Correlates of circulating ovarian cancer early detection markers and their contribution to discrimination of early detection models: results from the EPIC cohort.

BACKGROUND: Ovarian cancer early detection markers CA125, CA15.3, HE4, and CA72.4 vary between healthy women, limiting their utility for screening. METHODS: We evaluated cross-sectional relationships between lifestyle and reproductive factors and these markers among controls (n = 1910) from a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC). Improvements in discrimination of prediction models adjusting for correlates of the markers were evaluated among postmenopausal women in the nested case-control study (n = 590 cases). Generalized linear models were used to calculate geometric means of CA125, CA15.3, and HE4. CA72.4 above vs. below limit of detection was evaluated using logistic regression. Early detection prediction was modeled using conditional logistic regression. RESULTS: CA125 concentrations were lower, and CA15.3 higher, in post- vs. premenopausal women (p ≤ 0.02). Among postmenopausal women, CA125 was higher among women with higher parity and older age at menopause (ptrend ≤ 0.02), but lower among women reporting oophorectomy, hysterectomy, ever use of estrogen-only hormone therapy, or current smoking (p < 0.01). CA15.3 concentrations were higher among heavier women and in former smokers (p ≤ 0.03). HE4 was higher with older age at blood collection and in current smokers, and inversely associated with OC use duration, parity, and older age at menopause (≤ 0.02). No associations were observed with CA72.4. Adjusting for correlates of the markers in prediction models did not improve the discrimination. CONCLUSIONS: This study provides insights into sources of variation in ovarian cancer early detection markers in healthy women and informs about the utility of individualizing marker cutpoints based on epidemiologic factors

Risk of high-grade serous ovarian cancer associated with pelvic inflammatory disease, parity and breast cancer

Background: Ovarian carcinoma is not a single disease, but rather a collection of subtypes with differing molecular properties and risk profiles. The most common of these, and the subject of this work, is high-grade serous ovarian carcinoma (HGSC). Methods: In this population-based study we identified a cohort of 441,382 women resident in Western Australia who had ever been admitted to hospital in the State. Of these, 454 were diagnosed with HGSC. We used Cox regression to derive hazard ratios (HRs) comparing the risk of disease in women who had each of a range of medical diagnoses and surgical procedures with women who did not. Results: We found an increased risk of HGSC associated with a diagnosis of pelvic inflammatory disease (PID) (HR 1.47, 95% CI 1.04–2.07) but not with a diagnosis of infertility or endometriosis with HRs of 1.12 (95% CI 0.73–1.71) and 0.82 (95% CI 0.55–1.22) respectively. A personal history of breast cancer was associated with a three-fold increase in the rate of HGSC. Increased parity was associated with a reduced risk of HGSC in women without a personal history of breast cancer (HR 0.57; 95% CI 0.44-0.73), but not in women with a personal history of breast cancer (HR 1.48; 95% CI 0.74–2.95). Conclusions: Our finding of an increased risk of HGSC associated with PID lends support to the hypothesis that inflammatory processes may be involved in the etiology of HGSC

Correlates of circulating ovarian cancer early detection markers and their contribution to discrimination of early detection models: results from the EPIC cohort

Background: Ovarian cancer early detection markers CA125, CA15.3, HE4, and CA72.4 vary between healthy women, limiting their utility for screening.Methods: We evaluated cross-sectional relationships between lifestyle and reproductive factors and these markers among controls (n = 1910) from a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC). Improvements in discrimination of prediction models adjusting for correlates of the markers were evaluated among postmenopausal women in the nested case-control study (n = 590 cases). Generalized linear models were used to calculate geometric means of CA125, CA15.3, and HE4. CA72.4 above vs. below limit of detection was evaluated using logistic regression. Early detection prediction was modeled using conditional logistic regression.Results: CA125 concentrations were lower, and CA15.3 higher, in post- vs. premenopausal women (p ≤ 0.02). Among postmenopausal women, CA125 was higher among women with higher parity and older age at menopause (ptrend ≤ 0.02), but lower among women reporting oophorectomy, hysterectomy, ever use of estrogen-only hormone therapy, or current smoking (p &lt; 0.01). CA15.3 concentrations were higher among heavier women and in former smokers (p ≤ 0.03). HE4 was higher with older age at blood collection and in current smokers, and inversely associated with OC use duration, parity, and older age at menopause (≤ 0.02). No associations were observed with CA72.4. Adjusting for correlates of the markers in prediction models did not improve the discrimination.Conclusions: This study provides insights into sources of variation in ovarian cancer early detection markers in healthy women and informs about the utility of individualizing marker cutpoints based on epidemiologic factors.</br

Leukocyte telomere length in relation to pancreatic cancer risk: a prospective study.

