A Nomogram Predicting the Probability of Primary Breast Cancer Survival at 2-and 5-Years Using Pathological and Biological Tumor Parameters
A Nomogram Predicting the Probability of Primary Breast Cancer Survival at 2-and 5-Years Using Pathological and Biological Tumor Parameters
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DOI：
10.1002/jso.21712
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发表时间：
2011-06-01
影响因子：
2.5
通讯作者：
Martin, Pierre-Marie
中科院分区：
文献类型：
--
作者：
Mazouni, Chafika;Bonnier, Pascal;Martin, Pierre-Marie
目的：我们的目标是基于肿瘤病理和生物学参数，开发一种预测原发性乳腺癌个体总生存期（OS）的nomogram方法。方法：对180例原发性乳腺癌患者进行回顾性队列研究，建立nomographic。采用原发肿瘤的病理因素和肿瘤蛋白酶的前瞻性测定。采用多变量Cox比例风险模型探讨与OS的关系，并采用回归系数构建nomogram。用200个bootstrap重新采样对nomogram进行内部验证。结果：nomogram最终变量包括肿瘤大小（P = 0.04）、淋巴结病理状态（P = 0.01）、雌激素受体状态（P = 0.04）、尿激酶纤溶酶原激活物抑制剂-1 （PAI-1; P = 0.02）、胸苷激酶（P = 0.03）、组织蛋白酶D （P = 0.004）。2年和5年nomogram对OS概率的预测精度分别为0.874和0.832。结论：利用组织学和生物学参数成功建立了预测BC患者2年和5年OS的nomogram。这种预后工具在决策和治疗研究中应该证明是有用的。中华外科杂志。2011；103:746 - 750。(C) 2011 Wiley-Liss, Inc。
Purpose: Our objective was to develop a nomogram to predict individual overall survival (OS) for primary breast cancer, based on pathological and biological tumor parameters.Methods: A retrospective study in a cohort of 180 patients with primary breast cancer was used to build the nomogram. Pathological factors and tumor proteases measured prospectively in primary tumors were used. A multivariate Cox proportional hazards model was used to explore the relationship with OS, and regression coefficients were used to build the nomogram. The nomogram was internally validated with 200 bootstrap re-samples.Results: The final variables included in the nomogram comprised tumor size (P = 0.04), nodal pathological status (P = 0.01), estrogen receptor status (P = 0.04), urokinase plasminogen activator inhibitor-1 (PAI-1; P = 0.02), thymidine kinase (P = 0.03), and cathepsin D (P = 0.004). The predictive accuracy of the nomogram at estimating the probability of OS, at both 2 and 5 years, was respectively 0.874 and 0.832 before and after calibration.Conclusion: A nomogram to predict 2- and 5-year OS in BC, using histological and biological parameters was successfully developed. This prognostic tool should prove useful in decision-making and therapeutic research. J. Surg. Oncol. 2011; 103:746-750. (C) 2011 Wiley-Liss, Inc.