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用于预测接受新辅助治疗的直肠癌患者生存率的列线图和风险评分模型。

Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy.

作者信息

Wei Fang-Ze, Mei Shi-Wen, Chen Jia-Nan, Wang Zhi-Jie, Shen Hai-Yu, Li Juan, Zhao Fu-Qiang, Liu Zheng, Liu Qian

机构信息

Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union College, Beijing 100021, China.

出版信息

World J Gastroenterol. 2020 Nov 14;26(42):6638-6657. doi: 10.3748/wjg.v26.i42.6638.

Abstract

BACKGROUND

Colorectal cancer is a common digestive cancer worldwide. As a comprehensive treatment for locally advanced rectal cancer (LARC), neoadjuvant therapy (NT) has been increasingly used as the standard treatment for clinical stage II/III rectal cancer. However, few patients achieve a complete pathological response, and most patients require surgical resection and adjuvant therapy. Therefore, identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance.

AIM

To establish effective prognostic nomograms and risk score prediction models to predict overall survival (OS) and disease-free survival (DFS) for LARC treated with NT.

METHODS

Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017. The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors, which were validated by the Cox regression method. Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves, and that of the two nomograms was conducted by calculating the concordance index (C-index) and calibration curves. The results were validated in a cohort of 65 patients from 2015 to 2017.

RESULTS

Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model: Vascular_tumors_bolt, cancer nodules, yN, body mass index, matchmouth distance from the edge, nerve aggression and postoperative carcinoembryonic antigen. The nomogram showed good predictive value for OS, with a C-index of 0.91 (95%CI: 0.85, 0.97) and good calibration. In the validation cohort, the C-index was 0.69 (95%CI: 0.53, 0.84). The risk factor prediction model showed good predictive value. The areas under the curve for 3- and 5-year survival were 0.811 and 0.782. The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77 (95%CI: 0.69, 0.85). In the validation cohort, the C-index was 0.71 (95%CI: 0.61, 0.81). The prediction model for DFS also had good predictive value, with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754.

CONCLUSION

We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT.

摘要

背景

结直肠癌是全球常见的消化道癌症。作为局部晚期直肠癌(LARC)的综合治疗方法,新辅助治疗(NT)已越来越多地被用作临床II/III期直肠癌的标准治疗方法。然而,很少有患者能达到完全病理缓解,大多数患者需要手术切除和辅助治疗。因此,识别危险因素并建立准确的模型来预测LARC患者的预后具有重要的临床意义。

目的

建立有效的预后列线图和风险评分预测模型,以预测接受NT治疗的LARC患者的总生存期(OS)和无病生存期(DFS)。

方法

列线图和危险因素评分预测模型基于2015年至2017年在癌症医院接受NT治疗的患者。采用最小绝对收缩和选择算子回归模型筛选预后危险因素,并通过Cox回归方法进行验证。使用受试者工作特征曲线评估两种预测模型的性能,通过计算一致性指数(C指数)和校准曲线评估两种列线图的性能。结果在2015年至2017年的65例患者队列中进行了验证。

结果

七个特征与OS显著相关,并被纳入OS预测列线图和预测模型:血管肿瘤栓子、癌结节、yN、体重指数、距边缘的吻合口距离、神经侵犯和术后癌胚抗原。该列线图对OS显示出良好的预测价值,C指数为0.91(95%CI:0.85,0.97),校准良好。在验证队列中,C指数为0.69(95%CI:0.53,0.84)。危险因素预测模型显示出良好的预测价值。3年和5年生存率的曲线下面积分别为0.811和0.782。预测DFS的列线图包括ypTNM和神经侵犯,显示出良好的校准,C指数为0.77(95%CI:0.69,0.85)。在验证队列中,C指数为0.71(95%CI:0.61,0.81)。DFS预测模型也具有良好的预测价值,3年生存率的AUC为0.784,5年生存率的AUC为0.754。

结论

我们建立了准确的列线图和预测模型,用于预测接受NT治疗后的LARC患者的OS和DFS。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f74/7673964/d2af68e65be5/WJG-26-6638-g001.jpg

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