Nomura Y, Tashiro H, Osaki A
Department of Breast Surgery, National Kyushu Cancer Center, Fukuoka, Japan.
Oncology. 1995 Sep-Oct;52(5):376-80. doi: 10.1159/000227492.
Although clinicians want to know how tumor response affects the survival of advanced cancer patients, the direct comparison of response with survival is severely discouraged because of biases essentially involved. In 159 patients with advanced breast cancer treated with adreno-oophorectomy, we analyzed the survival of the patients using the Kaplan and Meier method with the landmark method (landmark time of 3 months after treatment). A multivariate analysis with the Cox proportional hazard model for survival with explanatory variables including response of patients at the landmark time (3 months after therapy) was performed in order to find probable prognostic factors. By the Kaplan and Meier curves with the landmark method, response category showed a significant difference in the survival of the patients (log rank test; p < 0.0001). In the Cox model in the patients of landmark time of 3 months after therapy, we found that response was the most powerful factor for survival out of 10 variables (p = 0.0001), and the dominant site of metastasis significantly and independently modified the survival length (p = 0.001). ER status was indifferent in the analysis; however, when the response category was not included, ER was shown to be most influential. We propose that a combination of the Cox model with the landmark method would be a rational and useful approach to estimate probable prognostic factors including treatment outcome variables such as response for the survival analysis in advanced cancer patients.
尽管临床医生想知道肿瘤反应如何影响晚期癌症患者的生存,但由于存在本质上的偏差,强烈不鼓励将反应与生存进行直接比较。在159例接受肾上腺卵巢切除术治疗的晚期乳腺癌患者中,我们采用Kaplan-Meier法和标志性方法(治疗后3个月为标志性时间)分析了患者的生存情况。为了找出可能的预后因素,我们使用Cox比例风险模型对生存情况进行多变量分析,解释变量包括标志性时间(治疗后3个月)患者的反应。通过采用标志性方法的Kaplan-Meier曲线,反应类别在患者生存方面显示出显著差异(对数秩检验;p<0.0001)。在治疗后3个月标志性时间的患者的Cox模型中,我们发现反应是10个变量中对生存影响最有力的因素(p=0.0001),转移的主要部位显著且独立地改变了生存长度(p=0.001)。雌激素受体(ER)状态在分析中无差异;然而,当不包括反应类别时,ER显示出最具影响力。我们建议,将Cox模型与标志性方法相结合,将是一种合理且有用的方法,用于估计包括治疗结果变量(如反应)在内的可能的预后因素,以用于晚期癌症患者的生存分析。