基于术前纤维蛋白原与白蛋白比值构建肝癌微血管侵犯的预测模型

doi:10.3877/cma.j.issn.2095-3232.2024.01.006

目的

探讨纤维蛋白原（FIB）与ALB比值（FAR）对肝细胞癌（肝癌）微血管侵犯（MVI）的预测价值。

方法

回顾性分析2013年1月至2020年10月在北京医院接受手术治疗的193例肝癌患者临床资料。患者均签署知情同意书，符合医学伦理学规定。其中男162例，女31例；平均年龄（60±13）岁。术后病理检查证实合并MVI 88例。收集患者术前血清FIB、ALB等数据，计算FAR。采用ROC曲线分析FAR诊断价值。采用Logistic回归模型分析MVI发生的影响因素。根据多因素分析结果构建MVI预测列线图。采用Unreliability检验评估该列线图的预测效果。

结果

FAR诊断MVI的最佳界值为0.057时，将患者分为高FAR组130例，低FAR组63例。Logistic多因素回归分析显示，肿瘤直径≥3 cm（OR=3.263，95%CI：1.300～6.261，P=0.010）、AFP≥400 μg/L（OR=2.818，95%CI：1.214～6.542，P=0.016）、AFP 20～400 μg/L（OR=2.326，95%CI：1.026～5.271，P=0.043）、总蛋白≥85 g/L（OR=1.107，95%CI：1.038～1.181，P=0.002）和FAR≥0.057（OR=2.600，95%CI：1.079～6.261，P=0.033）是MVI的独立危险因素。将肿瘤直径、AFP、总蛋白和FAR纳入构建列线图，ROC曲线下面积为0.755，校正曲线显示效果良好（P=0.956）。

结论

基于FAR建立的肝癌MVI临床预测模型简便可靠，有助于MVI高危肝癌患者的早期识别，制定更为精准的治疗方案。

关键词: 癌，肝细胞, 微血管侵犯, 纤维蛋白原与白蛋白比值, 列线图

Objective

To evaluate the predictive value of fibrinogen (FIB)-to-albumin (ALB) ratio (FAR) for microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Methods

Clinical data of 193 patients with liver cancer who underwent surgical treatment in Beijing Hospital from January 2013 to October 2020 were retrospectively analyzed. The informed consents of all patients were obtained and the local ethical committee approval was received. Among them, 162 patients were male and 31 female, aged (60±13) years on average. 88 cases were confirmed with MVI by postoperative pathological examination. Preoperative serum FIB, ALB and other data were collected and the FAR was calculated. The diagnostic value of FAR was analyzed by the ROC curve. The influencing factors of MVI were assessed by Logistic regression model. According to the results of multivariate analysis, the nomogram for predicting MVI was established. The prediction efficacy of this nomogram was evaluated by Unreliability test.

Results

When the optimal cut-off value of FAR in diagnosing MVI was 0.057, all patients were divided into high group (n=130) and low FAR group (n=63). Multivariate Logistic regression analysis showed that tumor diameter ≥3 cm (OR=3.263, 95%CI: 1.300-6.261, P=0.010), AFP≥400 μg/L (OR=2.818, 95%CI:1.214-6.542, P=0.016); AFP 20-400 μg/L,(OR=2.326, 95%CI:1.026-5.271, P=0.043), total protein (OR=1.107, 95%CI:1.038-1.181, P=0.002) and FAR (OR=2.600, 95%CI:1.079-6.261, P=0.033) were independent risk factors for MVI. Tumor diameter, AFP, total protein and FAR were included in the nomogram, and the area under the ROC curve was 0.755, and the calibration curve showed high efficacy (P=0.956).

Conclusions

Clinical prediction model for MVI of liver cancer based on FAR is simple and reliable, which contributes to early identification of high-risk HCC patients with MVI and making more precise treatment regimens.

