SURVIVAL DETERMINANTS IN PATIENTS WITH ADVANCED OVARIAN-CANCER
SURVIVAL DETERMINANTS IN PATIENTS WITH ADVANCED OVARIAN-CANCER
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DOI：
10.1006/gyno.1993.1195
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发表时间：
1993-08-01
影响因子：
4.7
通讯作者：
MOEKEN, CM
中科院分区：
文献类型：
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作者：
ANSELL, SM;RAPOPORT, BL;MOEKEN, CM
对127例连续晚期可测量卵巢癌妇女进行分析，以评估预测生存的因素。所有患者均接受以顺铂为基础的化疗作为IIIB至IV期疾病的治疗。对18个临床、放射学和生化参数进行单变量和多变量分析。使用递归分割和合并（RPA）来定义具有不同生存潜力的预后子集。在单变量分析中，预测生存的因素是体重减轻、组织学、分期、转移灶数量、腹水存在、残留肿瘤大小和肿瘤缓解率。当这些重要的变量包括在考克斯模型中时，疾病的晚期、除腺浆液性癌以外的组织学类型、肿瘤块的存在和肿瘤反应的缓慢速率独立地预测较差的生存率。使用三个疾病相关的预后变量，RPA模型推导出，并确定了三个组的中位生存时间分别为76，28和21个月（P= 0.001）。最佳生存期为76个月，见于III期非大体积腺浆液性卵巢癌患者。结论：肿瘤反应率在预测卵巢癌患者的预后方面是重要的。此外，RPA模型强调了预后因素之间的相互作用，并确定了预计10年生存率为50%的患者亚组。
An analysis was performed on 127 consecutive women with advanced measurable ovarian cancer to evaluate factors predicting for survival. All patients receivedcis-platinum-based chemotherapy as treatment for stage IIIB to stage IV disease. Eighteen clinical, radiological, and biochemical parameters were subjected to univariate and multivariate analyses. Recursive partitioning and amalgamation (RPA) was used to define prognostic subsets with different survival potentials. In the univariate analysis, factors that predicted for survival were weight loss, histology, stage, number of metastases, presence of ascites, size of the residual tumor, and rate of tumor response. When these significant variables were included in a Cox model, advanced stage of disease, histology other than adenoserous carcinoma, the presence of tumor bulk, and a slow rate of tumor response independently predicted a poorer survival. Using the three disease-related prognostic variables, a RPA model was derived and three groups were identified with median survival times of 76, 28, and 21 months, respectively (P= 0.001). The best survival time of 76 months was seen in patients with stage III, non-bulky, adenoserous ovarian carcinoma. It is concluded that the rate of tumor response is important in predicting the outcome of patients with ovarian cancer. Furthermore, the interactions between prognostic factors are emphasized by the RPA model and a subgroup of patients with a projected 10-year survival of 50% is identified.