A longitudinal analysis with CA-125 to predict overall survival in patients with ovarian cancer.
- Author:
An Jen CHIANG
1
;
Jiabin CHEN
;
Yu Che CHUNG
;
Huan Jung HUANG
;
Wen Shiung LIOU
;
Chung CHANG
Author Information
- Publication Type:Original Article
- Keywords: CA-125; Longitudinal analysis; Ovarian cancer; Overall survival; Prediction
- MeSH: Counseling; Diagnosis; Drug Therapy; Half-Life; Humans; Models, Statistical; Neoplasm, Residual; Ovarian Neoplasms*; Retrospective Studies
- From:Journal of Gynecologic Oncology 2014;25(1):51-57
- CountryRepublic of Korea
- Language:English
- Abstract: OBJECTIVE: The objective of this study was to explore the association of longitudinal CA-125 measurements with overall survival (OS) time by developing a flexible model for patient-specific CA-125 profiles, and to provide a simple and reliable prediction of OS. METHODS: A retrospective study was performed on 275 patients with ovarian cancer who underwent at least one cycle of primary chemotherapy in our institute. Serial measurements of patients' CA-125 levels were performed at different frequencies according to their clinical plans. A statistical model coupling the Cox proportional hazards and the mixed-effects models was applied to determine the association of OS with patient-specific longitudinal CA-125 values. Stage and residual tumor size were additional variables included in the analysis. RESULTS: A total of 1,601 values of CA-125 were included. Longitudinal CA-125 levels, stage, and the residual tumor size were all significantly associated with OS. A patient-specific survival probability could be calculated. Validation showed that, in average, 85.4% patients were correctly predicted to have a high or low risk of death at a given time point. Comparison with a traditional model using CA-125 half-life and time to reach CA-125 nadir showed that the longitudinal CA-125 model had an improved predicative value. CONCLUSION: Longitudinal CA-125 values, measured from the diagnosis of ovarian cancer to the completion of primary chemotherapy, could be used to reliably predict OS after adjusting for the stage and residual tumor disease. This model could be potentially useful in clinical counseling of patients with ovarian cancer.
