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Development and validation of circulating CA125 prediction models in postmenopausal women.

Published version
Peer-reviewed

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Authors

Babic, Ana 
Rosner, Bernard A 
Fortner, Renée T 
Vitonis, Allison F 

Abstract

BACKGROUND: 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. METHODS: 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. RESULT: 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% of the total variance of CA125. The correlation between measured and predicted CA125 was comparable in PLCO testing dataset (r = 0.18) and external validation datasets (r = 0.14). The dichotomous CA125 prediction model included age, race, BMI, smoking status and duration, hysterectomy, time since menopause, and duration of HT with AUC of 0.64 in PLCO and 0.80 in validation dataset. CONCLUSIONS: 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.

Description

Keywords

CA125, Early detection, Ovarian cancer, Postmenopausal, Prediction model, Aged, CA-125 Antigen, Early Detection of Cancer, Female, Humans, Middle Aged, Models, Theoretical, Neoplasms, Postmenopause

Journal Title

J Ovarian Res

Conference Name

Journal ISSN

1757-2215
1757-2215

Volume Title

12

Publisher

Springer Science and Business Media LLC
Sponsorship
National Cancer Institute (R01 CA193965, R01 CA 158119, R35 CA197605, P01 CA087969)