Li Huiming, Liu Jun, Yan Shaoying, Rao Chunmei, Wang Ling
Department of Laboratory Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, People's Republic of China.
Department of Laboratory Medicine, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, 200438, People's Republic of China.
Cancer Manag Res. 2023 Jun 14;15:501-509. doi: 10.2147/CMAR.S408548. eCollection 2023.
Platelet distribution width (PDW) is a marker of platelet anisocytosis that increases with platelet activation. The clinical implications of PDW in HCC are not well-defined. This study aimed to determine whether PDW could predict recurrence in patients with HCC after resection.
Between January and December 2008, 471 patients with HCC were recruited retrospectively. The clinicopathological characteristics of patients with HCC were analyzed based on the relationship between the two PDW groups. Kaplan-Meier curves and multivariate Cox regression analyses were used to evaluate the relationship between PDW and disease-free survival (DFS). A novel nomogram was developed based on the identified independent risk factors. Its accuracy was evaluated using a calibration curve and concordance index. The predictive value was evaluated using a receiver operating characteristic (ROC) curve.
PDW was significantly associated with direct bilirubin, total bilirubin, urea, and prothrombin time. Patients with PDW ≥ 17.1 were a significantly shorter DFS than those with PDW < 17.1 (17.98% vs 49.83%, < 0.001). Multivariate analysis determined that alpha-fetoprotein (AFP), carcinoembryonic antigen, microvascular invasion (MVI), tumor size, and tumor number were the independent variables associated with DFS. Patients with PDW ≥ 17.1 had a hazard ratio of 1.381 (95% confidence interval: 1.069-1.783, = 0.014) for DFS. AFP, PDW, MVI, tumor size, and tumor number were identified as preoperative independent risk factors for DFS and used to establish the nomogram. Calibration curve analysis revealed that the standard curve fitted well with the predicted curve. ROC curve analysis demonstrated the high efficiency of the nomogram.
Increased PDW may predict recurrence-free survival in patients with HCC. Our nomogram model also performed well in predicting patient prognoses.
血小板分布宽度(PDW)是血小板异质性的一个指标,随血小板活化而增加。PDW在肝癌中的临床意义尚不明确。本研究旨在确定PDW是否可预测肝癌切除术后患者的复发情况。
回顾性纳入2008年1月至12月期间的471例肝癌患者。根据两个PDW组之间的关系分析肝癌患者的临床病理特征。采用Kaplan-Meier曲线和多因素Cox回归分析评估PDW与无病生存期(DFS)之间的关系。基于确定的独立危险因素绘制了一个新的列线图。使用校准曲线和一致性指数评估其准确性。使用受试者工作特征(ROC)曲线评估预测价值。
PDW与直接胆红素、总胆红素、尿素和凝血酶原时间显著相关。PDW≥17.1的患者DFS明显短于PDW<17.1的患者(17.98%对49.83%,<0.001)。多因素分析确定甲胎蛋白(AFP)、癌胚抗原、微血管侵犯(MVI)、肿瘤大小和肿瘤数量是与DFS相关的独立变量。PDW≥17.1的患者DFS的风险比为1.381(95%置信区间:1.069-1.783,=0.014)。AFP、PDW、MVI、肿瘤大小和肿瘤数量被确定为DFS的术前独立危险因素,并用于建立列线图。校准曲线分析显示标准曲线与预测曲线拟合良好。ROC曲线分析表明列线图具有较高的效率。
PDW升高可能预测肝癌患者的无复发生存期。我们的列线图模型在预测患者预后方面也表现良好。