甲状腺癌患者术后复发风险预测的列线图模型建立

目的 建立预测甲状腺癌患者术后复发风险的列线图模型.方法 回顾性分析2015年7月—2017年12月因甲状腺癌于沈阳医学院附属中心医院普外科行手术治疗的患者临床资料,筛选甲状腺癌术后复发的独立危险因素,基于筛选结果建立列线图预测模型,并对模型的预测准确性进行内外部验证.结果 Logistic回归分析结果显示,肿瘤大小≥...

Establishment of a nomogram model for predicting the risk of postoperative recurrence in patients with thyroid cancer

Objective The aim of this study was to establish a nomogram model for predicting the risk of recurrence in patients with thyroid cancer.Methods The clinical data of patients who underwent surgery for thyroid cancer in our hospital from July 2015 to December 2017 were retrospectively analyzed,independent risk factors for postoperative recurrence of thyroid cancer were screened,and a nomogram prediction model was established based on the screening results.The prediction accuracy of the model was verified internally and externally.Results Logistic regression analysis showed that tumor size≥4 cm(OR=2.741,95%CI:1.259~5.966),undifferentiated carcinoma(OR=4.974,95%CI:1.819~13.598),glandular infiltration(OR=2.624,95%CI:1.093~6.300),preoperative lymph node metastasis(OR=2.628,95%CI:1.165~5.928),stageⅢ~Ⅳthyroid cancer(OR=2.984,95%CI:1.329~6.698),unilateral glandular lobe plus isthmus resection(OR=2.797,95%CI:1.1403~6.861),and undissected lymph nodes(OR=2.553,95%CI:1.269~5.134)were independent risk factors for recurrence of thyroid cancer after surgery.A nomogram model was established based on the above independent risk factors.The model verification showed that the C-index of the modeling set and the validation set were 0.822 and 0.796,respectively;the calibration curves were close to the ideal curve,and the AUC was 0.816(95%CI:0.788~0.856)and 0.765(95%CI:0.731~0.802),indicating that the nomogram model had a good predicted accuracy.Conclusion There are many risk factors for postoperative recurrence in patients with thyroid cancer.The nomogram model constructed based on the risk factors in this article has a good predictive accuracy,which can provide reference for clinical staff to screen high-risk groups and formulate relevant prevention and treatment measures.