首页|基于临床指标和MRI征象构建的列线图对原发性肝癌中医证型的诊断效能

基于临床指标和MRI征象构建的列线图对原发性肝癌中医证型的诊断效能

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目的 探究临床指标联合MRI征象的列线图模型对原发性肝癌中医证型的判断效能.方法 回顾性收集2018年9月—2023年7月在陕西中医药大学附属医院住院的138例原发性肝癌患者临床资料,并分为实证组(n=84)和虚证组(n=54),所有患者均在治疗前行钆塞酸二钠增强MRI扫描.计数资料组间比较采用χ2检验或Fisher确切概率检验.计量资料两组间比较采用成组t检验.应用Logistic回归分析原发性肝癌中医证型的独立预测因子,并构建列线图模型,将所有患者按8∶2随机分为训练组(n=110)和验证组(n=28).通过校准曲线、受试者工作特征曲线(ROC曲线)和决策曲线评估模型的临床效能.结果 实证组与虚证组比较,中性粒细胞、淋巴细胞、血小板、白蛋白、中性粒细胞/淋巴细胞比值、凝血酶原时间、甲胎蛋白、直接胆红素、间接胆红素、总胆红素、有无门静脉侵犯、肿瘤个数、肝胆期肿瘤信号和表观扩散系数差异均有统计学意义(P值均<0.05).Logistic回归分析结果显示,甲胎蛋白(OR=0.003,95%CI:0.000~0.052,P<0.001)、凝血酶原时间(OR=0.032,95%CI:0.004~0.286,P=0.002)、淋巴细胞(OR=0.032,95%CI:0.004~0.268,P=0.002)、白蛋白(OR=0.009,95%CI:0.001~0.163,P=0.001)、中性粒细胞/淋巴细胞比值(OR=0.040,95%CI:0.003~0.457,P=0.010)、直接胆红素(OR=0.014,95%CI:0.001~0.198,P=0.002)、门静脉癌栓(OR=0.005,95%CI:0.000~0.115,P=0.001)、肿瘤个数(OR=12.740,95%CI:1.212~133.937,P=0.034)和表观扩散系数(OR=19.269,95%CI:3.163~117.387,P=0.001)是原发性肝癌中医证型分型的独立预测因子.训练组的ROC曲线下面积(AUC)、敏感度、特异度和准确度分别为0.962、84.1%、92.4%和89.1%,验证组的AUC、敏感度、特异度和准确度分别为0.848、63.6%、100.0%和85.7%.校准曲线显示列线图模型在训练组和验证组中的预测证型与实际证型之间有较好的一致性.决策曲线显示列线图在较大的阈值概率范围内有较好的净收益.结论 基于临床指标联合MRI征象的列线图模型在判断原发性肝癌中医证型方面具有良好的临床效能和价值.
Performance of a nomogram model established based on clinical indices and magnetic resonance imaging signs in the diagnosis of traditional Chinese medicine syndrome types of primary liver cancer
Objective To investigate the performance of a nomogram model established based on clinical indices and magnetic resonance imaging(MRI)signs in determining the traditional Chinese medicine(TCM)syndrome types of primary liver cancer.Methods A retrospective analysis was performed for the clinical data of 138 patients with primary liver cancer who were hospitalized in The Affiliated Hospital of Shaanxi University of Chinese Medicine from September 2018 to July 2023,and the patients were divided into excess syndrome group with 84 patients and deficiency syndrome group with 54 patients.All patients underwent Gd-EOB-DTPA contrast-enhanced MRI scan before treatment.The independent-samples t test was used for comparison of continuous data between two groups,and the chi-square or the Fisher's exact test was used for comparison of categorical data between groups.A Logistic regression analysis was used to investigate the independent predictive factors for the TCM syndrome type of primary liver cancer,and a nomogram model was established.The patients were randomly divided into training group with 110 patients and validation group with 28 patients at a ratio of 8∶2,and the calibration curve,the receiver operating characteristic(ROC)curve,and the decision curve were used to evaluate the clinical performance of this model.Results There were significant differences between the excess syndrome group and the deficiency syndrome group in neutrophils,lymphocyte count(LYM),platelet count,albumin(Alb),neutrophil-lymphocyte ratio(NLR),prothrombin time(PT),alpha-fetoprotein(AFP),direct bilirubin(DBil),indirect bilirubin,total bilirubin,presence or absence of portal vein invasion,number of tumors,hepatobiliary tumor signal,and apparent diffusion coefficient(ADC)(all P<0.05).The Logistic regression analysis showed that AFP(odds ratio[OR]=0.003,95%confidence interval[CI]:0.000—0.052,P<0.001),PT(OR=0.032,95%CI:0.004—0.286,P=0.002),LYM(OR=0.032,95%CI:0.004—0.286,P=0.002),Alb(OR=0.009,95%CI:0.001—0.163,P=0.001),NLR(OR=0.040,95%CI:0.003—0.457,P=0.010),DBil(OR=0.014,95%CI:0.001—0.198,P=0.002),portal vein cancer thrombus(OR=0.005,95%CI:0.000—0.115,P=0.001),number of tumors(OR=12.740,95%CI:1.212—133.937,P=0.034),and ADC(OR=19.269,95%CI:3.163—117.387,P=0.001)were independent predictive factors for TCM syndrome types of primary liver cancer.In the training group,the model had an area under the ROC curve(AUC)of 0.962,a sensitivity of 84.1%,a specificity of 92.4%,and an accuracy of 89.1%,and in the validation group,the model had an AUC of 0.848,a sensitivity of 63.6%,a specificity of 100.0%,and an accuracy of 85.7%.The calibration curve showed that the nomogram model had good consistency between predicted syndrome types and actual syndrome types in the training group and the validation group,and the decision curve showed that the nomogram model had good net benefits within a relatively wide range of threshold probability.Conclusion The nomogram model based on clinical indices and MRI signs has good clinical efficacy and value in judging the TCM syndrome type of primary liver cancer.

Liver NeoplasmsSyndrome Differentiation ClassificationMagnetic Resonance ImagingNomograms

王莹、张喜荣

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陕西中医药大学医学技术学院,陕西咸阳 712000

肝肿瘤 辨证分型 磁共振成像 列线图

陕西省卫生健康科研基金项目陕西省重点产业创新链项目

2022D0472021ZDLSF04-10

2024

临床肝胆病杂志
吉林大学

临床肝胆病杂志

CSTPCD北大核心
影响因子:1.428
ISSN:1001-5256
年,卷(期):2024.40(7)