列线图建立与验证用于预测 T1 期结直肠癌淋巴结转移风险
Nomogram Development and External Validation for Predicting the Risk of Lymph Node Metastasis in T1 Colorectal Cancer.
机构信息
Center for Colorectal Cancer, Research Institute and Hospital, National Cancer Center, Goyang, Korea.
Biometrics Research Branch, Research Institute and Hospital, National Cancer Center, Goyang, Korea.
出版信息
Cancer Res Treat. 2019 Oct;51(4):1275-1284. doi: 10.4143/crt.2018.569. Epub 2019 Jan 17.
PURPOSE
Predicting lymph node metastasis (LNM) risk is crucial in determining further treatment strategies following endoscopic resection of T1 colorectal cancer (CRC). This study aimed to establish a new prediction model for the risk of LNM in T1 CRC patients.
MATERIALS AND METHODS
The development set included 833 patients with T1 CRC who had undergone endoscopic (n=154) or surgical (n=679) resection at the National Cancer Center. The validation set included 722 T1 CRC patients who had undergone endoscopic (n=249) or surgical (n=473) resection at Daehang Hospital. A logistic regression model was used to construct the prediction model. To assess the performance of prediction model, discrimination was evaluated using the receiver operating characteristic (ROC) curves with area under the ROC curve (AUC), and calibration was assessed using the Hosmer-Lemeshow (HL) goodness-of-fit test.
RESULTS
Five independent risk factors were determined in the multivariable model, including vascular invasion, high-grade histology, submucosal invasion, budding, and background adenoma. In final prediction model, the performance of the model was good that the AUC was 0.812 (95% confidence interval [CI], 0.770 to 0.855) and the HL chi-squared test statistic was 1.266 (p=0.737). In external validation, the performance was still good that the AUC was 0.771 (95% CI, 0.708 to 0.834) and the p-value of the HL chi-squared test was 0.040. We constructed the nomogram with the final prediction model.
CONCLUSION
We presented an externally validated new prediction model for LNM risk in T1 CRC patients, guiding decision making in determining whether additional surgery is required after endoscopic resection of T1 CRC.
目的
预测 T1 结直肠癌(CRC)患者的淋巴结转移(LNM)风险对于确定内镜切除后的进一步治疗策略至关重要。本研究旨在建立一种新的 T1 CRC 患者 LNM 风险预测模型。
材料与方法
开发集纳入了 833 例在国家癌症中心接受内镜(n=154)或手术(n=679)切除的 T1 CRC 患者,验证集纳入了 722 例在大韩医院接受内镜(n=249)或手术(n=473)切除的 T1 CRC 患者。采用 logistic 回归模型构建预测模型。使用受试者工作特征(ROC)曲线评估预测模型的性能,曲线下面积(AUC)评估区分度,Hosmer-Lemeshow(HL)拟合优度检验评估校准度。
结果
多变量模型确定了 5 个独立的危险因素,包括血管侵犯、高级别组织学、黏膜下浸润、芽生和背景腺瘤。在最终预测模型中,模型性能良好,AUC 为 0.812(95%置信区间 [CI],0.770 至 0.855),HL χ 2 检验统计量为 1.266(p=0.737)。外部验证中,模型性能仍良好,AUC 为 0.771(95%CI,0.708 至 0.834),HL χ 2 检验的 p 值为 0.040。我们使用最终预测模型构建了列线图。
结论
我们提出了一种新的 T1 CRC 患者 LNM 风险的外部验证预测模型,为确定是否需要在 T1 CRC 内镜切除后进行额外手术提供决策依据。