scholarly journals Phthalate Exposure and Breast Cancer Incidence: A Danish Nationwide Cohort Study

2019 ◽  
Vol 37 (21) ◽  
pp. 1800-1809 ◽  
Author(s):  
Thomas P. Ahern ◽  
Anne Broe ◽  
Timothy L. Lash ◽  
Deirdre P. Cronin-Fenton ◽  
Sinna Pilgaard Ulrichsen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Cancer Incidence ◽  
Dibutyl Phthalate ◽  
Cox Regression ◽  
Breast Cancer Incidence ◽  
Drug Products ◽  
Phthalate Exposure ◽  
Long Term Treatment ◽  
High Level

PURPOSE Phthalate exposure is ubiquitous and especially high among users of drug products formulated with phthalates. Some phthalates mimic estradiol and may promote breast cancer. Existing epidemiologic studies on this topic are small, mostly not prospective, and have given inconsistent results. We estimated associations between longitudinal phthalate exposures and breast cancer risk in a Danish nationwide cohort, using redeemed prescriptions for phthalate-containing drug products to measure exposure. METHODS We ascertained the phthalate content of drugs marketed in Denmark using an internal Danish Medicines Agency ingredient database. We enrolled a Danish nationwide cohort of 1.12 million women at risk for a first cancer diagnosis on January 1, 2005. By combining drug ingredient data with the Danish National Prescription registry, we characterized annual, cumulative phthalate exposure through redeemed prescriptions. We then fit multivariable Cox regression models to estimate associations between phthalate exposures and incident invasive breast carcinoma according to tumor estrogen receptor status. RESULTS Over 9.99 million woman-years of follow-up, most phthalate exposures were not associated with breast cancer incidence. High-level dibutyl phthalate exposure (≥ 10,000 cumulative mg) was associated with an approximately two-fold increase in the rate of estrogen receptor–positive breast cancer (hazard ratio, 1.9; 95% CI, 1.1 to 3.5), consistent with in vitro evidence for an estrogenic effect of this compound. Lower levels of dibutyl phthalate exposure were not associated with breast cancer incidence. CONCLUSION Our results suggest that women should avoid high-level exposure to dibutyl phthalate, such as through long-term treatment with pharmaceuticals formulated with dibutyl phthalate.

Neuronatin is a modifier of estrogen receptor-positive breast cancer incidence and outcome

2019 ◽  
Vol 177 (1) ◽  
pp. 77-91
Author(s):  
Cody Plasterer ◽  
Shirng-Wern Tsaih ◽  
Amy R. Peck ◽  
Inna Chervoneva ◽  
Caitlin O’Meara ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Cancer Incidence ◽  
Breast Cancer Incidence ◽  
Estrogen Receptor Positive ◽  
Positive Breast Cancer

Breast cancer incidence by estrogen receptor status in Denmark from 1996 to 2007

2012 ◽  
Vol 136 (2) ◽  
pp. 559-564 ◽  
Author(s):  
J. Bigaard ◽  
C. Stahlberg ◽  
M.-B. Jensen ◽  
M. Ewertz ◽  
N. Kroman
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Cancer Incidence ◽  
Estrogen Receptor Status ◽  
Breast Cancer Incidence ◽  
Receptor Status

scholarly journals Evaluating the prognostic performance of a polygenic risk score for breast cancer risk stratification

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Maria Olsen ◽  
Krista Fischer ◽  
Patrick M. Bossuyt ◽  
Els Goetghebeur
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Cox Regression ◽  
Breast Cancer Incidence ◽  
Independent Study ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Prognostic Performance

Abstract Background Polygenic risk scores (PRS) could potentially improve breast cancer screening recommendations. Before a PRS can be considered for implementation, it needs rigorous evaluation, using performance measures that can inform about its future clinical value. Objectives To evaluate the prognostic performance of a regression model with a previously developed, prevalence-based PRS and age as predictors for breast cancer incidence in women from the Estonian biobank (EstBB) cohort; to compare it to the performance of a model including age only. Methods We analyzed data on 30,312 women from the EstBB cohort. They entered the cohort between 2002 and 2011, were between 20 and 89 years, without a history of breast cancer, and with full 5-year follow-up by 2015. We examined PRS and other potential risk factors as possible predictors in Cox regression models for breast cancer incidence. With 10-fold cross-validation we estimated 3- and 5-year breast cancer incidence predicted by age alone and by PRS plus age, fitting models on 90% of the data. Calibration, discrimination, and reclassification were calculated on the left-out folds to express prognostic performance. Results A total of 101 (3.33‰) and 185 (6.1‰) incident breast cancers were observed within 3 and 5 years, respectively. For women in a defined screening age of 50–62 years, the ratio of observed vs PRS-age modelled 3-year incidence was 0.86 for women in the 75–85% PRS-group, 1.34 for the 85–95% PRS-group, and 1.41 for the top 5% PRS-group. For 5-year incidence, this was respectively 0.94, 1.15, and 1.08. Yet the number of breast cancer events was relatively low in each PRS-subgroup. For all women, the model’s AUC was 0.720 (95% CI: 0.675–0.765) for 3-year and 0.704 (95% CI: 0.670–0.737) for 5-year follow-up, respectively, just 0.022 and 0.023 higher than for the model with age alone. Using a 1% risk prediction threshold, the 3-year NRI for the PRS-age model was 0.09, and 0.05 for 5 years. Conclusion The model including PRS had modest incremental performance over one based on age only. A larger, independent study is needed to assess whether and how the PRS can meaningfully contribute to age, for developing more efficient screening strategies.

