TY  - JOUR
AU  - Sasamoto, Naoko
AU  - Babic, Ana
AU  - Rosner, Bernard A
AU  - Fortner, Renée T
AU  - Vitonis, Allison F
AU  - Yamamoto, Hidemi
AU  - Fichorova, Raina N
AU  - Titus, Linda J
AU  - Tjønneland, Anne
AU  - Hansen, Louise
AU  - Kvaskoff, Marina
AU  - Fournier, Agnès
AU  - Mancini, Francesca Romana
AU  - Boeing, Heiner
AU  - Trichopoulou, Antonia
AU  - Peppa, Eleni
AU  - Karakatsani, Anna
AU  - Palli, Domenico
AU  - Grioni, Sara
AU  - Mattiello, Amalia
AU  - Tumino, Rosario
AU  - Fiano, Valentina
AU  - Onland-Moret, N Charlotte
AU  - Weiderpass, Elisabete
AU  - Gram, Inger T
AU  - Quirós, J Ramón
AU  - Lujan-Barroso, Leila
AU  - Sánchez, Maria-Jose
AU  - Colorado-Yohar, Sandra
AU  - Barricarte, Aurelio
AU  - Amiano, Pilar
AU  - Idahl, Annika
AU  - Lundin, Eva
AU  - Sartor, Hanna
AU  - Khaw, Kay-Tee
AU  - Key, Timothy J
AU  - Muller, David
AU  - Riboli, Elio
AU  - Gunter, Marc
AU  - Dossus, Laure
AU  - Trabert, Britton
AU  - Wentzensen, Nicolas
AU  - Kaaks, Rudolf
AU  - Cramer, Daniel W
AU  - Tworoger, Shelley S
AU  - Terry, Kathryn L
TI  - Development and validation of circulating CA125 prediction models in postmenopausal women.
JO  - Journal of ovarian research
VL  - 12
IS  - 1
SN  - 1757-2215
CY  - London
PB  - BioMed Central
M1  - DKFZ-2019-02848
SP  - 116
PY  - 2019
AB  - Cancer Antigen 125 (CA125) is currently the best available ovarian cancer screening biomarker. However, CA125 has been limited by low sensitivity and specificity in part due to normal variation between individuals. Personal characteristics that influence CA125 could be used to improve its performance as screening biomarker.We developed and validated linear and dichotomous (≥35 U/mL) circulating CA125 prediction models in postmenopausal women without ovarian cancer who participated in one of five large population-based studies: Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, n = 26,981), European Prospective Investigation into Cancer and Nutrition (EPIC, n = 861), the Nurses' Health Studies (NHS/NHSII, n = 81), and the New England Case Control Study (NEC, n = 923). The prediction models were developed using stepwise regression in PLCO and validated in EPIC, NHS/NHSII and NEC.The linear CA125 prediction model, which included age, race, body mass index (BMI), smoking status and duration, parity, hysterectomy, age at menopause, and duration of hormone therapy (HT), explained 5
LB  - PUB:(DE-HGF)16
C6  - pmid:31771659
C2  - pmc:PMC6878636
DO  - DOI:10.1186/s13048-019-0591-4
UR  - https://inrepo02.dkfz.de/record/148282
ER  -