Liu Guanghua, Long Jiangwen, Liu Chaoshui, Chen Jie
Department of Blood Transfusion, Laboratory of Hematology, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University) Changsha 410002, Hunan, China.
Hunan Provincial Key Laboratory of The Research and Development of Novel Pharmaceutical Preparations, The "Double-First Class" Application Characteristic Discipline of Hunan Province (Pharmaceutical Science), Changsha Medical University Changsha 410219, Hunan, China.
Am J Transl Res. 2024 Dec 15;16(12):7511-7520. doi: 10.62347/PLQF5135. eCollection 2024.
To develop a nomogram to predict the risk of portal vein tumor thrombosis (PVTT) in hepatocellular carcinoma (HCC) patients.
Patients diagnosed with HCC at Hunan Provincial People's Hospital between January 2010 and January 2022 were enrolled. Data on demographic characteristics, comorbidities, and laboratory tests were collected. Multivariate logistic regression was used to identify independent risk factors for PVTT, which were then incorporated into a predictive nomogram. The nomogram's discriminative ability was evaluated using the area under the receiver operating characteristic (AUC) curve. Clinical utility was assessed through decision curve analysis (DCA).
Being male (OR 1.991, 95% CI 1.314-3.017, P = 0.001), Barcelona Clinic Liver Cancer (BCLC) staging (stage C: OR 8.043, 95% CI 4.334-14.926, P<0.001; stage D: OR 7.977, 95% CI 3.532-18.017, P<0.001), tumor size >5 cm (OR 1.792, 95% CI 1.116-2.876, P = 0.016), and D-dimer (OR 1.126, 95% CI 1.083-1.171, P<0.001) were identified as independent risk factors for PVTT. The nomogram formula is: Logit = -2.8961 + 0.6586 (male) + BCLC staging (-0.1922 for B, 1.9251 for C, or 1.7938 for D) + 0.5418 (tumor size >5 cm) + 0.1051 DDi. The nomogram achieved an AUC of 0.798 (95% CI 0.774-0.822) in the training set and 0.822 (95% CI 0.782-0.862) in the validation set. Sensitivities were 86.6% and 90.7%, while specificies were 68.2% and 71.8% in the training and validation sets, respectively, demonstrating strong discrimination and predictive accuracy. DCA indicated a favorable risk threshold probability.
A nomogram incorporating male sex, BCLC staging, tumor size, and D-dimer demonstrated good predictive performance for PVTT. This tool may aid in the early comprehensive assessment of PVTT risk in HCC patients.
构建一种列线图以预测肝细胞癌(HCC)患者门静脉肿瘤血栓形成(PVTT)的风险。
纳入2010年1月至2022年1月在湖南省人民医院诊断为HCC的患者。收集人口统计学特征、合并症和实验室检查数据。采用多因素逻辑回归确定PVTT的独立危险因素,然后将其纳入预测列线图。使用受试者操作特征(AUC)曲线下面积评估列线图的鉴别能力。通过决策曲线分析(DCA)评估临床实用性。
男性(OR 1.991,95%CI 1.314 - 3.017,P = 0.001)、巴塞罗那临床肝癌(BCLC)分期(C期:OR 8.043,95%CI 4.334 - 14.926,P<0.001;D期:OR 7.977,95%CI 3.532 - 18.017,P<0.001)、肿瘤大小>5 cm(OR 1.792,95%CI 1.116 - 2.876,P = 0.016)和D - 二聚体(OR 1.126,95%CI 1.083 - 1.171,P<0.001)被确定为PVTT的独立危险因素。列线图公式为:Logit = -2.8961 + 0.6586(男性)+ BCLC分期(B期为 - 0.1922,C期为1.9251,D期为1.7938)+ 0.5418(肿瘤大小>5 cm)+ 0.1051 D - 二聚体。列线图在训练集中的AUC为0.798(95%CI 为0.774 - 0.8那么2),在验证集中为0.822(95%CI 为0.782 - 0.862)。训练集和验证集的敏感性分别为86.6%和90.7%,特异性分别为68.2%和71.8%,显示出较强的鉴别能力和预测准确性。DCA表明风险阈值概率良好。
纳入男性、BCLC分期、肿瘤大小和D - 二聚体的列线图对PVTT具有良好的预测性能。该工具可能有助于对HCC患者PVTT风险进行早期综合评估。