Development and validation of circulating CA125 prediction models in postmenopausal women

Abstract

BackgroundCancer 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.MethodsWe 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.ResultThe 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.ConclusionsThe 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.

Diagnostic Accuracy and Appropriate Cut Off Value of Risk of Malignancy Index in Preoperative Discrimination Between Malignant and Benign Ovarian Tumors: Prospective Cross-sectional Study

“…among malignant cases 14.3% occurs in premenopausal patients and 80.6% cases occur in postmenopausal patients and it is comparable to previous study report (28,29). The mean age for benign tumor is 30±9yrs and the mean age for malignant tumor is 50.6±10.8yrs.…”

Characteristics of genomic mutations and signaling pathway alterations in thymic epithelial tumors

“…Perplexingly, the current study did not detect mutations in the GTF2I gene in thymoma or thymic carcinoma samples, which is possibly due to insufficient sample size. MUC16, a mucin expressed at high levels on the surface of epithelial ovarian tumor cells, exerts similar effects to MUC1, which binds or aggregates neutrophils and other cell types to provide antitumor immune protection (47,48). PD-L1 expression has been used as a tumor cell marker in a number of clinical trials and has been approved by FDA (the food and drug administration) (49).…”

Characteristics of Genomic Mutations and Signaling Pathway Alterations in Thymic Epithelial Tumors

“…MUC16, a mucin expressed at high levels on the surface of epithelial ovarian tumor cells, exerts effects similar to those of MUC1, which binds or aggregates neutrophils and other cell types to provide immune protection against tumors. [44,45] The expression of PD-L1 has been used as a tumor cell marker in a number of clinical trials and has been approved for this purpose. [46] It is thought that positive expression of PD-L1 in tumors is an indicator of patients who are more likely to respond to treatment.…”