Introduction/Background By analyzing the longitudinal data of serum CA (cancer antigen) 125 data during follow-up, we developed a framework for the dynamic determination of the follow-up interval based on serum biomarkers.
Methodology The longitudinal data of CA125 tests from routine 3-month follow-up visits of advanced epithelial ovarian cancer were retrospectively retrieved. A repeated-measure analysis using mixed model effects was developed to predict the probability of short-term recurrence (within 3 months and 6 months). The probability was calculated for the three predefined risk groups: serum CA125 levels lower than 10 U/ml, between 10 and 20 U/ml, and higher than 20 U/ml.
Results The 346 CA125 test results from 115 patients were subjected to longitudinal analysis. For results less than 10 U/ml, the predicted probabilities that the patient would experience recurrent disease within 3 and 6 months were 4.1% and 14.0%, respectively. For results between 10 U/ml and 20 U/ml, the predicted probabilities were 9.8% and 40.5%, respectively. For results greater than 20 U/ml, the predicted probabilities increased to 40.3% and 61.0%, respectively. Multivariate analysis indicated that the current CA125 level was the sole factor significantly associated with recurrence both within 3 months and within 6 months (all P < 0.001).
Conclusion We developed a risk model to predict the short-term recurrence risk of ovarian cancer and proposed a framework for the dynamic determination of the follow-up interval based on the results of CA125 testing.
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