Key words: Carcinoma, hepatocellular, Microvascular invasion, Fibrinogen-to-albumin ratio, Nomogram

表1 FAR与肝癌患者临床病理参数的关系[例（%）]

组别	例数	年龄≥65岁	性别男	HBV感染	肿瘤多发	肿瘤直径≥3 cm	AFP（μg/L）			BMI（kg/m²，±s）
组别	例数	年龄≥65岁	性别男	HBV感染	肿瘤多发	肿瘤直径≥3 cm	≥400	20～400	<20	BMI（kg/m²，±s）
高FAR组	130	53（40.8）	110（84.6）	87（66.9）	10（7.7）	109（83.8）	26（20.0）	28（21.5）	76（58.5）	24±3
低FAR组	63	21（33.3）	52（82.5）	54（85.7）	9（14.3）	42（66.7）	13（20.6）	13（20.6）	37（58.8）	25±3
统计值		χ²=0.992	χ²=0.136	χ²=7.613	χ²=2.079	χ²=7.356	χ²=0.025			t=-0.260
P值		0.319	0.713	0.006	0.149	0.007	0.987			0.795

表1 FAR与肝癌患者临床病理参数的关系[例（%）]

组别	例数	年龄≥65岁	性别男	HBV感染	肿瘤多发	肿瘤直径≥3 cm	AFP（μg/L）			BMI（kg/m²，±s）
组别	例数	年龄≥65岁	性别男	HBV感染	肿瘤多发	肿瘤直径≥3 cm	≥400	20～400	<20	BMI（kg/m²，±s）
高FAR组	130	53（40.8）	110（84.6）	87（66.9）	10（7.7）	109（83.8）	26（20.0）	28（21.5）	76（58.5）	24±3
低FAR组	63	21（33.3）	52（82.5）	54（85.7）	9（14.3）	42（66.7）	13（20.6）	13（20.6）	37（58.8）	25±3
统计值		χ²=0.992	χ²=0.136	χ²=7.613	χ²=2.079	χ²=7.356	χ²=0.025			t=-0.260
P值		0.319	0.713	0.006	0.149	0.007	0.987			0.795

表2 肝癌患者MVI发生的影响因素分析

变量	单因素分析		多因素分析
变量	OR（95%CI）	P值	OR（95%CI）	P值
年龄≥65岁	0.937（0.523～1.678）	0.048	0.962（0.491～1.886）	0.910
肿瘤直径≥3 cm	4.023（1.802～8.983）	0.001	3.263（1.300～6.261）	0.012
AFP≥400 μg/L	3.136（1.469～6.694）	0.003	2.818（1.214～6.542）	0.016
AFP 20～400 μg/L	2.033（0.986～4.193）	0.055	2.326（1.026～5.271）	0.043
总蛋白≥85 g/L	1.109（1.047～1.175）	<0.001	1.107（1.038～1.181）	0.002
FAR≥0.057	2.917（1.528～5.566）	0.001	2.600（1.079～6.261）	0.033
NLR≥2.1	2.504（1.377～4.554）	0.003	1.658（0.833～3.300）	0.150

表2 肝癌患者MVI发生的影响因素分析

变量	单因素分析		多因素分析
变量	OR（95%CI）	P值	OR（95%CI）	P值
年龄≥65岁	0.937（0.523～1.678）	0.048	0.962（0.491～1.886）	0.910
肿瘤直径≥3 cm	4.023（1.802～8.983）	0.001	3.263（1.300～6.261）	0.012
AFP≥400 μg/L	3.136（1.469～6.694）	0.003	2.818（1.214～6.542）	0.016
AFP 20～400 μg/L	2.033（0.986～4.193）	0.055	2.326（1.026～5.271）	0.043
总蛋白≥85 g/L	1.109（1.047～1.175）	<0.001	1.107（1.038～1.181）	0.002
FAR≥0.057	2.917（1.528～5.566）	0.001	2.600（1.079～6.261）	0.033
NLR≥2.1	2.504（1.377～4.554）	0.003	1.658（0.833～3.300）	0.150

图1 预测肝细胞癌MVI的列线图注：FAR为纤维蛋白原与白蛋白比值，MVI为微血管侵犯

图2 预测肝癌MVI的列线图校准曲线及拟合优度检验注：C（ROC）为曲线下面积；S：p为Unreliability检验P值

图3 预测肝癌MVI的列线图决策曲线注：曲线All表示所有患者均按微血管侵犯（MVI）阳性进行临床干预获益情况，直线None表示所有患者均按MVI阴性进行临床干预获益情况

