aMAP评分联合RAR及PIV构建慢性肝病患者肝细胞癌发生风险的预测模型

doi:10.11958/20241112

天津医药 ›› 2025, Vol. 53 ›› Issue (1): 42-46.doi: 10.11958/20241112

aMAP评分联合RAR及PIV构建慢性肝病患者肝细胞癌发生风险的预测模型

蒋晓涵(), 曹杰(), 刘丹丹, 薛丹, 郭志国

安徽医科大学附属宿州医院（安徽省宿州市立医院）消化内科（邮编234000

收稿日期:2024-08-19 修回日期:2024-10-29 出版日期:2025-01-15 发布日期:2025-02-06
通讯作者: ^△E-mail：caojiewen@126.com
作者简介:蒋晓涵（1993），女，主治医师，主要从事消化系统常见病及肿瘤性疾病的临床和内镜诊治研究。E-mail：jxhanhan1993@163.com
基金资助:
宿州市卫生健康科研项目(SZWJ2022a038)

Constructing a risk prediction model for hepatocellular carcinoma in patients with chronic liver disease based on aMAP score combined with RAR and PIV

JIANG Xiaohan(), CAO Jie(), LIU Dandan, XUE Dan, GUO Zhiguo

Department of Gastroenterology, Suzhou Hospital of Anhui Medical University, Suzhou Municipal Hospital of Anhui Province, Suzhou 234000, China

Received:2024-08-19 Revised:2024-10-29 Published:2025-01-15 Online:2025-02-06
Contact: ^△E-mail：caojiewen@126.com

蒋晓涵, 曹杰, 刘丹丹, 薛丹, 郭志国. aMAP评分联合RAR及PIV构建慢性肝病患者肝细胞癌发生风险的预测模型[J]. 天津医药, 2025, 53(1): 42-46.

JIANG Xiaohan, CAO Jie, LIU Dandan, XUE Dan, GUO Zhiguo. Constructing a risk prediction model for hepatocellular carcinoma in patients with chronic liver disease based on aMAP score combined with RAR and PIV[J]. Tianjin Medical Journal, 2025, 53(1): 42-46.

摘要/Abstract

摘要：

目的基于aMAP评分联合RAR及PIV构建并验证慢性肝病患者肝细胞癌（HCC）发生风险的预测模型。方法 143例慢性肝病患者按照是否发生HCC分为HCC组32例及非HCC组111例，比较2组一般临床资料、aMAP评分及外周血指标水平。采用多因素Logistic回归分析住院慢性肝病患者发生HCC的影响因素，构建并验证列线图风险预测模型。结果与非HCC组比较，HCC组年龄大、男性比例高，总胆红素（TBIL）、红细胞分布宽度（RDW）、中性粒细胞计数（NEU）、单核细胞计数（MON）、aMAP评分、RDW与ALB比值（RAR）、泛免疫炎症值（PIV）水平高，白蛋白（ALB）、淋巴细胞计数（LYM）水平低（P<0.05）。多因素Logistic回归分析显示，较高aMAP评分、RAR、PIV是住院慢性肝病患者HCC风险的独立危险因素（P<0.05）；据此构建的列线图风险预测模型受试者工作特征（ROC）曲线的曲线下面积（AUC）为0.823（95%CI：0.747~0.899），校准曲线显示预测值与实际观测值基本一致，Brier得分为0.125，决策曲线显示该模型具有明显的正向效益，Bootstrap法对预测模型进行内部验证的AUC为0.823（95%CI：0.820~0.825），提示模型具有良好的区分度。结论 aMAP评分联合RAR及PIV构建的慢性肝病患者发生HCC的列线图风险预测模型预测性能良好，有助于指导个体化治疗及随访。

关键词: 癌, 肝细胞, 列线图, ROC曲线, aMAP评分, 慢性肝病, 红细胞分布宽度与白蛋白比值, 泛免疫炎症值

Abstract:

Objective To construt and validate a risk prediction model for hepatocellular carcinoma (HCC) in patients with chronic liver disease based on age-male -ALBI-platelets (aMAP) score combined with RAR and PIV.Methods A total of 143 patients with chronic liver disease were divided into the HCC group (32 cases) and the non-HCC group (111 cases) according to whether HCC occurred. General clinical data, aMAP score and peripheral blood indicator level were compared between two groups. Multivariate Logistic regression was used to analyze influencing factors of HCC in inpatients with chronic liver disease. A nomogram risk prediction model was constructed and validated.Results Compared with the non-HCC group, there were higher age, higher proportion of males, higher levels of total bilirubin (TBIL), red blood cell distribution width (RDW), neutrophil count (NEU) and monocyte count (MON), lower levels of albumin (ALB) and lymphocyte count (LYM), higher levels of aMAP score, RDW to ALB (RAR) and pan-immune inflammation value (PIV) in the HCC group (P<0.05). Multivariate Logistic regression showed that higher levels of aMAP score, RAR and PIV were independent risk factors for HCC in inpatients with chronic liver disease (P<0.05). The area under receiver operator characteristic (ROC) curve (AUC) of the nomogram risk prediction model constructed based on above factors was 0.823 (95%CI: 0.747-0.899). The calibration curve showed that the predicted value was basically consistent with the actual observed value, and the Brier score was 0.125. The decision curve showed that the model had a clear positive net benefit. The AUC of internal validation of the prediction model by Bootstrap method was 0.823 (95%CI: 0.820-0.825), indicating that the model had a good degree of differentiation.Conclusion The nomogram risk prediction model based on aMAP score, RAR and PIV showed a good predictive performance of HCC in patients with chronic liver disease, which could benefits the individualized treatment and follow-up.

