BACKGROUND/AIMS Pancreatic ductal adenocarcinoma (PDAC) is associated with high mortality, even after surgical resection. The existing predictive models for survival have limitations. This study aimed to develop better nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in PDAC patients after surgery. METHODS A total of 6323 PDAC patients were retrospectively recruited from the Surveillance, Epidemiology, and End Results (SEER) database and randomly allocated into training, validation, and test cohorts. Multivariate Cox regression analysis was conducted to identify significant independent factors for OS and CSS, which were used for construction of nomograms. The performance was evaluated, validated, and compared with that of the 8th edition AJCC staging system. RESULTS Ten independent factors were significantly correlated with OS and CSS. The 1-, 3-, and 5-year OS rates were 40%, 20%, and 15%, and 1-, 3-, and 5-year CSS rates were 45%, 24%, and 19%, respectively. The nomograms were calibrated well, with c-indexes of 0.640 for OS and 0.643 for CSS, respectively. Notably, relative to the 8th edition AJCC staging system, the nomograms were able to stratify each AJCC stage into three prognostic subgroups for more robust risk stratification. Furthermore, the nomograms achieved significant clinical validity, exhibiting wide threshold probabilities and high net benefit. Performance assessment also showed high predictive accuracy and reliability. CONCLUSIONS The predictive ability and reliability of the established nomograms have been validated, and therefore, these nomograms hold potential as novel approaches to predicting survival and assessing survival risks for PDAC patients after surgery.

中文翻译：

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用于预测胰腺导管腺癌手术切除后患者存活率的新型列线图的开发和验证。

背景/目的 胰腺导管腺癌 (PDAC) 与高死亡率相关，即使在手术切除后也是如此。现有的生存预测模型存在局限性。本研究旨在开发更好的列线图来预测 PDAC 患者术后总生存率 (OS) 和癌症特异性生存率 (CSS)。方法 总共 6323 名 PDAC 患者从监测、流行病学和最终结果 (SEER) 数据库中回顾性招募，并随机分配到训练、验证和测试队列中。进行多变量 Cox 回归分析以确定 OS 和 CSS 的显着独立因素，用于构建列线图。对性能进行了评估、验证，并与第 8 版 AJCC 分期系统的性能进行了比较。结果 10 个独立因素与 OS 和 CSS 显着相关。1年、3年和5年OS率分别为40%、20%和15%，1年、3年和5年CSS率分别为45%、24%和19%。列线图校准良好，OS 的 c 指数分别为 0.640，CSS 的 c 指数为 0.643。值得注意的是，相对于第 8 版 AJCC 分期系统，列线图能够将每个 AJCC 分期分为三个预后亚组，以便进行更稳健的风险分层。此外，列线图实现了显着的临床有效性，表现出广泛的阈值概率和高净收益。性能评估还显示出很高的预测准确性和可靠性。结论 已建立列线图的预测能力和可靠性已得到验证，因此，