Weiser Martin R, Landmann Ron G, Kattan Michael W, Gonen Mithat, Shia Jinru, Chou Joanne, Paty Philip B, Guillem José G, Temple Larissa K, Schrag Deborah, Saltz Leonard B, Wong W Douglas
Department of Surgery, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10021, USA.
J Clin Oncol. 2008 Jan 20;26(3):380-5. doi: 10.1200/JCO.2007.14.1291.
Estimates of recurrence after curative colon cancer surgery are integral to patient care, forming the basis of cancer staging and treatment planning. The categoric staging system of the American Joint Committee on Cancer (AJCC) is commonly used to convey risk by grouping patients based on anatomic elements. Although easy to implement, there remains significant heterogeneity within each stage grouping. In the era of multimodality treatment, a more refined tool is needed to predict recurrence.
An institutional database of 1,320 patients with nonmetastatic colon cancer was used to develop a nomogram to estimate recurrence after curative surgery. Prognostic factors were assessed with multivariable analysis using Cox regression, whereas nonlinear continuous variables were modeled with cubic splines. The model was internally validated with bootstrapping, and performance was assessed by concordance index and a calibration curve.
The colon cancer recurrence nomogram predicted relapse with a concordance index of 0.77, improving on the stratification provided by either the AJCC fifth or sixth staging scheme. Factors in the model included patient age, tumor location, preoperative carcinoembryonic antigen, T stage, numbers of positive and negative lymph nodes, lymphovascular invasion, perineural invasion, and use of postoperative chemotherapy.
Using common clinicopathologic factors, the recurrence nomogram is better able to account for tumor and patient heterogeneity, thereby providing a more individualized outcome prognostication than that afforded by the AJCC categoric system. By identifying both the high- and low-risk patients within any particular stage, the nomogram is expected to aid in treatment planning and future trial design.
根治性结肠癌手术后复发的评估是患者护理的重要组成部分,是癌症分期和治疗计划的基础。美国癌症联合委员会(AJCC)的分类分期系统通常用于通过根据解剖学因素对患者进行分组来传达风险。尽管易于实施,但每个分期组内仍存在显著的异质性。在多模式治疗时代,需要一种更精细的工具来预测复发。
使用一个包含1320例非转移性结肠癌患者的机构数据库来开发一个列线图,以估计根治性手术后的复发情况。使用Cox回归进行多变量分析评估预后因素,而非线性连续变量则用三次样条进行建模。该模型通过自展法进行内部验证,并通过一致性指数和校准曲线评估性能。
结肠癌复发列线图预测复发的一致性指数为0.77,优于AJCC第五版或第六版分期方案提供的分层。模型中的因素包括患者年龄、肿瘤位置、术前癌胚抗原、T分期、阳性和阴性淋巴结数量、淋巴管侵犯、神经周围侵犯以及术后化疗的使用。
利用常见的临床病理因素,复发列线图能够更好地解释肿瘤和患者的异质性,从而提供比AJCC分类系统更个性化的预后预测。通过识别任何特定阶段内的高风险和低风险患者,列线图有望有助于治疗计划和未来试验设计。