[1]	Zheng R, Zhang S, Zeng H, et al. Cancer incidence and mortality in China, 2016[J]. J Nat Cancer Center, 2022, 2(1):1-9.
[2]	中华人民共和国国家卫生健康委员会医政医管局. 原发性肝癌诊疗指南(2022年版)[J]. 中华消化外科杂志, 2022, 21(2):143-68.
[3]	Chen ZH, Zhang XP, Wang H, et al. Effect of microvascular invasion on the postoperative long-term prognosis of solitary small HCC: a systematic review and meta-analysis[J]. HPB, 2019, 21(8):935-944.
[4]	Zhang XP, Wang K, Wei XB, et al. An eastern hepatobiliary surgery hospital microvascular invasion scoring system in predicting prognosis of patients with hepatocellular carcinoma and microvascular invasion after R0 liver resection: a large-scale, multicenter study[J]. Oncologist, 2019, 24(12):e1476-1488.
[5]	Wang W, Guo Y, Zhong J, et al. The clinical significance of microvascular invasion in the surgical planning and postoperative sequential treatment in hepatocellular carcinoma[J]. Sci Rep, 2021, 11(1):2415.
[6]	Zhang LP, Ren H, Du YX, et al. Prognostic value of the preoperative fibrinogen-to-albumin ratio in pancreatic ductal adenocarcinoma patients undergoing R0 resection[J]. World J Gastroenterol, 2020, 26(46):7382-7404.
[7]	叶莹鹏, 杨勇, 蔡星晨, 等. 单发大肝癌术后早期复发危险因素分析[J]. 中华普通外科杂志, 2023, 38(1):1-6.
[8]	Zhong XP, Zhang YF, Mei J, et al. Anatomical versus non-anatomical resection for hepatocellular carcinoma with microscope vascular invasion: a propensity score matching analysis[J]. J Cancer, 2019, 10(17):3950-3957.
[9]	Okamura Y, Sugiura T, Ito T, et al. Anatomical resection is useful for the treatment of primary solitary hepatocellular carcinoma with predicted microscopic vessel invasion and/or intrahepatic metastasis[J]. Surg Today, 2021, 51(9):1429-1439.
[10]	Sun Z, Li Z, Shi XL, et al. Anatomic versus non-anatomic resection of hepatocellular carcinoma with microvascular invasion: a systematic review and meta-analysis[J]. Asian J Surg, 2021, 44(9): 1143-1150.
[11]	Zhou J, Sun H, Wang Z, et al. Guidelines for the diagnosis and treatment of hepatocellular carcinoma (2019 edition)[J]. Liver Cancer, 2020, 9(6):682-720.
[12]	Ma XL, Tang WG, Yang MJ, et al. Serum STIP1, a novel indicator for microvascular invasion, predicts outcomes and treatment response in hepatocellular carcinoma[J]. Front Oncol, 2020(10):511.
[13]	Zhang H, Zhou Y, Li Y, et al. Predictive value of gamma-glutamyl transpeptidase to lymphocyte count ratio in hepatocellular carcinoma patients with microvascular invasion[J]. BMC Cancer, 2020, 20(1): 132.
[14]	Wang Q, Li C, Zhang J, et al. Radiomics models for predicting microvascular invasion in hepatocellular carcinoma: a systematic review and radiomics quality score assessment[J]. Cancers, 2021, 13(22):5864.
[15]	Zhong X, Peng J, Xie Y, et al. A nomogram based on multi-modal ultrasound for prediction of microvascular invasion and recurrence of hepatocellular carcinoma[J]. Eur J Radiol, 2022(151):110281.
[16]	Ghanim B, Hoda MA, Klikovits T, et al. Circulating fibrinogen is a prognostic and predictive biomarker in malignant pleural mesothelioma[J]. Br J Cancer, 2014, 110(4):984-990.
[17]	Gan W, Yi Y, Fu Y, et al. Fibrinogen and C-reactive protein score is a prognostic index for patients with hepatocellular carcinoma undergoing curative resection: a prognostic nomogram study[J]. J Cancer, 2018, 9(1):148-156.
[18]	Staton CA, Brown NJ, Lewis CE. The role of fibrinogen and related fragments in tumour angiogenesis and metastasis[J]. Expert Opin Biol Ther, 2003, 3(7):1105-1120.
[19]	Kwaan HC, Lindholm PF. Fibrin and fibrinolysis in cancer[J]. Semin Thromb Hemost, 2019, 45(4):413-422.
[20]	Dai T, Peng L, Lin G, et al. Preoperative elevated plasma fibrinogen level predicts tumor recurrence and poor prognosis in patients with hepatocellular carcinoma[J]. J Gastrointest Oncol, 2019, 10(6):1049-1063.
