列线图预测淋巴结阴性乳腺癌患者的个体预后。

A nomogram to predict individual prognosis in node-negative breast carcinoma.

机构信息

Laboratoire de transfert d'oncologie biologique, Assistance Publique - Hôpitaux de Marseille, Faculté de Médecine Nord, Marseille, France.

出版信息

Eur J Cancer. 2012 Nov;48(16):2954-61. doi: 10.1016/j.ejca.2012.04.018. Epub 2012 May 31.

DOI:10.1016/j.ejca.2012.04.018

PMID:22658808

Abstract

BACKGROUND

Currently, the benefit of chemotherapy (CT) in node-negative breast carcinoma (NNBC) is discussed. The evaluation of classical clinical and histological factors is limited to assess individual outcome. A statistical model was developed to improve the prognostic accuracy of NNBC.

METHODS

A total of 305 node-negative breast carcinomas who underwent surgery (+/- radiotherapy) but no adjuvant treatment were selected. Putative prognosis factors including age, tumour size, oestrogen receptor (ER), progesterone receptor (PgR), Scarff-Bloom-Richardon (SBR) grading, urokinase plasminogen activator (uPA), plasminogen activator inhibitor 1 (PAI-1) and thymidine kinase (TK) were evaluated. The developed model was internally validated using Harrell's concordance index. A prognosis index (PI) was proposed and compared with Adjuvant! Online program.

RESULTS

Age (p < 0.001), pathological tumour size (pT) (p < 0.001), PgR (p = 0.02), and PAI-1 (p ≤ 0.001) were included in the Cox regression model predicting Breast cancer specific survival (BCSS) at 5-years. Internal validation revealed a concordance index of 0.71. A PI score was derived from our nomogram. The PI score was significantly associated with BCSS (hazard ratio (HR): 4.1 for intermediate, p=0.02, HR: 8.8, p < 0.001 for high group) as compared to Adjuvant! Online score (HR: 1.4, p=0.14).

CONCLUSION

A nomogram can be used to predict probability survival curves for individual breast cancer patients.

摘要

背景

目前，正在讨论化疗（CT）对淋巴结阴性乳腺癌（NNBC）的益处。评估经典的临床和组织学因素仅限于评估个体预后。建立了一个统计模型来提高 NNBC 的预后准确性。

方法

共选择 305 例接受手术（+/- 放疗）但未接受辅助治疗的淋巴结阴性乳腺癌患者。评估了潜在的预后因素，包括年龄、肿瘤大小、雌激素受体（ER）、孕激素受体（PgR）、Scarff-Bloom-Richardon（SBR）分级、尿激酶型纤溶酶原激活物（uPA）、纤溶酶原激活物抑制剂 1（PAI-1）和胸苷激酶（TK）。使用 Harrell 的一致性指数对内建模型进行了验证。提出了一个预后指数（PI），并与 Adjuvant! Online 程序进行了比较。

结果

年龄（p<0.001）、病理肿瘤大小（pT）（p<0.001）、PgR（p=0.02）和 PAI-1（p≤0.001）被纳入预测 5 年乳腺癌特异性生存（BCSS）的 Cox 回归模型。内部验证显示一致性指数为 0.71。从我们的列线图中得出了一个 PI 评分。PI 评分与 BCSS 显著相关（中危组 HR：4.1，p=0.02，高危组 HR：8.8，p<0.001），而与 Adjuvant! Online 评分（HR：1.4，p=0.14）相比。