Department of Epidemiology and Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Department of Gastroenterology, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huai'an, China.
Cancer Med. 2020 Aug;9(15):5490-5499. doi: 10.1002/cam4.3215. Epub 2020 Jun 15.
Most patients with gastric cancer (GC) are first diagnosed at stage III-IV and surgery resection remains the primary therapeutic modality for these patients. However, clinical staging used for prediction of those patients provides limited information. We collected clinicopathological data and disease-progression information from 508 patients with stage III-IV GC at three Chinese hospitals and 1298 patients from the Surveillance, Epidemiology, and End Results database. Based on the stepwise multivariate regression model, we constructed a novel nomogram to predict overall survival (OS). The performance of discrimination for this model was measured using Harrell's concordance index (C-index) and receiver-operating characteristic curve (ROC), and was validated using calibration plots. Multivariate Cox regression analyses showed that tumor size, age at diagnosis, N stage, tumor grade, and distant metastases were outstanding independent prognostic factors of stage III-IV GC. We developed a nomogram based on these five prognostic predictors. In the training set, the C-index of the nomogram was 0.645 (95% CI: 0.611-0.679), which was higher than that of the American Joint Committee on Cancer TNM system alone (sixth TNM: 0.544; seventh TNM: 0.575; eighth TNM: 0.568). Similar results were observed in validation cohort. Moreover, calibration blots demonstrated good consistency between the actual and predicted OS probabilities. According to the nomogram, GC individuals could be classified into three groups (low-, middle-, and high-risk) (P < .001). Our nomogram complements the current staging system for prediction of individual prognosis with stage III-IV GC, and may be helpful for making individualized treatment decisions.
大多数胃癌（GC）患者在 III-IV 期被首次诊断，手术切除仍然是这些患者的主要治疗方式。然而，用于预测这些患者的临床分期提供的信息有限。我们从三家中国医院的 508 名 III-IV 期 GC 患者和 Surveillance, Epidemiology, and End Results 数据库中收集了临床病理数据和疾病进展信息。基于逐步多变量回归模型，我们构建了一个新的列线图来预测总生存期（OS）。该模型的判别性能通过 Harrell 一致性指数（C-index）和接受者操作特征曲线（ROC）进行测量，并通过校准图进行验证。多变量 Cox 回归分析表明，肿瘤大小、诊断时年龄、N 分期、肿瘤分级和远处转移是 III-IV 期 GC 的显著独立预后因素。我们基于这五个预后预测因子开发了一个列线图。在训练集中，该列线图的 C-index 为 0.645（95%CI：0.611-0.679），高于美国癌症联合委员会 TNM 系统（第六版 TNM：0.544；第七版 TNM：0.575；第八版 TNM：0.568）。在验证队列中也观察到了类似的结果。此外，校准图表明实际和预测的 OS 概率之间具有良好的一致性。根据列线图，GC 个体可分为三组（低危、中危和高危）（P<.001）。我们的列线图补充了目前用于预测 III-IV 期 GC 个体预后的分期系统，可能有助于制定个体化治疗决策。
