Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China.
Institute of Hepatobiliary Surgery of Chinese PLA, Beijing, China.
BMC Cancer. 2021 May 8;21(1):524. doi: 10.1186/s12885-021-08250-4.
Pancreatic head adenocarcinoma (PHAC), a malignant tumour, has a very poor prognosis, and the existing prognostic tools lack good predictive power. This study aimed to develop a better nomogram to predict overall survival after resection of non-metastatic PHAC.
Patients with non-metastatic PHAC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and divided randomly into training and validation cohorts at a ratio of 7:3. Cox regression analysis was used to screen prognostic factors and construct the nomogram. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the performance of the model. The predictive accuracy and clinical benefits of the nomogram were validated using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA).
From 2010 to 2016, 6419 patients with non-metastatic PHAC who underwent surgery were collected from the SEER database. A model including T stage, N stage, grade, radiotherapy, and chemotherapy was constructed. The concordance index of the nomogram was 0.676, and the AUCs of the model assessing survival at multiple timepoints within 60 months were significantly higher than those of the American Joint Committee on Cancer (AJCC) 8th staging system in the training cohort. Calibration curves showed that the nomogram had ability to predict the actual survival. The NRI, IDI, and DCA curves also indicated that our nomogram had higher predictive capability and clinical utility than the AJCC staging system.
Our nomogram has an ability to predict overall survival after resection of non-metastatic PHAC and includes prognostic factors that are easy to obtain in clinical practice. It would help assist clinicians to conduct personalized medicine.
胰腺头部腺癌(PHAC)是一种恶性肿瘤,预后极差,现有的预后工具预测能力不佳。本研究旨在开发一种更好的列线图来预测非转移性 PHAC 切除后的总生存期。
从监测、流行病学和最终结果(SEER)数据库中收集非转移性 PHAC 患者,并按 7:3 的比例随机分为训练和验证队列。使用 Cox 回归分析筛选预后因素并构建列线图。计算净重新分类改善(NRI)和综合判别改善(IDI)以评估模型的性能。使用曲线下面积(AUC)、校准曲线和决策曲线分析(DCA)验证列线图的预测准确性和临床获益。
2010 年至 2016 年,从 SEER 数据库中收集了 6419 例接受手术治疗的非转移性 PHAC 患者。构建了一个包含 T 分期、N 分期、分级、放疗和化疗的模型。该列线图的一致性指数为 0.676,在训练队列中,该模型评估 60 个月内多个时间点的生存情况的 AUC 明显高于美国癌症联合委员会(AJCC)第 8 分期系统。校准曲线表明该列线图具有预测实际生存的能力。NRI、IDI 和 DCA 曲线也表明,我们的列线图比 AJCC 分期系统具有更高的预测能力和临床应用价值。
我们的列线图能够预测非转移性 PHAC 切除后的总生存期,并且包含在临床实践中易于获得的预后因素。它将有助于协助临床医生进行个性化治疗。