卵巢浆液性腺癌预后评分模型的建立及应用

Construction and utilization of the prognostic model of serous ovarian adenocarcinoma

目的通过分析卵巢浆液性腺癌的预后相关因素,建立其预后评分模型,并应用于临床预测患者的生存概率。方法对北京大学人民医院104例卵巢浆液性腺癌患者的临床病理资料进行回顾性分析。Kaplan-meier单因素生存分析筛选预后相关因素；COX单因素和多因素回归分析确定各预后相关因素内分层因素及各预后相关因素的风险系数；Pearson等级相关分析剔除各预后相关因素间的相互影响。根据上述两个风险系数对各预后相关因素进行评分,建立预后评分模型,据此预测患者的生存概率。结果单因素生存分析显示,手术病理分期(P=0．0029)、病理分级(P= 0．0054)、术后残留灶直径(P=0．0000)、淋巴结转移(P=0．0000)以及化疗情况(P=0．0000)是卵巢浆液性腺癌的预后相关因素。Pearson等级相关分析显示,手术病理分期对预后的影响最大,随后依次为化疗、淋巴结转移、病理分级以及术后残留灶直径(其独立风险系数分别为1．3392、0．9206、0．7071、0．6004、0．4985)。根据预后风险系数对各预后相关因素进行评分,得到了卵巢浆液性腺癌的预后评分模型。通过该模型量化了化疗和术后残留灶直径这两个可变因素对患者生存概率的影响。随着预后评分的增加,患者的生存概率降低。结论通过筛选影响预后的相关因素,建立卵巢浆液性腺癌的预后评分模型。该模型可以量化预后相关因素,尤其是化疗和残留灶直径这两个指标,预测患者的生存概率,为临床工作提供了一种科学判断预后的方法。

Objective To analyze the related factors with prognosis in patients with serous ovarian adenocarcinoma and to set up a prognostic model of serous ovarian adenocareinoma. Methods The clinical, pathological and follow-up data of 104 cases with serous ovarian adenocarcinoma were retrospectively analyzed. Kaplan-meier univariate analysis was used to screen the prognostic factors; COX univariate and multivariate analyses were used to determine the risk coefficient of each factors and different layers in each factor. Pearson rank correlation was used to reject the influence of different factors with each other. And the prognostic model of serous ovarian adenocarcinoma was set up based on the result of the above study, which could be used to deduce the survival probability of patients with serous ovarian adenocarcinoma. Results International Federation of Gynecology and Obstetrics （FIGO） stage （ P = 0. 0029 ）, histological grade （ P = 0. 0054 ）, residual disease （ P = 0. 0000）, metastasis of lymph nodes （ P = 0. 0000 ） and chemotherapy （ P = 0. 0000） were the related factors of prognosis in patients with serous ovarian adenocareinoma, of which FIGO stage was the most important one, followed sequentially by histological grade, metastasis of lymph node, residual disease and chemotherapy （ the independent risk coefficient of each factor was 1. 3392, 0. 9206, 0. 7071, 0. 6004, 0. 4985 in sequence）. We set up a prognosis model according to the prognostic index of each factors. The effect of chemotherapy and residual disease on prognosis could be quantified by this model, and the higher the score, the lower the survival probability of patients. Conclusions FIGO stage, histological grade, residual disease, metastasis of lymph nodes and chemotherapy are important prognostic factors of serous ovarian adenocarcinoma. This model can be used to estimate the prognosis of patients withserous ovarian adenocarcinoma, and the effect of both chemotherapy and residual disease on the prognosis could be quantified by the model.