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. 2019 Jun;28(6):1076-1085.
doi: 10.1158/1055-9965.EPI-18-1120. Epub 2019 Apr 4.

Predicting Circulating CA125 Levels among Healthy Premenopausal Women

Naoko Sasamoto  1   2 , Ana Babic  2   3 , Bernard A Rosner  2   4 , Renée T Fortner  5 , Allison F Vitonis  6 , Hidemi Yamamoto  7 , Raina N Fichorova  2   7 , Anne Tjønneland  8 , Louise Hansen  8 , Kim Overvad  9 , Marina Kvaskoff  10   11 , Agnès Fournier  10   11 , Francesca Romana Mancini  10   11 , Heiner Boeing  12 , Antonia Trichopoulou  13   14 , Eleni Peppa  13 , Anna Karakatsani  13   15 , Domenico Palli  16 , Valeria Pala  17 , Amalia Mattiello  18 , Rosario Tumino  19 , Chiara C Grasso  20 , N Charlotte Onland-Moret  21 , Elisabete Weiderpass  22   23   24   25 , J Ramón Quirós  26 , Leila Lujan-Barroso  27 , Miguel Rodríguez-Barranco  28   29 , Sandra Colorado-Yohar  30   31 , Aurelio Barricarte  32   33 , Miren Dorronsoro  34 , Annika Idahl  35   36 , Eva Lundin  37 , Hanna Sartor  38   39 , Kay-Tee Khaw  40 , Timothy J Key  41 , David Muller  42 , Elio Riboli  43 , Marc J Gunter  43 , Laure Dossus  43 , Rudolf Kaaks  5 , Daniel W Cramer  6   2 , Shelley S Tworoger  44 , Kathryn L Terry  6   2
Affiliations

Predicting Circulating CA125 Levels among Healthy Premenopausal Women

Naoko Sasamoto et al. Cancer Epidemiol Biomarkers Prev. 2019 Jun.

Abstract

Background: Cancer antigen 125 (CA125) is the most promising ovarian cancer screening biomarker to date. Multiple studies reported CA125 levels vary by personal characteristics, which could inform personalized CA125 thresholds. However, this has not been well described in premenopausal women.

Methods: We evaluated predictors of CA125 levels among 815 premenopausal women from the New England Case Control Study (NEC). We developed linear and dichotomous (≥35 U/mL) CA125 prediction models and externally validated an abridged model restricting to available predictors among 473 premenopausal women in the European Prospective Investigation into Cancer and Nutrition Study (EPIC).

Results: The final linear CA125 prediction model included age, race, tubal ligation, endometriosis, menstrual phase at blood draw, and fibroids, which explained 7% of the total variance of CA125. The correlation between observed and predicted CA125 levels based on the abridged model (including age, race, and menstrual phase at blood draw) had similar correlation coefficients in NEC (r = 0.22) and in EPIC (r = 0.22). The dichotomous CA125 prediction model included age, tubal ligation, endometriosis, prior personal cancer diagnosis, family history of ovarian cancer, number of miscarriages, menstrual phase at blood draw, and smoking status with AUC of 0.83. The abridged dichotomous model (including age, number of miscarriages, menstrual phase at blood draw, and smoking status) showed similar AUCs in NEC (0.73) and in EPIC (0.78).

Conclusions: We identified a combination of factors associated with CA125 levels in premenopausal women.

Impact: Our model could be valuable in identifying healthy women likely to have elevated CA125 and consequently improve its specificity for ovarian cancer screening.

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Conflict of interest statement

Conflict of interest: The authors declare no potential conflicts of interest.

Figures

Figure 1.
Figure 1.. Study design of the development and validation of the CA125 prediction model using the New England Case Control Study (NEC) and European Prospective Investigation into Cancer and Nutrition Study (EPIC)
We developed the CA125 prediction models (linear and dichotomous) using the New England Case Control Study (NEC) and conducted external validation using the European Prospective Investigation into Cancer and Nutrition Study (EPIC).
Figure 2.
Figure 2.. Development and validation of linear CA125 prediction model in the New England Case Control Study (NEC) and European Prospective Investigation into Cancer and Nutrition Study (EPIC)
The predicted versus the observed log-transformed CA125 values were plotted and Pearson correlation coefficient (r) was calculated to assess the performance of the linear CA125 prediction model in the New England Case Control Study (NEC) and European Prospective Investigation into Cancer and Nutrition Study (EPIC). A, Linear CA125 prediction model performance in NEC. B, Abridged linear CA125 prediction model performance in NEC. C, Abridged linear CA125 prediction model performance in EPIC.
Figure 3.
Figure 3.. Development and validation of dichotomous CA125 prediction model in the New England Case Control Study (NEC) and European Prospective Investigation into Cancer and Nutrition Study (EPIC)
Receiver Operating Characteristic (ROC) curves were plotted and the Area Under the Curve (AUC) was calculated to assess the discriminatory performance of the dichotomous CA125 prediction model in the New England Case Control Study (NEC) and European Prospective Investigation into Cancer and Nutrition Study (EPIC). Dichotomous CA125 prediction model performance in NEC (solid line), abridged dichotomous CA125 prediction model performance in NEC (dashed line), abridged dichotomous CA125 prediction model performance in EPIC (dotted line).
See this image and copyright information in PMC

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