A Nomogram Predicting the Prognosis of Renal Cell Carcinoma Patients with Lung Metastases.
A Nomogram Predicting the Prognosis of Renal Cell Carcinoma Patients with Lung Metastases.
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DOI：
10.1155/2021/6627562
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发表时间：
2021
影响因子：
--
通讯作者：
Cao H
中科院分区：
文献类型：
--
作者：
Sheng X;Lu X;Wu J;Chen L;Cao H
预测肾细胞癌(RCC)肺转移患者生存的最佳工具仍然存在争议。我们从监测、流行病学和最终结果(SEER)数据库中选择了2010至2015年间被诊断为肾癌和肺转移的患者。选择纳入标准和排除标准后，其余患者纳入模型分析。最小绝对收缩和选择算子(LASSO)回归被用来选择最重要的特征来构建预测癌症特异性生存的诺模图。校准图和一致性指数(C指数)被用来评估验证队列中诺模图的有效性。采用Kaplan-Meier(KM)生存曲线评价套索回归选择的重要因素与预后的关系。绘制受试者工作特征(ROC)曲线，比较我们所建立的诺模图和基于TNM分期的模型的敏感性和特异性。共有1369名患者符合纳入标准，但不符合排除标准。套索回归模型将15个特征减少为7个潜在的生存预测因素，包括肿瘤分级、手术范围、N和T状态、组织学特征以及脑和骨转移状态。这些特征在KM生存曲线上具有良好的区分性。诺模图显示了出色的判别力(C指数，0.71；95%可信区间：0.70至0.72)，并在癌症特异性1年和2年生存率方面进行了良好的校准。当应用于验证队列时，诺模图显示出很大的区分力(C指数0.68)和足够的校正。诺模图的曲线下面积(AUC)在1年和2年分别为0.767和0.780，TNM分期的AUC分别为0.617和0.618。我们的诺模图可能在预测有肺转移的肾癌患者的癌症特异性生存方面发挥重要作用。
The optimal tool for predicting the survival of renal cell carcinoma (RCC) patients with lung metastases remains controversial. We selected patients diagnosed with RCC and lung metastases, from 2010 to 2015, from the Surveillance, Epidemiology, and End Results (SEER) database. After the selection of inclusion criteria and exclusion criterion, the rest of the patients were incorporated into model analysis. Least absolute shrinkage and selection operator (LASSO) regression was used to select the most important features for construction of a nomogram predicting cancer-specific survival. A calibration plot and the concordance index (C-index) were used to estimate nomogram efficacy in a validation cohort. The association between important factors selected by LASSO regression, and prognosis was assessed by the Kaplan-Meier (KM) survival curve. The receiver operating characteristic (ROC) curves were drawn to compare sensitivity and specificity between the nomogram we built and the TNM stage-based model. A total of 1,369 patients met the inclusion criteria, but not the exclusion criteria. The LASSO regression model reduced 15 features to seven potential predictors of survival, including tumor grade, the extent of surgery, N and T status, histological profile, and brain and bone metastasis status. Such features had good discrimination in the KM survival curves. The nomogram showed excellent discriminatory power (C-index, 0.71; 95% confidence interval: 0.70 to 0.72) and good calibration in terms of both 1- and 2-year cancer-specific survival. The nomogram showed great discriminatory power (C-index 0.68) and adequate calibration when applied to the validation cohort. The areas under the curve (AUCs) of nomogram were 0.767 and 0.780, respectively, and the AUCs of TNM stage were 0.617 and 0.618 at 1 and 2 years, respectively. Our nomogram might play a major role in predicting the cancer-specific survival of RCC patients with lung metastases.
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影响因子：
45.3
作者：
Motzer, RJ;Mazumdar, M;Ferrara, J
通讯作者：
Ferrara, J
影响因子：
6.6
作者：
Kattan, MW;Reuter, V;Russo, P
通讯作者：
Russo, P
影响因子：
50.5
作者：
Négrier, S;Escudier, B;Lasset, C
通讯作者：
Lasset, C
影响因子：
--
作者：
Jing CY;Fu YP;Shen HJ;Zheng SS;Lin JJ;Yi Y;Huang JL;Xu X;Zhang J;Zhou J;Fan J;Ren ZG;Qiu SJ;Zhang BH
通讯作者：
Zhang BH
DOI：
10.1016/s1470-2045(14)71116-7
发表时间：
2015-04
期刊：
The Lancet. Oncology
影响因子：
--
作者：
Balachandran VP;Gonen M;Smith JJ;DeMatteo RP
通讯作者：
DeMatteo RP