Chang Chung, Chiang An Jen, Chen Wei-An, Chang Hsueh-Wen, Chen Jiabin
Department of Applied Mathematics, National Sun Yat-sen University, Kaohsiung, Taiwan, Republic of China.
Department of Obstetrics & Gynecology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan, Republic of China.
Biomark Med. 2016;10(1):53-61. doi: 10.2217/bmm.15.110. Epub 2015 Nov 13.
To develop a new package of joint model to fit longitudinal CA125 in epithelial ovarian cancer relapse.
PATIENTS & METHODS: Included were 305 epithelial ovarian cancer patients who reached complete remission after cytoreductive surgery and first-line chemotherapy. Univariate and multivariate analysis with a joint model was performed to select independent risk factors, which were subsequently combined to predict recurrence.
Independent factors were longitudinal CA125, age, stage and residual tumor size (p < 0.05). Prediction of recurrence with these factors had an average of 80.7% accuracy, 5.6-10.7% better than kinetic factors.
The new package of joint model fits longitudinal CA125 well. Potential application can be extended to other biomarkers.
开发一种新的联合模型包，以拟合上皮性卵巢癌复发时的纵向CA125数据。
纳入305例上皮性卵巢癌患者，这些患者在肿瘤细胞减灭术和一线化疗后达到完全缓解。采用联合模型进行单因素和多因素分析以选择独立危险因素，随后将这些因素结合起来预测复发情况。
独立因素为纵向CA125、年龄、分期和残余肿瘤大小（p<0.05）。利用这些因素预测复发的准确率平均为80.7%，比动力学因素高5.6 - 10.7%。
新的联合模型包能很好地拟合纵向CA125数据。其潜在应用可扩展到其他生物标志物。