Key words: carcinoma, hepatocellular, nomograms, ROC curve, aMAP score, chronic liver disease, RAR, PIV

中图分类号:

R735.7

图/表 7

参考文献 28

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组别		饮酒史		高血压		糖尿病
组别	n		年龄/岁		性别（男/女）		吸烟史
非HCC组	111		53.00（48.00，60.00）		71/40		19（17.12）
HCC组	32		57.50（51.25，65.00）		28/4		8（25.00）
Z或χ²			2.401^＊		6.459^＊		1.008
非HCC组		19（17.1）		18（16.22）		13（11.71）
HCC组		10（31.3）		2（6.25）		8（25.00）
χ²		3.069		1.306		2.521

组别		饮酒史		高血压		糖尿病
组别	n		年龄/岁		性别（男/女）		吸烟史
非HCC组	111		53.00（48.00，60.00）		71/40		19（17.12）
HCC组	32		57.50（51.25，65.00）		28/4		8（25.00）
Z或χ²			2.401^＊		6.459^＊		1.008
非HCC组		19（17.1）		18（16.22）		13（11.71）
HCC组		10（31.3）		2（6.25）		8（25.00）
χ²		3.069		1.306		2.521

组别		RDW/%			NEU/ （×10⁹/L）			LYM/ （×10⁹/L）			MON/ （×10⁹/L）
组别			n	TBIL/（μmol/L）			ALB/（g/L）			PLT/（×10⁹/L）
非HCC组			111	16.10（12.00，23.30）			36.72±6.11			144.03±77.77
HCC组			32	24.40（15.95，43.00）			30.66±5.80			137.31±60.36
Z或t				3.587^＊＊			5.002^＊＊			0.450
非HCC组		13.3（12.8，16.0）			2.6（1.7，3.6）			1.5±0.8			0.3（0.2，0.5）
HCC组		15.1（13.8，17.9）			3.5（2.5，6.6）			1.0±0.5			0.4（0.3，0.7）
Z或t		3.450^＊＊			3.284^＊＊			4.073^＊＊			2.919^＊＊
组别	aMAP评分/分					RAR			PIV
非HCC组	59.0（52.0，66.0）					0.4（0.3，0.5）			95.0（38.8，181.9）
HCC组	64.5（61.0，68.0）					0.5（0.4，0.6）			190.6（127.5，598.8）
Z	3.362^＊＊					4.400^＊＊			4.282^＊＊

组别		RDW/%			NEU/ （×10⁹/L）			LYM/ （×10⁹/L）			MON/ （×10⁹/L）
组别			n	TBIL/（μmol/L）			ALB/（g/L）			PLT/（×10⁹/L）
非HCC组			111	16.10（12.00，23.30）			36.72±6.11			144.03±77.77
HCC组			32	24.40（15.95，43.00）			30.66±5.80			137.31±60.36
Z或t				3.587^＊＊			5.002^＊＊			0.450
非HCC组		13.3（12.8，16.0）			2.6（1.7，3.6）			1.5±0.8			0.3（0.2，0.5）
HCC组		15.1（13.8，17.9）			3.5（2.5，6.6）			1.0±0.5			0.4（0.3，0.7）
Z或t		3.450^＊＊			3.284^＊＊			4.073^＊＊			2.919^＊＊
组别	aMAP评分/分					RAR			PIV
非HCC组	59.0（52.0，66.0）					0.4（0.3，0.5）			95.0（38.8，181.9）
HCC组	64.5（61.0，68.0）					0.5（0.4，0.6）			190.6（127.5，598.8）
Z	3.362^＊＊					4.400^＊＊			4.282^＊＊

因素	β	SE	Wald χ²	P	OR	OR 95%CI
aMAP评分	0.094	0.040	5.594	0.018	1.098	1.016~1.187
RAR	3.419	1.741	3.857	0.049	30.545	1.007~926.364
PIV	0.003	0.001	7.376	0.007	1.003	1.001~1.005
常数项	-9.363	2.386	15.399	<0.001	0.000

aMAP评分联合RAR及PIV构建慢性肝病患者肝细胞癌发生风险的预测模型

Constructing a risk prediction model for hepatocellular carcinoma in patients with chronic liver disease based on aMAP score combined with RAR and PIV

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变量	AUC	AUC 95% CI	截断值	敏感度/%	特异度/%	约登指数
aMAP评分	0.695	0.602~0.789	60.50分	78.13	45.05	0.331
RAR	0.756	0.666~0.845	0.34	96.88	45.95	0.428
PIV	0.749	0.651~0.847	121.43	78.13	62.16	0.403
预测模型	0.823	0.747~0.899	-	93.75	54.05	0.478

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