Department of Oral and Maxillofacial Surgery, Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, 510055 Guangdong, China.
Guangdong Provincial Key Laboratory of Stomatology, Guangzhou 510080 Guangdong, China.
Biomed Res Int. 2022 Aug 29;2022:7894523. doi: 10.1155/2022/7894523. eCollection 2022.
Salivary gland adenoid cystic carcinoma (SACC) is the second highest incidence of malignant salivary gland tumor. The purpose of this study was to establish nomograms combined with SACC patients based on the Surveillance, Epidemiology, and End Results (SEER) database.
Patients with SACC were included in the SEER∗Stat Database from 2004 to 2016. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to filter potential prognostic clinical variables. Multivariate analysis from the Cox proportional hazards model was performed to determine the independent prognostic factors on overall survival (OS) and disease-specific survival (DSS), applied to develop nomograms. The Schönfeld residual test verified the proportional hazard assumption. The discrimination and consistency of nomograms was assessed and validated according to concordance index (-index), receiver operating characteristic (ROC) curves, and calibration curves using an internal 1,000 times bootstrap resampling. The nomogram's net clinical benefit was assessed through decision curve analysis (DCA).
A total of 658 patients with SACC were included. Age, T stage, N stage, M stage, histologic grade, and surgery were independent prognostic factors for OS and DSS. Based on these independent prognostic factors, nomograms were developed to predict 3-, 5-, and 10-year OS and DSS. In the validation of 1,000 times bootstrap resampling, the -index and ROC curves had good discriminatory ability. The calibration curves indicated excellent consistency between the predicted and actual survival results in the nomograms. The DCA curves demonstrated that the nomograms had good clinical benefit and were superior to the TNM stage and other variables.
Two nomograms developed in this study precisely predicted the 3-, 5-, and 10-year OS and DSS rates of patients with SACC in accordance with independent prognostic factors, and their clinical value is better than TNM staging, providing a prognostic reference for other SACC patients.
涎腺腺样囊性癌（SACC）是第二大常见的恶性涎腺肿瘤。本研究旨在基于监测、流行病学和最终结果（SEER）数据库建立 SACC 患者的列线图。
纳入 2004 年至 2016 年 SEER∗Stat 数据库中的 SACC 患者。应用最小绝对收缩和选择算子（LASSO）Cox 回归分析筛选潜在的预后临床变量。采用 Cox 比例风险模型的多变量分析确定总生存（OS）和疾病特异性生存（DSS）的独立预后因素，用于建立列线图。Schönfeld 残差检验验证了比例风险假设。根据一致性指数（-指数）、接受者操作特征（ROC）曲线和内部 1000 次 bootstrap 重采样校准曲线评估和验证列线图的区分度和一致性。通过决策曲线分析（DCA）评估列线图的净临床获益。
共纳入 658 例 SACC 患者。年龄、T 分期、N 分期、M 分期、组织学分级和手术是 OS 和 DSS 的独立预后因素。基于这些独立的预后因素，建立了预测 3、5 和 10 年 OS 和 DSS 的列线图。在 1000 次 bootstrap 重采样验证中，-指数和 ROC 曲线具有良好的区分能力。校准曲线表明列线图预测与实际生存结果之间具有极好的一致性。DCA 曲线表明列线图具有良好的临床获益，优于 TNM 分期和其他变量。
本研究建立的两个列线图精确地预测了 SACC 患者的 3、5 和 10 年 OS 和 DSS 率，符合独立的预后因素，其临床价值优于 TNM 分期，为其他 SACC 患者提供了预后参考。
