预后指数累计分布曲线拐点分析在卵巢癌患者预后分类中的运用

Application of cumulative distribution curve inflection point analysis of prognosis index in prognosis of ovarian cancer patients

摘要:

目的  了解卵巢癌（OVCA）患者的预后，帮助临床医师对OVCA患者制定科学合理的治疗方案。方法  利用多重逐步Cox比例风险回归模型分析RNAs表达数据，建立OVCA患者的预后指数（PI）模型。依据PI分布曲线的拐点，将OVCA患者分为高危组和低危组。结果  由10个RNAs表达数据计算得到PI值的累计分布曲线，有1个拐点（278.00，-0.780）。将552例OVCA患者分为高危组和低危组，中位生存时间分别为1 678和1 058 d。经Log-rank检验，两组间生存率比较，差异有统计学意义（χ2=46.365，P =0.000），低危组生存率高于高危组。实例分析表明，利用PI曲线拐点对OVCA患者预后进行分类，具有较好的分类效果。结论  用累计分布曲线拐点方法建立OVCA患者的预后分类模型，能进行很好分类，为OVCA患者的治疗和管理提供新的科学依据。

Abstract:

Objective To understand the prognosis of ovarian cancer, and help clinicians to make scientific and reasonable treatment plans for ovarian cancer patients. Methods Using the Cox's proportional hazards regression equation method, a prognostic index (PI) was constructed for ovarian cancer patients. With the individual inflection point of the prognostic index curve, ovarian cancer patients were classified to high-risk group and low-risk group. Results The cumulative distribution curves were established using the expression data of 10 RNAs, and 1 inflection point (278.00, -0.780) was obtained. Using this inflection point, 552 ovarian cancer patients were divided into high-risk group and low-risk group, and the median survival time of the two groups was 1,678 days and 1,058 days respectively. Log-rank test showed that the survival rate of the low-risk group was significantly higher than that of the high-risk group (χ2 = 46.365, P = 0.000). Case analysis showed that the inflection point of the prognostic index curve had good classification effect on the patients with ovarian cancer. Conclusions The prognosis model of ovarian cancer patients based on the inflection point of the cumulative distribution curve can accurately classify the prognosis of ovarian cancer patients, which will provide a new scientific basis for the treatment and management of ovarian cancer patients.