摘要/Abstract
摘要： 目的·探究乳腺癌脊柱转移患者的预后影响因素并构建预后预测模型。方法·回顾性研究2008年1月—2016年1月上海交通大学医学院附属瑞金医院诊治的乳腺癌脊柱转移患者160例，就临床特征与预后情况进行生存分析，探索预后影响因素，并依据各因素的回归系数完成预后预测模型的构建。结果·160例乳腺癌脊柱转移患者，平均年龄56.8岁（范围22～82岁），中位随访时间40（24，55）个月。生存分析结果显示，患者一般情况、激素受体表达情况、内脏转移情况和血清糖类抗原125水平与脊柱转移后总生存期显著相关（均P<0.05）。依据各因素回归系数，构建0～6分的生存预测模型，按照不同得分将患者分为3组：0～1分为低危组，2～4分为中危组，5～6分为高危组。结论·患者一般情况、激素受体表达情况、内脏转移情况和血清糖类抗原125水平是乳腺癌脊柱转移患者的独立预后影响因素，而基于该4项临床特征构建的预后预测模型可用于评估这类患者的预后。
关键词: 乳腺癌, 脊柱转移, 预后预测模型, 雌激素受体, 孕激素受体, 内脏转移, 糖类抗原125
Abstract:
Objective · To explore the prognostic factors for the breast cancer patients with spinal metastasis, and establish a prognostic scoring model. Methods · A total of 160 breast cancer patients with spinal metastasis in Ruijin Hospital, Shanghai Jiao Tong University School of Medicine from January 2008 to January 2016 were retrospectively identified. The clinical characteristics and prognosis were analyzed by univariate and multivariate survival analysis to explore the prognostic factors. And then a prognostic scoring model was developed according to the regression coefficient for each independent prognostic factor. Results · The 160 breast cancer patients with spinal metastasis whose average age was 56.8 years (range 22-82 years) were identified, and the median follow-up was 40 (24, 55) months. The multivariate Cox analysis showed that the patients' general condition, hormone receptor expression, visceral metastasis, and serum carbohydrate antigen 125 (CA125) level significantly influenced survival (P<0.05). According to the regression coefficients, a survival prediction scoring model comprising these factors was established, which ranged from 0 to 6 points. Three risk groups with different prognoses were identified : low risk group (0-1 point), intermediate risk group (2-4 points), and high risk group (5-6 points). Conclusion · The general condition, hormone receptor expression, visceral metastasis, and serum CA125 level were independent prognostic factors for the breast cancer patients with spinal metastasis. And the prognostic scoring model comprising these four clinical factors can effectively predict the patients' prognoses.
Key words: breast cancer, spinal metastasis, prognostic scoring model, estrogen receptor, progesterone receptor, visceral metastasis, carbohydrate antigen 125 (CA125)
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