scholarly journals Foods, macronutrients and breast cancer risk in postmenopausal women: a large UK cohort

2018 ◽  
Vol 48 (2) ◽  
pp. 489-500 ◽  
Author(s):  
Timothy J Key ◽  
Angela Balkwill ◽  
Kathryn E Bradbury ◽  
Gillian K Reeves ◽  
Ai Seon Kuan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Multiple Testing ◽  
Alcohol Intake ◽  
Cox Regression ◽  
Estrogen Receptor Status ◽  
Breast Cancer Incidence ◽  
Receptor Status ◽  
Validated Questionnaire ◽  
Increased Risk

Abstract Background The role of diet in breast cancer aetiology is unclear; recent studies have suggested associations may differ by estrogen receptor status. Methods Baseline diet was assessed in 2000–04 using a validated questionnaire in 691 571 postmenopausal UK women without previous cancer, who had not changed their diet recently. They were followed by record linkage to national cancer and death databases. Cox regression yielded adjusted relative risks for breast cancer for 10 food items and eight macronutrients, subdivided mostly into five categories of baseline intake. Trends in risk across the baseline categories were calculated, assigning re-measured intakes to allow for measurement error and changes in intake over time; P-values allowed for multiple testing. Results Women aged 59.9 (standard deviation (SD 4.9)) years at baseline were followed for 12 (SD 3) years; 29 005 were diagnosed with invasive breast cancer. Alcohol intake had the strongest association with breast cancer incidence: relative risk (RR) 1.08 [99% confidence interval (CI) 1.05–1.11] per 10 g/day higher intake, P = 5.8 × 10−14. There were inverse associations with fruit: RR 0.94 (99% CI 0.92–0.97) per 100 g/day higher intake, P = 1.1 × 10−6, and dietary fibre: RR 0.91 (99% CI 0.87–0.96) per 5 g/day increase, P = 1.1 × 10−4. Fruit and fibre intakes were correlated (ρ = 0.62) and were greater among women who were not overweight, so residual confounding cannot be excluded. There was no heterogeneity for any association by estrogen receptor status. Conclusions By far the strongest association was between alcohol intake and an increased risk of breast cancer. Of the other 17 intakes examined, higher intakes of fruit and fibre were associated with lower risks of breast cancer, but it is unclear whether or not these associations are causal.

scholarly journals Evaluating the Prognostic Performance of a Polygenic Risk Score for Breast Cancer Risk Stratification

2020 ◽  
Author(s):  
Maria Olsen ◽  
Krista Fischer ◽  
Patrick M. Bossuyt ◽  
Els Goetghebeur
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Cox Regression ◽  
Breast Cancer Incidence ◽  
Independent Study ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Breast Cancers ◽  
Polygenic Risk ◽  
Prognostic Performance

Abstract Background: Polygenic risk scores (PRS) could potentially improve breast cancer screening recommendations. We analyzed how well a recently developed prevalence-based breast cancer PRS (Läll et al., 2009) performs in expressing women’s future risk of incident breast cancer. Objectives: To evaluate the prognostic performance of models using PRS and age as predictors, vs age alone, for breast cancer incidence in women from the Estonian biobank (EstBB) cohort. Methods: We analyzed data on 30,312 women from the EstBB cohort. They entered the cohort between 2002 and 2011, were between 20-89 years, without history of breast cancer, and with full 5-year follow-up by 2015. We examined PRS and other potential risk factors as possible predictors in Cox regression models for breast cancer incidence. With 10-fold cross validation we estimated 3- and 5-year breast cancer incidence from age alone and PRS plus age, fitting models on 90% of the data. Calibration, discrimination, and reclassification then expressed prognostic performance on the left-out folds. Results: A total of 101 (3.33‰) and 185 (6.1‰) incident breast cancers were observed within 3 and 5 years, respectively. For women in the current Estonian screening age (50-62 years), the ratio of observed vs PRS-age modelled 3-year incidence was 0.86 for women in the 75-85% PRS-group, 1.34 for the 85-95% PRS-group, and 1.41 for the top 5% PRS-group. For 5-year incidence, this was respectively 0.94, 1.15, and 1.08. Yet, the number of breast cancer events were relatively low in each PRS-subgroup. The model’s AUC was 0.720 (95% CI: 0.675-0.765) for 3-year and 0.704 (95% CI: 0.670-0.737) for 5-year, respectively, just 0.022 and 0.023 higher than for the model with age alone. Using a 1% risk prediction threshold, the 3-year NRI for the PRS-age model was 0.09 and 0.05 for 5 years.Conclusion: The model including PRS had modest incremental performance. This suggests that the potential benefit of adding PRS to age for guiding screening likely affects a relatively small proportion of women. A larger, independent study is needed to assess whether and how the PRS can meaningfully contribute to developing more efficient screening strategies.

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