| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 3944603 | Gynecologic Oncology | 2014 | 7 Pages |
•Early predictors of clinical benefit during drug development are needed.•The links between early changes in CA125 and PFS in ovarian cancer were quantified.•Early changes in CA125 may be an early predictive tool of the expected gain in PFS.
ObjectiveEarly prediction of the expected benefit of treatment in recurrent ovarian cancer (ROC) patients may help in drug development decisions. The actual value of 50% CA-125 decrease is being reconsidered. The main objective of the present study was to quantify the links between longitudinal assessments of CA-125 kinetics and progression-free survival (PFS) in treated recurrent ovarian cancer (ROC) patients.MethodsThe CALYPSO randomized phase III trial database comparing two platinum-based regimens in ROC patients was randomly split into a “learning dataset” and a “validation dataset”. A parametric survival model was developed to associate longitudinal modeled CA-125 changes (ΔCA125), predictive factors, and PFS. The predictive performance of the model was evaluated with simulations.ResultsThe PFS of 534 ROC patients were properly characterized by a parametric mathematical model. The modeled ΔCA125 from baseline to week 6 was a better predictor of PFS than the modeled fractional change in tumor size. Simulations confirmed the model's predictive performance.ConclusionsWe present the first parametric survival model quantifying the relationship between PFS and longitudinal CA-125 kinetics in treated ROC patients. The model enabled calculation of the increase in ΔCA125 required to observe a predetermined benefit in PFS to compare therapeutic strategies in populations. Therefore, ΔCA125 may be a predictive marker of the expected gain in PFS and an early predictive tool in drug development decisions.
