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首页> 外文期刊>Cancer Management and Research >Development and Validation of Nomograms for Predicting the Prognosis of Triple-Negative Breast Cancer Patients Based on 379 Chinese Patients
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Development and Validation of Nomograms for Predicting the Prognosis of Triple-Negative Breast Cancer Patients Based on 379 Chinese Patients

机译：基于379例患者的三重阴性乳腺癌患者预测的载体鉴定

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Purpose: We aimed to construct universally applicable nomograms incorporating prognostic factors to predict the prognosis of patients with triple-negative breast cancer (TNBC). Patients and methods: Clinicopathological data of 379 patients with TNBC from March 2008 to June 2014 were retrospectively collected and analyzed. The endpoints were disease-free survival (DFS) and overall survival (OS). Patients were randomly divided into a training group and an independent validation group. In the training group, the prognostic factors were screened to develop nomograms. C-index and calibration curves were used to evaluate the predictive accuracy and discriminative ability of nomograms in both groups. The accuracy of the nomograms was also compared with the traditional American Joint Committee on Cancer Tumor-Node-Metastasis anatomical stage (8th edition). Results: Four prognostic factors (albumin-to-globulin ratio, neutrophil-to-lymphocyte ratio, positive lymph nodes, and tumor size) were used to construct the nomogram of DFS. In addition to the aforementioned factors, age was taken into account in the construction of the OS nomogram. The C-index of the DFS nomogram in the training and validation groups was 0.71 (95% confidence interval [CI]: 0.64–0.77) and 0.69 (95% CI: 0.58–0.79), respectively; the C-index of the OS nomogram was 0.77 (95% CI: 0.70–0.84) and 0.74 (95% CI: 0.62–0.86), respectively. This suggests that the nomograms had high accuracy. Moreover, calibration curves showed good consistencies in both groups. Our models showed superiority in predicting accuracy compared with the AJCC TNM staging system. Furthermore, two web pages of the nomograms were produced: DFS: https://sh-skipper.shinyapps.io/TNBC1/ ; OS: https://sh-skipper.shinyapps.io/TNBC2/ . Conclusion: These predictive models are simple and easy to use, particularly the web versions. They have certain clinical value in predicting the prognosis of patients with TNBC. They can assist doctors in identifying patients at different prognostic risks and strengthen the treatment or follow-up accordingly.
机译：目的：我们旨在构建普遍适用的墨迹图，该载体掺入预后因素，以预测三阴性乳腺癌患者的预后（TNBC）。患者和方法：回顾性和分析了2008年3月至2014年6月379名TNBC患者的临床病理学数据。终点是无病的存活（DFS）和总存活（OS）。患者随机分为培训组和独立的验证组。在培训组中，筛选预后因素以开发载体图。 C折射率和校准曲线用于评估两组载体载体的预测精度和鉴别能力。还与传统的美国癌症肿瘤 - 节点转移解剖学阶段（第8版）进行了比较了载体的准确性。结果：使用四种预后因素（白蛋白 - 球蛋白比，中性粒细胞对淋巴细胞比，阳性淋巴结和肿瘤大小）构建DFS的铭文图。除上述因素外，在核心载体结构建设中考虑了年龄。培训和验证组中DFS载体的C折射率为0.71（95％置信区间[CI]：0.64-0.77）和0.69（95％CI：0.58-0.79）; OS NOMAG图的C折射率分别为0.77（95％CI：0.70-0.84）和0.74（95％CI：0.62-0.86）。这表明载体精度高。此外，校准曲线在两个组中显示出良好的浓度。与AJCC TNM分期系统相比，我们的模型在预测准确性方面表现出优越。此外，制作了两个载体的网页：DFS：https：//sh-skipper.shinyapps.io/tnbc1/; OS：https://sh-skipper.shinyapps.io/tnbc2/。结论：这些预测模型简单易用，尤其是Web版本。它们具有一定的临床价值来预测TNBC患者的预后。他们可以帮助医生识别不同预后风险的患者，并相应地加强治疗或随访。

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