 (11): 806- 811
XU Cheng , LI Jingdong , SHI Gang et al. Different prognostic factors are associated with early and late intrahepatic recurrence following curative hepatectomy for patients with hepatocellular carcinoma[J]. Chinese Journal of Surgery, 2010, 48 (11): 806- 811
doi: 10.3760/cma.j.issn.0529-5815.2010.11.003
[25]   薛艳.肝细胞癌根治性切除术的预后数学模型的构建及验证[D].大连: 大连医科大学, 2015.
XUE Yan. Establishment and validation of prognosis mathematical model of hepatocellular carcinoma after radical liver resection[D]. Dalian: Dalian Medical University, 2015. (in Chinese)
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