Predictive nomogram based on serum tumor markers and clinicopathological features for stratifying lymph node metastasis in breast cancer.
Predictive nomogram based on serum tumor markers and clinicopathological features for stratifying lymph node metastasis in breast cancer.
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基于血清肿瘤标志物和临床病理特征的预测列线图对乳腺癌淋巴结转移进行分层
DOI：
10.1186/s12885-022-10436-3
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发表时间：
2022-12-19
期刊：
影响因子：
3.8
通讯作者：
中科院分区：
文献类型：
--
作者：
本研究旨在结合患者的临床病理及肿瘤特征因素，建立预测患者腋窝淋巴结状态的nomogram。共有705名乳腺癌患者参加了这项研究。所有患者随机分为训练组和验证组。采用单变量和多变量有序逻辑回归确定各变量的预测能力。根据从逻辑回归结果中选择的因素进行nomogram分析。采用受试者工作特征曲线（ROC）分析、校正图和决策曲线分析（DCA）评价模型的判别能力和准确性。Logistic回归分析显示，CEA、CA125、CA153、肿瘤大小、血管浸润、钙化和肿瘤分级是aln阳性的独立预后因素。综合所有预测因素，成功开发并验证了模态图。无ALN转移、ALN阳性、ALN 4次及以上转移的nomogram c -index预测训练组为0.826、0.706、0.855，验证组为0.836、0.731、0.897。此外，标定图和DCA显示了我们的模态图令人满意的性能。我们成功构建并验证了结合患者临床病理和肿瘤特征因素预测患者腋窝淋巴结状态的nomogram。
This study was aimed to establish the nomogram to predict patients’ axillary node status by using patients’ clinicopathological and tumor characteristic factors. A total of 705 patients with breast cancer were enrolled in this study. All patients were randomly divided into a training group and a validation group. Univariate and multivariate ordered logistic regression were used to determine the predictive ability of each variable. A nomogram was performed based on the factors selected from logistic regression results. Receiver operating characteristic curve (ROC) analysis, calibration plots and decision curve analysis (DCA) were used to evaluate the discriminative ability and accuracy of the models. Logistic regression analysis demonstrated that CEA, CA125, CA153, tumor size, vascular-invasion, calcification, and tumor grade were independent prognostic factors for positive ALNs. Integrating all the predictive factors, a nomogram was successfully developed and validated. The C-indexes of the nomogram for prediction of no ALN metastasis, positive ALN, and four and more ALN metastasis were 0.826, 0.706, and 0.855 in training group and 0.836, 0.731, and 0.897 in validation group. Furthermore, calibration plots and DCA demonstrated a satisfactory performance of our nomogram. We successfully construct and validate the nomogram to predict patients’ axillary node status by using patients’ clinicopathological and tumor characteristic factors.
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DOI：
10.1016/s1470-2045(14)70460-7
发表时间：
2014-11
期刊：
The Lancet. Oncology
影响因子：
--
作者：
Donker M;van Tienhoven G;Straver ME;Meijnen P;van de Velde CJ;Mansel RE;Cataliotti L;Westenberg AH;Klinkenbijl JH;Orzalesi L;Bouma WH;van der Mijle HC;Nieuwenhuijzen GA;Veltkamp SC;Slaets L;Duez NJ;de Graaf PW;van Dalen T;Marinelli A;Rijna H;Snoj M;Bundred NJ;Merkus JW;Belkacemi Y;Petignat P;Schinagl DA;Coens C;Messina CG;Bogaerts J;Rutgers EJ
通讯作者：
Rutgers EJ
影响因子：
3
作者：
Chao, C;Wong, SL;McMasters, KM
通讯作者：
McMasters, KM
影响因子：
2.6
作者：
Radenkovic, Sandra;Milosevic, Zorica;Jurisic, Vladimir
通讯作者：
Jurisic, Vladimir
影响因子：
45.3
作者：
Coutant, Charles;Olivier, Camille;Rouzier, Roman
通讯作者：
Rouzier, Roman
影响因子：
51.1
作者：
Krag, David N.;Anderson, Stewart J.;Julian, Thomas B.;Brown, Ann M.;Harlow, Seth P.;Costantino, Joseph P.;Ashikaga, Takamaru;Weaver, Donald L.;Mamounas, Eleftherios P.;Jalovec, Lynne M.;Frazier, Thomas G.;Noyes, R. Dirk;Robidoux, Andre;Scarth, Hugh M. C.;Wolmark, Norman
通讯作者：
Wolmark, Norman