Chung Chang1, An Jen Chiang2,3,4, Wei-An Chen1, Hsueh-Wen Chang3, Jiabin Chen5,6. 1. Department of Applied Mathematics, National Sun Yat-sen University, Kaohsiung, Taiwan, Republic of China. 2. Department of Obstetrics & Gynecology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan, Republic of China. 3. Department of Biological Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan, Republic of China. 4. Department of Pharmacy & Graduate Institute of Pharmaceutical Technology, Tajen University, Pingtung, Taiwan, Republic of China. 5. Multidisciplinary Science Research Center, National Sun Yat-sen University, Kaohsiung, Taiwan, Republic of China. 6. Da-Yeh University, Changhua, Taiwan, Republic of China.
Abstract
AIMS: 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. RESULTS: 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. CONCLUSION: The new package of joint model fits longitudinal CA125 well. Potential application can be extended to other biomarkers.
AIMS: To develop a new package of joint model to fit longitudinal CA125 in epithelial ovarian cancer relapse. PATIENTS & METHODS: Included were 305 epithelial ovarian cancerpatients 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. RESULTS: 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. CONCLUSION: The new package of joint model fits longitudinalCA125 well. Potential application can be extended to other biomarkers.
Authors: Azahara Palomar Muñoz; José Manuel Cordero García; Mª Del Prado Talavera Rubio; Ana Mª García Vicente; Francisco José Pena Pardo; Germán Andrés Jiménez Londoño; Ángel Soriano Castrejón; Enrique Aranda Aguilar Journal: Medicine (Baltimore) Date: 2018-04 Impact factor: 1.889