Department of Surgery, Howard University College of Medicine, Washington, DC 20060, USA.
J Surg Res. 2010 Oct;163(2):264-9. doi: 10.1016/j.jss.2010.03.017. Epub 2010 Apr 1.
Much debate exists over the significance of the number of lymph nodes (LN) examined after colon resection.
The Surveillance, Epidemiology and End Results (SEER) database was queried for patients who presented with colonic adenocarcinoma. Multiple Cox proportional hazard regressions were run using successive LN cut-offs (6-26), first controlling for and then stratifying by T-stage. This was repeated in subsets of patients delineated by LN status. Additional variables controlled for in every regression were age, gender, ethnicity, marital status, number of positive LN, grade, metastases, and extent of surgery. After each regression, a Harrell's C statistic and an Akaike's information criterion (AIC) were performed to test the predictive capacity and fit of the model, respectively.
128,071 patients met selection criteria. The highest Harrell's C statistics among all patients were the cutoffs at 14 LN and 15 LN. Between those, the AIC shows that the cutoff at 15 LN fit the data more closely than the 14 LN cutoff. The models with the best predictive ability and best fit by T-stage were T1, 14 LN; T2, 10 LN; T3, 10 LN; T4, 12 LN.
Using a population-based dataset, we show the optimal number of LN examined is dependent upon the patient's tumor stage. Across all T-stages, the highest optimal number of LN resected was 15. Since it is possible to estimate but not perfectly predict the stage of a patient's tumor preoperatively, we believe the recommendation should be based on the most conservative measure.
在结肠切除术后检查的淋巴结数量的意义存在很大争议。
使用监测、流行病学和最终结果(SEER)数据库对患有结肠腺癌的患者进行了查询。使用连续的淋巴结截断值(6-26)进行了多次 Cox 比例风险回归,首先控制然后按 T 期分层。在按淋巴结状态划分的患者亚组中重复了此操作。在每个回归中控制的其他变量包括年龄、性别、种族、婚姻状况、阳性淋巴结数量、分级、转移和手术范围。在每次回归后,进行了 Harrell 的 C 统计量和 Akaike 的信息量准则(AIC)以分别测试模型的预测能力和拟合度。
符合选择标准的患者为 128071 名。所有患者中最高的 Harrell 的 C 统计量是 14 个淋巴结和 15 个淋巴结的截断值。在这些值之间,AIC 表明 15 个淋巴结截断值比 14 个淋巴结截断值更能准确地拟合数据。具有最佳预测能力和最佳 T 分期拟合的模型为 T1,14 个淋巴结;T2,10 个淋巴结;T3,10 个淋巴结;T4,12 个淋巴结。
使用基于人群的数据集,我们表明检查的最佳淋巴结数量取决于患者的肿瘤分期。在所有 T 分期中,切除的最佳淋巴结数量最高为 15 个。由于术前可以估计但不能完美预测患者肿瘤的分期,因此我们认为建议应基于最保守的措施。