[21]	Wang L, Li Q, Zhang J, et al. A novel prognostic scoring model based on albumin and gamma-glutamyltransferase for hepatocellular carcinoma prognosis[J]. Cancer Manag Res, 2019(11):10685-10694.
[22]	Sun DW, An L, Lv GY. Albumin-fibrinogen ratio and fibrinogen-prealbumin ratio as promising prognostic markers for cancers: an updated meta-analysis[J]. World J Surg Oncol, 2020, 18(1):9.
[23]	Xu Q, Yan Y, Gu S, et al. A novel inflammation-based prognostic score: the fibrinogen/albumin ratio predicts prognoses of patients after curative resection for hepatocellular carcinoma[J]. J Immunol Res, 2018:4925498.
[24]	Prieto J, Melero I, Sangro B. Immunological landscape and immunotherapy of hepatocellular carcinoma[J]. Nat Rev Gastroenterol Hepatol, 2015, 12(12):681-700.
[25]	Mantovani A, Ponzetta A, Inforzato A, et al. Innate immunity, inflammation and tumour progression: double-edged swords[J]. J Intern Med, 2019, 285(5):524-532.
[26]	Brostjan C, Oehler R. The role of neutrophil death in chronic inflammation and cancer[J]. Cell Death Discov, 2020(6):26.
[27]	Zhang J, Huang SH, Li H, et al. Preoperative lymphocyte count is a favorable prognostic factor of disease-free survival in non-small-cell lung cancer[J]. Med Oncol, 2013, 30(1):352.
[28]	Mjaess G, Chebel R, Karam A, et al. Prognostic role of neutrophil-to-lymphocyte ratio (NLR) in urological tumors: an umbrella review of evidence from systematic reviews and meta-analyses[J]. Acta Oncol, 2021, 60(6):704-713.
[29]	Chan SWS, Smith E, Aggarwal R, et al. Systemic inflammatory markers of survival in epidermal growth factor-mutated non-small-cell lung cancer: single-institution analysis, systematic review, and meta-analysis[J]. Clin Lung Cancer, 2021, 22(5):390-407.
[30]	Pravisani R, Mocchegiani F, Isola M, et al. Postoperative trends and prognostic values of inflammatory and nutritional biomarkers after liver transplantation for hepatocellular carcinoma[J]. Cancers, 2021, 13(3):513.
[31]	Feliciano EMC, Kroenke CH, Meyerhardt JA, et al. Association of systemic inflammation and sarcopenia with survival in nonmetastatic colorectal cancer: results from the C SCANS study[J]. JAMA Oncol, 2017, 3(12):e172319.
[32]	于艳龙, 刘中华, 史赢, 等. 术前中性粒细胞与淋巴细胞比值和肿瘤相关因素预测肝癌患者微血管浸润[J]. 中华肝胆外科杂志, 2019, 25(2):120-123.
[33]	Margonis GA, Sergentanis TN, Ntanasis-Stathopoulos I, et al. Impact of surgical margin width on recurrence and overall survival following R0 hepatic resection of colorectal metastases: a systematic review and meta-analysis[J]. Ann Surg, 2018, 267(6):1047-1055.
[34]	Zheng J, Chakraborty J, Chapman WC, et al. Preoperative prediction of microvascular invasion in hepatocellular carcinoma using quantitative image analysis[J]. J Am Coll Surg, 2017, 225(6):778-788, e1.
[35]	Lei Z, Li J, Wu D, et al. Nomogram for preoperative estimation of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma within the Milan criteria[J]. JAMA Surg, 2016, 151(4): 356-363.
[36]	Chen S, Ji R, Shi X, et al. Retrospective analysis of efficacy, safety, and prognostic factors in a cohort of Chinese hepatocellular carcinoma patients treated with drug-eluting bead transarterial chemoembolization[J]. Braz J Med Biol Res, 2019, 52(12):e8467.

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Establishment of prediction model for microvascular invasion of hepatocellular carcinoma based on preoperative fibrinogen-to-albumin ratio

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Establishment of prediction model for microvascular invasion of hepatocellular carcinoma based on preoperative fibrinogen-to-albumin ratio