Guo Xingren, Song Xiangyang, Long Xiaoyin, Liu Yahui, Xie Yixin, Xie Cheng, Ji Bai
The Department of General Surgery Center-Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Jilin University, Changchun, China.
Front Oncol. 2023 Jan 25;13:1053375. doi: 10.3389/fonc.2023.1053375. eCollection 2023.
Pancreatic cancer is one of the most malignant cancers worldwide, and it mostly occurs in the head of the pancreas. Existing laparoscopic pancreaticoduodenectomy (LPD) surgical techniques have has undergone a learning curve, a wide variety of approaches for the treatment of pancreatic cancer have been proposed, and the operation has matured. At present, pancreatic head cancer has been gradually changing from "surgeons' evaluation of anatomical resection" to "biologically inappropriate resection". In this study, the risk of lymph node metastasis in pancreatic head cancer was predicted using common preoperative clinical indicators.
The preoperative clinical data of 191 patients with pancreatic head cancer who received LPD in the First Affiliated Hospital of Jilin University from May 2016 to December 2021 were obtained. A univariate regression analysis study was conducted, and the indicators with a significance level of P<0.05 were included in the univariate logistic regression analysis into multivariate. Lastly, a nomogram was built based on age, tumor size, leucocyte,albumin(ALB), and lymphocytes/monocytes(LMR). The model with the highest resolution was selected by obtaining the area under a curve. The clinical net benefit of the prediction model was examined using decision curve analyses.Risk stratification was performed by combining preoperative CT scan with existing models.
Multivariate logistic regression analysis found age, tumor size, WBC, ALB, and LMR as five independent factors. A nomogram model was constructed based on the above indicators. The model was calibrated by validating the calibration curve within 1000 bootstrap resamples. The ROC curve achieved an AUC of 0.745(confidence interval of 95%: 0.673-0.816), thus indicating that the model had excellent discriminative skills. DCA suggested that the predictive model achieved a high net benefit in the nearly entire threshold probability range.
This study has been the first to investigate a nomogram for preoperative prediction of lymphatic metastasis in pancreatic head cancer. The result suggests that age, ALB, tumor size, WBC, and LMR are independent risk factors for lymph node metastasis in pancreatic head cancer. This study may provide a novel perspective for the selection of appropriate continuous treatment regimens, the increase of the survival rate of patients with pancreatic head cancer, and the selection of appropriate neoadjuvant therapy patients.
胰腺癌是全球最恶性的癌症之一,大多发生在胰头。现有的腹腔镜胰十二指肠切除术(LPD)手术技术经历了学习曲线,已提出多种治疗胰腺癌的方法,且该手术已成熟。目前,胰头癌已逐渐从“外科医生对解剖性切除的评估”转变为“生物学上不适当的切除”。在本研究中,使用常见的术前临床指标预测胰头癌淋巴结转移的风险。
获取2016年5月至2021年12月在吉林大学第一医院接受LPD的191例胰头癌患者的术前临床资料。进行单因素回归分析研究,将显著性水平P<0.05的指标纳入单因素逻辑回归分析以进行多因素分析。最后,基于年龄、肿瘤大小、白细胞、白蛋白(ALB)和淋巴细胞/单核细胞(LMR)构建列线图。通过获取曲线下面积选择分辨率最高的模型。使用决策曲线分析检查预测模型的临床净效益。通过将术前CT扫描与现有模型相结合进行风险分层。
多因素逻辑回归分析发现年龄、肿瘤大小、白细胞、ALB和LMR为五个独立因素。基于上述指标构建了列线图模型。通过在1000次自抽样重采样内验证校准曲线对模型进行校准。ROC曲线的AUC为0.745(95%置信区间:0.673 - 0.816),表明该模型具有出色的判别能力。DCA表明预测模型在几乎整个阈值概率范围内实现了高净效益。
本研究首次探讨了用于术前预测胰头癌淋巴转移的列线图。结果表明年龄、ALB、肿瘤大小、白细胞和LMR是胰头癌淋巴结转移的独立危险因素。本研究可能为选择合适的连续治疗方案、提高胰头癌患者生存率以及选择合适的新辅助治疗患者提供新的视角。