Cao Yuting, Jiang Yi, Lin Xiao, Liu Jinsong, Lu Tao, Cheng Wenjun, Yan Fangrong
Int J Gynecol Cancer. 2018 Jan;28(1):85-91. doi: 10.1097/IGC.0000000000001134.
In clinical practice, gynecologic oncologists are interested in predicting the prognosis of patients through information from different sources. Recently, the overall survival (OS) of ovarian cancer patients has been widely and intensively researched, and a large number of risk factors have been determined, including the biomarker of cancer antigen 125 (CA-125). For newly diagnosed patients, it is critical to construct effective prognostic models to predict prognosis dynamically by combining their CA-125 values with adjusted clinical factors.
METHODS/MATERIALS: A total of 227 ovarian cancer participants entered this study. A 4-step method was used to construct a joint model to examine the association between longitudinal CA-125 measurements and OS time, to explore time-independent predictive factors influencing OS, and to obtain an accurate and credible dynamic prediction of OS for specific subjects.
We found that CA-125 values were greatly affected by observation time, menarche, Federation International of Gynecology and Obstetrics stage, and ascites at baseline. Similarly, CA-125 values, menopause, Federation International of Gynecology and Obstetrics stage, and surgery state at baseline were selected from the best Cox proportion hazard model and showed a strong correlation with OS. In addition, the analyses presented by the joint model depict that, as time goes by, increasing CA-125 was deemed to be a significant predictor of death.
Together, our results show that a joint model could be highly efficient in clinical consultation and diagnosis for patients newly diagnosed as having ovarian cancer. Longitudinal CA-125 values, which are measured over time, can be used to credibly predict OS after taking all adjusted covariates into account.
在临床实践中，妇科肿瘤学家有兴趣通过不同来源的信息预测患者的预后。最近，卵巢癌患者的总生存期（OS）受到了广泛而深入的研究，并且已经确定了大量风险因素，包括癌抗原125（CA-125）生物标志物。对于新诊断的患者，通过将其CA-125值与调整后的临床因素相结合来构建有效的预后模型以动态预测预后至关重要。
方法/材料：共有227名卵巢癌参与者进入本研究。采用四步法构建联合模型，以检验纵向CA-125测量值与OS时间之间的关联，探索影响OS的时间独立预测因素，并获得针对特定受试者的准确可靠的OS动态预测。
我们发现CA-125值受观察时间、初潮、国际妇产科联盟分期和基线腹水的影响很大。同样，从最佳Cox比例风险模型中选择了CA-125值、绝经、国际妇产科联盟分期以及基线手术状态，它们与OS显示出强烈相关性。此外，联合模型的分析表明，随着时间的推移，CA-125升高被认为是死亡的重要预测因素。
总之，我们的结果表明联合模型在新诊断为卵巢癌的患者的临床咨询和诊断中可能非常有效。在考虑所有调整后的协变量后，随时间测量的纵向CA-125值可用于可靠地预测OS。
