Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China (mainland).
Ningbo Fourth Hospital, Ningbo, Zhejiang, China (mainland).
Med Sci Monit. 2019 May 18;25:3683-3691. doi: 10.12659/MSM.913533.
BACKGROUND The primary objective of this study was to assess the cumulative incidence of cause-specific mortality (CSM) and other causes of mortality (OCM) for patients with metastatic pancreatic duct adenocarcinoma (mPDAC). The secondary objective was to calculate the probability of CSM and build a competing risk nomogram to predict CSM for mPDAC. MATERIAL AND METHODS We identified patients with mPDAC between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. We assessed the cumulative incidence function (CIF) for cause-specific mortality and other causes of mortality. We used Gray's test to investigate the differences. The Fine and Gray proportional subdistribution hazard model was applied to model CIF. And a competing risk nomogram was built to predict the probability of CSM for mPDAC. RESULTS There were 10 527 eligible patients diagnosed with mPDAC from 2010 to 2015 who were included in our formal analysis. The 6-month cumulative incidence of CSM was 60.3% and 5.9% for other causes. Predictors of SCM for mPDAC included surgery, age, tumor size, chemotherapy, radiation therapy, bone metastasis, and liver metastasis. The nomogram was proven to be well calibrated, and had good model discriminative ability. CONCLUSIONS We assessed the CIF of CSM and competing risk mortality in patients with mPDAC using the SEER database. The Fine and Gray proportional subdistribution hazard model performance was good, with a concordance index of 0.74, and the competing-risks nomogram was built, which can be a helpful predictive tool for cases with mPDAC. However, a validation sample data set and further verification are still needed to assess a profile for prognostic use in a prospective study.
本研究的主要目的是评估转移性胰腺导管腺癌(mPDAC)患者的特定原因死亡率(CSM)和其他死亡原因的累积发生率(OCM)。次要目的是计算 CSM 的概率并构建竞争风险列线图以预测 mPDAC 的 CSM。
我们从监测、流行病学和最终结果(SEER)数据库中确定了 2010 年至 2015 年间患有 mPDAC 的患者。我们评估了特定原因死亡率和其他死亡原因的累积发生率函数(CIF)。我们使用 Gray 检验来研究差异。Fine 和 Gray 比例亚分布风险模型用于对 CIF 进行建模。并且构建了竞争风险列线图以预测 mPDAC 的 CSM 概率。
我们对 2010 年至 2015 年间符合条件的 10527 例 mPDAC 患者进行了正式分析。6 个月时 CSM 的累积发生率为 60.3%,其他原因的累积发生率为 5.9%。mPDAC 的 SCM 的预测因素包括手术、年龄、肿瘤大小、化疗、放疗、骨转移和肝转移。列线图证明具有良好的校准度和良好的模型判别能力。
我们使用 SEER 数据库评估了 mPDAC 患者的 CSM 和竞争风险死亡率的 CIF。Fine 和 Gray 比例亚分布风险模型的性能良好,一致性指数为 0.74,构建了竞争风险列线图,可作为 mPDAC 患者的有用预测工具。但是,仍然需要验证样本数据集和进一步验证,以在前瞻性研究中评估预后使用的概况。