Department of Gastrointestinal Surgery, Affiliated Hospital of Nantong University, Chongchuan District, No. 20 Xisi Road, Nantong, 226000, China.
Medical School, Nantong University, Nantong, Jiangsu Province, China.
Int J Colorectal Dis. 2024 Apr 1;39(1):44. doi: 10.1007/s00384-024-04622-x.
Considering the poor prognosis and high lymph node (LN) involvement rate of colorectal signet ring cell carcinoma (SRCC), this study aimed to construct a prognostic nomogram to predict overall survival (OS) with satisfactory accuracy and utility, based on LN status indicators with superior predictability.
Using the Surveillance, Epidemiology, and End Results (SEER) database, we obtained cases of colorectal SRCC patients and employed univariate and multivariate Cox analyses to determine independent prognostic factors. Kaplan-Meier curves were utilized to visualize survival differences among these factors. Receiver operating characteristic curves were generated to assess predictive performances of models incorporating various LN status indicators. A novel nomogram, containing optimal LN status indicators and other prognostic factors, was developed to predict OS, whose discriminatory ability and accuracy were evaluated using calibration curves and decision curve analysis.
A total of 1663 SRCC patients were screened from SEER database. Older patients and those with grades III-IV, tumor sizes > 39 mm, T3/T4 stage, N1/N2 stage, M1 stage, and higher log odds of positive lymph nodes (LODDS) values exhibited poorer prognoses. Age, grade, tumor size, TNM stage, and LODDS were independent prognostic factors. The model containing N stage and LODDS outperformed the one relying solely on N stage as LN status indicator, resulting in a validated nomogram for accurately predicting OS in SRCC patients.
The integration of LODDS, N stage, and other risk factors into a nomogram offered precise OS predictions, enhancing therapeutic decision-making and tailored follow-up management for colorectal SRCC patients.
鉴于结直肠印戒细胞癌(SRCC)预后差且淋巴结(LN)受累率高,本研究旨在构建一个预后列线图,基于预测能力较强的 LN 状态指标,以获得具有满意准确性和实用性的总生存期(OS)预测。
利用监测、流行病学和最终结果(SEER)数据库,我们获得了结直肠 SRCC 患者的病例,并采用单因素和多因素 Cox 分析确定独立的预后因素。Kaplan-Meier 曲线用于可视化这些因素之间的生存差异。生成受试者工作特征曲线来评估纳入各种 LN 状态指标的模型的预测性能。建立了一个新的列线图,包含最佳的 LN 状态指标和其他预后因素,用于预测 OS,通过校准曲线和决策曲线分析评估其区分能力和准确性。
从 SEER 数据库中筛选出 1663 例 SRCC 患者。较年长的患者和那些分级为 III-IV 级、肿瘤大小>39mm、T3/T4 期、N1/N2 期、M1 期以及阳性淋巴结对数优势比(LODDS)值较高的患者预后较差。年龄、分级、肿瘤大小、TNM 分期和 LODDS 是独立的预后因素。包含 N 分期和 LODDS 的模型优于仅依赖 N 分期作为 LN 状态指标的模型,为 SRCC 患者准确预测 OS 提供了验证后的列线图。
将 LODDS、N 分期和其他危险因素纳入列线图,可以提供精确的 OS 预测,增强了结直肠 SRCC 患者的治疗决策和个体化随访管理。