Department of Surgical Oncological and Gastrointestinal Sciences, University of Padova, Padova, Italy.
Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Eur J Surg Oncol. 2022 May;48(5):1025-1032. doi: 10.1016/j.ejso.2021.11.127. Epub 2021 Dec 6.
Accurate estimation of survival and recurrence are important to inform decisions regarding therapy and surveillance. We sought to design and validate a dynamic prognostic model for patients undergoing resection for gastric adenocarcinoma.
Patients who underwent curative-intent surgery for gastric adenocarcinoma between 2000 and 2020 were identified using a multi-institutional database. Landmark analysis was used to create dynamic OS and DFS prediction models. Model performance was internally cross-validated via bootstrap resampling.
Among 895 patients, 507 (57.2%) patients underwent partial gastrectomy (n = 507, 57.2%) while 380 (42.8%) had total gastrectomy. Median tumor size was 40 mm (IQR: 25-65), most tumors were located in the antrum (n = 344, 39.5%) and infiltrated the subserosa (T3 tumors: n = 283, 31.9%) or serosa (T4 tumors: n = 253, 28.5%); lymph node metastasis occurred in 528 (59.1%) patients. Median OS and DFS were 17.5 (IQR: 7.5-42.8) and 14.3 months (IQR: 6.5-39.9), respectively. The impact of age, sex, preoperative comorbidities, tumor size and location, extent of lymphadenectomy and total number of lymph nodes examined, Lauren class, T and N category, postoperative complications, and tumor recurrence varied over time (all p < 0.05). An online tool to predict dynamic OS and DFS based on patient survival relative to time survived was developed and made available for clinical use. Discrimination ability of OS and DFS was excellent (C-index: 0.84 and 0.86, respectively) and calibration plots revealed good prediction.
An online dynamic prognostic tool was developed and validated to predict OS and DFS following resection of gastric adenocarcinoma. Landmark analysis to predict long-term outcomes based on follow-up time may be helpful to surgeons and patients.
准确估计生存和复发对于指导治疗和监测决策非常重要。我们旨在设计并验证一种用于接受胃腺癌切除术患者的动态预后模型。
使用多机构数据库确定 2000 年至 2020 年间接受根治性手术的胃腺癌患者。使用里程碑分析创建动态 OS 和 DFS 预测模型。通过自举重采样对内部分叉验证。
在 895 例患者中，507 例（57.2%）接受了部分胃切除术（n=507，57.2%），380 例（42.8%）接受了全胃切除术。中位肿瘤大小为 40mm（IQR：25-65），大多数肿瘤位于胃窦（n=344，39.5%），浸润浆膜下层（T3 肿瘤：n=283，31.9%）或浆膜（T4 肿瘤：n=253，28.5%）；528 例（59.1%）患者发生淋巴结转移。中位 OS 和 DFS 分别为 17.5（IQR：7.5-42.8）和 14.3 个月（IQR：6.5-39.9）。年龄、性别、术前合并症、肿瘤大小和位置、淋巴结清扫程度和检查的总淋巴结数、Lauren 分级、T 和 N 分类、术后并发症和肿瘤复发的影响随时间而变化（均 p<0.05）。开发了一种基于患者生存相对于生存时间的动态 OS 和 DFS 预测的在线工具，并可用于临床使用。OS 和 DFS 的区分能力非常出色（C 指数：0.84 和 0.86），校准图显示了良好的预测。
开发并验证了一种用于预测胃腺癌切除术后 OS 和 DFS 的在线动态预后工具。基于随访时间预测长期结果的里程碑分析可能对外科医生和患者有帮助。
