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目的：探讨增殖细胞核抗原（ＰＣＮＡ）、原癌基因（ＣｅｒｂＢ２）、组织蛋白酶Ｄ（ＣａｔｈＤ）、转移抑制基因（ｎｍ２３Ｈ１）、微血管数（ＭＶＣ）、肥大细胞数（ＭＣ）、雌激素调节基因（ＰＳ２）、前列腺特异抗原（ＰＳＡ）９个生物学因素与乳腺浸润性癌（ｉｎｖａｓｉｖｅｂｒｅａｓｔｃａｎｃｅｒ，ＩＢＣ）预后的关系。方法：单因素分析：ＫａｐｌａｎＭｅｉｒ生存曲线法。列联检验法。多因素分析：ＣＯＸ比例风险模型。结果：经ＣＯＸ模型ＭＰＬＲ方法检验显示出明显影响乳腺浸润性癌预后的４个因素，ＰＳ２、ＭＶＣ、ｎｍ２３Ｈ１、ＣｅｒｂＢ２．用比例风险模型计算出每个患者的预后指数ＰＩ（Ｐｒｏｇｎｏｓｔｉｃｉｎｄｅｘ），根据预后指数大小将８６例乳腺癌术后患者分为２组，分别建立其术后生存率预测模型。结果提示ＰＩ值愈大，预后愈差，反之预后则好。结论：ＰＳ２、ＭＶＣ、ｎｍ２３Ｈ１、ＣｅｒｂＢ２是乳腺浸润性癌术后独立的预后指标。ＰＩ可能是临床评价病人预后、识别ＩＢＣ术后复发的高危险性病人很有实用价值的指标。
Objective: To investigate the effects of proliferating cell nuclear antigen (PCNA), proto-oncogene (CerbB2), cathepsin D (CathD), metastasis suppressor gene (nm23H1), microvessel count (MVC), and mast cell number (MC) The relationship between 9 biological factors including estrogen-regulated gene (PS2) and prostate-specific antigen (PSA) and the prognosis of invasive breast cancer (IBC). Methods: Single factor analysis: Kaplan-Meir survival curve method. Alignment test. Multivariate analysis: COX proportional hazard model. RESULTS: The COX model MPLR method showed four factors that significantly affected the prognosis of invasive breast cancer, PS2, MVC, nm23-H1, and C-erbB-2. The prognostic index (PI) of each patient was calculated using a proportional hazards model. According to the prognostic index, 86 breast cancer patients were divided into 2 groups and their postoperative survival rate prediction models were established. The results suggest that the greater the PI value, the worse the prognosis, whereas the prognosis is better. Conclusion: PS2, MVC, nm23H1, and CerbB2 are independent prognostic indicators of breast invasive carcinoma. PI may be a useful indicator for clinical evaluation of patient prognosis and identification of high-risk patients with IBC postoperative recurrence.