Early modeled longitudinal CA-125 kinetics and survival of ovarian cancer patients: A GINECO AGO MRC CTU Study

Abstract

Purpose: Regarding cancer antigen 125 (CA-125) longitudinal kinetics during chemotherapy, the actual predictive value of theGynecologicCancer Intergroup(GCIG) CA-125 response criterion is questioned. The modeled CA-125 elimination rate constant KELIM exhibited higher prognostic value in patients with recurrent ovarian cancer enrolled in the CALYPSO trial. The objective was to validate the higher predictive and prognostic values of KELIM during first-line treatments. Experimental Design: Data from three large phase III trials were analyzed: AGO OVAR 9 [learning set: carboplatinpaclitaxel (CP) ± gemcitabine; n = 1,288]; AGO OVAR 7 (validation set: CP ± topotecan; n = 192); and ICON7 (validation set: CP ± bevacizumab; n = 1,388). The CA-125 profiles were fit with a nonlinear mixed-effect model during the first 100 days, and the individual KELIM were calculated. KELIM prognostic and predictive values for survival were assessed against GCIG criterion and other prognostic factors in univariate/multivariate analyses. Results: The GCIG CA-125 endpoint provided no meaningful predictive/prognostic information. C-index analyses confirmed the higher predictive value of KELIM compared with GCIG criterion for progression-free survival and overall survival (OS). KELIM provided reproducible prognostic information. Patients with favorable KELIM ≥ upper tercile (0.0711 per days) consistently experienced better OS, with HRs between 0.44 and 0.58 (e.g.,median OS >65 months vs. l35 months). Conclusions: Modeled KELIM provides higher predictive and prognostic information based on CA-125 longitudinal kinetics compared with GCIGresponse criteria during first-line chemotherapy. Integration of this endpoint in guidelines may be considered. Individual KELIM and survival simulations can be calculated at http://www.biomarker-kinetics.org/. Further assessment of the surrogate value of KELIM treatment- related variations in a GCIG meta-analysis is warranted.