Construction and Validation of a Novel Nomogram for Predicting the Risk of Metastasis in a Luminal B Type Invasive Ductal Carcinoma Population.

IF 2.1 Q3 ONCOLOGY World Journal of Oncology Pub Date : 2023-12-01 Epub Date: 2023-11-03 DOI:10.14740/wjon1553
Xu Dong Zhu, Jia Hui Yu, Fu Lu Ai, Yue Wang, Wu Lv, Gui Lin Yu, Xian Kui Cao, Jie Lin
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Abstract

Background: Postoperative distant metastasis is the main cause of death in breast cancer patients. We aimed to construct a nomogram to predict the risk of metastasis of luminal B type invasive ductal carcinoma.

Methods: We applied the data of 364 luminal B type breast cancer patients between 2008 and 2013. Patients were categorized into modeling group and validation group randomly (1:1). The breast cancer metastasis nomogram was developed from the logistic regression model using clinicopathological variables. The area under the receiver-operating characteristic curve (AUC) was calculated in modeling group and validation group to evaluate the predictive accuracy of the nomogram.

Results: The multivariate logistic regression analysis showed that tumor size, No. of the positive level 1 axillary lymph nodes, human epidermal growth factor receptor 2 (HER2) status and Ki67 index were the independent predictors of the breast cancer metastasis. The AUC values of the modeling group and the validation group were 0.855 and 0.818, respectively. The nomogram had a well-fitted calibration curve. The positive and negative predictive values were 49.3% and 92.7% in the modeling group, and 47.9% and 91.0% in the validation group. Patients who had a score of 60 or more were thought to have a high risk of breast cancer metastasis.

Conclusions: The nomogram has a great predictive accuracy of predicting the risk of breast cancer metastasis. If patients had a score of 60 or more, necessary measures, like more standard treatment methods and higher treatment adherence of patients, are needed to take to lower the risk of metastasis and improve the prognosis.

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预测腔内B型浸润性导管癌转移风险的新Nomogram构建与验证
背景:乳腺癌术后远处转移是乳腺癌患者死亡的主要原因。我们的目的是建立一个图来预测腔内B型浸润性导管癌转移的风险。方法:应用2008 - 2013年364例腔内B型乳腺癌患者资料。将患者随机分为建模组和验证组(1:1)。乳腺癌转移形态图是利用临床病理变量建立的逻辑回归模型。模型组和验证组分别计算受试者工作特征曲线下面积(AUC),评价nomogram预测准确度。结果:多因素logistic回归分析显示,肿瘤大小、肿瘤发生率、肿瘤发生率、肿瘤发生率均高于对照组。1级腋窝淋巴结阳性率、人表皮生长因子受体2 (HER2)水平和Ki67指数是乳腺癌转移的独立预测因子。建模组和验证组的AUC值分别为0.855和0.818。图的标定曲线拟合良好。模型组阳性预测值为49.3%,阴性预测值为92.7%,验证组阳性预测值为47.9%,阴性预测值为91.0%。得分在60分以上的患者被认为有乳腺癌转移的高风险。结论:nomogram对乳腺癌转移风险有较高的预测准确性。如果患者的评分在60分及以上,则需要采取必要的措施,如更规范的治疗方法,提高患者的治疗依从性,以降低转移的风险,改善预后。
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来源期刊
CiteScore
6.10
自引率
15.40%
发文量
37
期刊介绍: World Journal of Oncology, bimonthly, publishes original contributions describing basic research and clinical investigation of cancer, on the cellular, molecular, prevention, diagnosis, therapy and prognosis aspects. The submissions can be basic research or clinical investigation oriented. This journal welcomes those submissions focused on the clinical trials of new treatment modalities for cancer, and those submissions focused on molecular or cellular research of the oncology pathogenesis. Case reports submitted for consideration of publication should explore either a novel genomic event/description or a new safety signal from an oncolytic agent. The areas of interested manuscripts are these disciplines: tumor immunology and immunotherapy; cancer molecular pharmacology and chemotherapy; drug sensitivity and resistance; cancer epidemiology; clinical trials; cancer pathology; radiobiology and radiation oncology; solid tumor oncology; hematological malignancies; surgical oncology; pediatric oncology; molecular oncology and cancer genes; gene therapy; cancer endocrinology; cancer metastasis; prevention and diagnosis of cancer; other cancer related subjects. The types of manuscripts accepted are original article, review, editorial, short communication, case report, letter to the editor, book review.
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