Background: Unexpected results were recently reported about the poor surrogacy of Gynecologic Cancer Intergroup (GCIG) defined CA-125 response in recurrent ovarian cancer (ROC) patients. Mathematical modeling may help describe CA-125 decline dynamically and discriminate prognostic kinetic parameters.
Methods: Data from CALYPSO phase III trial comparing 2 carboplatin-based regimens in ROC patients were analyzed. Based on population kinetic approach, serum [CA-125] concentration-time profiles during first 50 treatment days were fit to a semi-mechanistic model with following parameters: "d[CA-125]/dt=(KPROD∗exp (BETA∗t))∗Effect-KELIM∗[CA-125]" with time, t; tumor growth rate, BETA; CA-125 tumor production rate, KPROD; CA-125 elimination rate, KELIM and K-dependent treatment indirect Effect. The predictive values of kinetic parameters were tested regarding progression-free survival (PFS) against other reported prognostic factors.
Results: Individual CA-125 kinetic profiles from 895 patients were modeled. Three kinetic parameters categorized by medians had predictive values using univariate analyses: K; KPROD and KELIM (all P<0.001). Using Cox multivariate analysis, 5 independent predictors of PFS remained significant: GCIG CA-125 response (favoring carboplatin-paclitaxel arm), treatment arm, platinum free-interval, measurable lesions and KELIM (HR=0.53; 95% CI 0.45-0.61; P<0.001).
Conclusions: Mathematical modeling of CA-125 kinetics in ROC patients enables understanding of the time-change components during chemotherapy. The contradictory surrogacy of GCIG-defined CA-125 response was confirmed. The modeled CA-125 elimination rate KELIM, potentially assessable in routine, may have promising predictive value regarding PFS. Further validation of this predictive marker is warranted.
Keywords: CA-125 antigen; Computer simulation; Kinetics; Ovarian epithelial cancer; Survival analysis.
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