Development and validation of circulating CA125 prediction models in postmenopausal women.
Naoko SasamotoAna BabicBernard A RosnerRenée T FortnerAllison F VitonisHidemi YamamotoRaina N FichorovaLinda J TitusAnne TjønnelandLouise HansenMarina KvaskoffAgnès FournierFrancesca Romana ManciniHeiner BoeingAntonia TrichopoulouEleni PeppaAnna KarakatsaniDomenico PalliSara GrioniAmalia MattielloRosario TuminoValentina FianoN Charlotte Onland-MoretElisabete WeiderpassInger T GramJ Ramón QuirósLeila Lujan-BarrosoMaria-Jose SánchezSandra Colorado-YoharAurelio BarricartePilar AmianoAnnika IdahlEva LundinHanna SartorKay-Tee KhawTimothy J KeyDavid MullerElio RiboliMarc GunterLaure DossusBritton TrabertNicolas WentzensenRudolf KaaksDaniel W CramerShelley S TworogerKathryn L TerryPublished in: Journal of ovarian research (2019)
The linear prediction model explained a small portion of the total variability of CA125, suggesting the need to identify novel predictors of CA125. The dichotomous prediction model showed moderate discriminatory performance which validated well in independent dataset. Our dichotomous model could be valuable in identifying healthy women who may have elevated CA125 levels, which may contribute to reducing false positive tests using CA125 as screening biomarker.