BACKGROUND: Several studies have examined leukocyte telomere length (LTL) as a possible predictor for cancer at various organ sites. The hypothesis originally motivating many of these studies was that shorter telomeres would be associated with an increase in cancer risk; the results of epidemiologic studies have been inconsistent, however, and suggested positive, negative, or null associations. Two studies have addressed the association of LTL in relation to pancreatic cancer risk and the results are contrasting. METHODS: We measured LTL in a prospective study of 331 pancreatic cancer cases and 331 controls in the context of the European Prospective Investigation into Cancer and Nutrition (EPIC). RESULTS: We observed that the mean LTL was higher in cases (0.59 ± 0.20) than in controls (0.57 ± 0.17), although this difference was not statistically significant (P = 0.07), and a basic logistic regression model showed no association of LTL with pancreas cancer risk. When adjusting for levels of HbA1c and C-peptide, however, there was a weakly positive association between longer LTL and pancreatic cancer risk [OR, 1.13; 95% confidence interval (CI), 1.01-1.27]. Additional analyses by cubic spline regression suggested a possible nonlinear relationship between LTL and pancreatic cancer risk (P = 0.022), with a statistically nonsignificant increase in risk at very low LTL, as well as a significant increase at high LTL. CONCLUSION: Taken together, the results from our study do not support LTL as a uniform and strong predictor of pancreatic cancer. IMPACT: The results of this article can provide insights into telomere dynamics and highlight the complex relationship between LTL and pancreatic cancer risk

Correlates of circulating ovarian cancer early detection markers and their contribution to discrimination of early detection models: results from the EPIC cohort

Background: Ovarian cancer early detection markers CA125, CA15.3, HE4, and CA72.4 vary between healthy women, limiting their utility for screening. Methods: We evaluated cross-sectional relationships between lifestyle and reproductive factors and these markers among controls (n = 1910) from a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC). Improvements in discrimination of prediction models adjusting for correlates of the markers were evaluated among postmenopausal women in the nested case-control study (n = 590 cases). Generalized linear models were used to calculate geometric means of CA125, CA15.3, and HE4. CA72.4 above vs. below limit of detection was evaluated using logistic regression. Early detection prediction was modeled using conditional logistic regression. Results: CA125 concentrations were lower, and CA15.3 higher, in post- vs. premenopausal women (p ≤ 0.02). Among postmenopausal women, CA125 was higher among women with higher parity and older age at menopause (ptrend ≤ 0.02), but lower among women reporting oophorectomy, hysterectomy, ever use of estrogen-only hormone therapy, or current smoking (p &lt; 0.01). CA15.3 concentrations were higher among heavier women and in former smokers (p ≤ 0.03). HE4 was higher with older age at blood collection and in current smokers, and inversely associated with OC use duration, parity, and older age at menopause (≤ 0.02). No associations were observed with CA72.4. Adjusting for correlates of the markers in prediction models did not improve the discrimination. Conclusions: This study provides insights into sources of variation in ovarian cancer early detection markers in healthy women and informs about the utility of individualizing marker cutpoints based on epidemiologic factors. © 2017 The Author(s)

Nutrient-wide association study of 57 foods/nutrients and epithelial ovarian cancer in the European Prospective Investigation into Cancer and Nutrition study and the Netherlands Cohort Study

Background: Studies of the role of dietary factors in epithelial ovarian cancer (EOC) development have been limited, and no specific dietary factors have been consistently associated with EOC risk. Objective: We used a nutrient-wide association study approach to systematically test the association between dietary factors and invasive EOC risk while accounting for multiple hypothesis testing by using the false discovery rate and evaluated the findings in an independent cohort. Design: We assessed dietary intake amounts of 28 foods/food groups and 29 nutrients estimated by using dietary questionnaires in the EPIC (European Prospective Investigation into Cancer and Nutrition) study (n = 1095 cases). We selected 4 foods/nutrients that were statistically significantly associated with EOC risk when comparing the extreme quartiles of intake in the EPIC study (false discovery rate = 0.43) and evaluated these factors in the NLCS (Netherlands Cohort Study; n = 383 cases). Cox regression models were used to estimate HRs and 95% CIs. Results: None of the 4 dietary factors that were associated with EOC risk in the EPIC study (cholesterol, polyunsaturated and saturated fat, and bananas) were statistically significantly associated with EOC risk in the NLCS; however, in meta-analysis of the EPIC study and the NLCS, we observed a higher risk of EOC with a high than with a low intake of saturated fat (quartile 4 compared with quartile 1; overall HR: 1.21; 95% CI: 1.04, 1.41). Conclusion: In the meta-analysis of both studies, there was a higher risk of EOC with a high than with a low intake of saturated fat