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.

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 Polygenic risk, susceptibility genes, and breast cancer over the life course

2020 ◽  
Author(s):  
Nina Mars ◽  
Elisabeth Widén ◽  
Sini Kerminen ◽  
Tuomo Meretoja ◽  
Matti Pirinen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
Clinical Decision Making ◽  
Breast Cancer Mortality ◽  
Breast Cancer Incidence ◽  
Positive Family History ◽  
Risk Scores ◽  
Limited Information ◽  
Polygenic Risk ◽  
Fold Enrichment

ABSTRACTPolygenic risk scores (PRS) for breast cancer have potential to improve risk prediction, but there is limited information on their clinical applicability. We set out to study how PRS could help in clinical decision making. Among 99,969 women in the FinnGen study with 6,879 breast cancer cases, the PRS was associated not only with breast cancer incidence but also with a range of breast cancer-related endpoints. Women with a breast cancer PRS above the 90th percentile had both higher breast cancer mortality (HR 2.40, 95%CI 1.82-3.17) and higher risk for non-localized disease at diagnosis (HR 2.94, 95%CI 2.63-3.28), compared to those with PRS <80th percentile. The PRS modified the breast cancer risk of two high-impact frameshift risk variants. Women with the c.1592delT variant in PALB2 (242-fold enrichment in Finland, 263 carriers) and an average PRS (20-80th percentile) had a lifetime risk of breast cancer at 58% (95%CI 50-66%), which increased to 85% (70-100%) with a high PRS (>90th percentile), and decreased to 27% (15-39%) with a low PRS (<20th percentile). Similarly, for c.1100delC in CHEK2 (3.7-fold enrichment; 1,543 carriers), the respective lifetime risks were 27% (95%CI 25-30%), 59% (52-67%), and 18% (13-22%). Among breast cancer cases, a PRS >90th percentile was associated with risk of contralateral breast cancer with HR 1.66 (95%CI 1.24-2.22). Finally, the PRS significantly refined the risk assessment of women with first-degree relatives diagnosed with breast cancer, i.e. the combination of high PRS (>90th percentile) and a positive family-history was associated with a 2.33-fold elevated risk (95%CI 1.57-3.46) compared to a positive family history alone. These findings demonstrate opportunities for a comprehensive way of assessing genetic risk in the general population, in breast cancer patients, and in unaffected family members.

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.

scholarly journals Polygenic risk score for the prediction of breast cancer is related to lesser terminal duct lobular unit involution of the breast

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Clara Bodelon ◽  
Hannah Oh ◽  
Andriy Derkach ◽  
Joshua N. Sampson ◽  
Brian L. Sprague ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Score ◽  
Polygenic Risk Score ◽  
Intermediate Step ◽  
Breast Cancers ◽  
Tissue Samples ◽  
Polygenic Risk ◽  
Age Related

Abstract Terminal duct lobular units (TDLUs) are the predominant anatomical structures where breast cancers originate. Having lesser degrees of age-related TDLU involution, measured as higher TDLUs counts or more epithelial TDLU substructures (acini), is related to increased breast cancer risk among women with benign breast disease (BBD). We evaluated whether a recently developed polygenic risk score (PRS) based on 313-common variants for breast cancer prediction is related to TDLU involution in the background, normal breast tissue, as this could provide mechanistic clues on the genetic predisposition to breast cancer. Among 1398 women without breast cancer, higher values of the PRS were significantly associated with higher TDLU counts (P = 0.004), but not with acini counts (P = 0.808), in histologically normal tissue samples from donors and diagnostic BBD biopsies. Mediation analysis indicated that TDLU counts may explain a modest proportion (≤10%) of the association of the 313-variant PRS with breast cancer risk. These findings suggest that TDLU involution might be an intermediate step in the association between common genetic variation and breast cancer risk.

scholarly journals Diabetes, Metformin, and Breast Cancer in Postmenopausal Women

2012 ◽  
Vol 30 (23) ◽  
pp. 2844-2852 ◽  
Author(s):  
Rowan T. Chlebowski ◽  
Anne McTiernan ◽  
Jean Wactawski-Wende ◽  
JoAnn E. Manson ◽  
Aaron K. Aragaki ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Postmenopausal Women ◽  
Cancer Incidence ◽  
Proportional Hazards ◽  
Breast Cancer Incidence ◽  
Cox Proportional Hazards ◽  
Diabetes Incidence ◽  
Breast Cancers ◽  
Cancer Risk Factors ◽  
Cancer Management

Purpose Emerging evidence suggests that metformin may reduce breast cancer incidence, but reports are mixed and few provide information on tumor characteristics. Therefore, we assessed associations among diabetes, metformin use, and breast cancer in postmenopausal women participating in Women's Health Initiative clinical trials. Patients and Methods In all, 68,019 postmenopausal women, including 3,401 with diabetes at study entry, were observed over a mean of 11.8 years with 3,273 invasive breast cancers diagnosed. Diabetes incidence status was collected throughout follow-up, with medication information collected at baseline and years 1, 3, 6, and 9. Breast cancers were confirmed by review of central medical records and pathology reports. Cox proportional hazards regression, adjusted for breast cancer risk factors, compared breast cancer incidence in women with diabetes who were metformin users or nonusers with breast cancer incidence in women without diabetes. Results Compared with that in women without diabetes, breast cancer incidence in women with diabetes differed by diabetes medication type (P = .04). Women with diabetes receiving medications other than metformin had a slightly higher incidence of breast cancer (hazard ratio [HR], 1.16; 95% CI, 0.93 to 1.45), and women with diabetes who were given metformin had lower breast cancer incidence (HR, 0.75; 95% CI, 0.57 to 0.99). The association was observed for cancers positive for both estrogen receptor and progesterone receptor and those that were negative for human epidermal growth factor receptor 2. Conclusion Metformin use in postmenopausal women with diabetes was associated with lower incidence of invasive breast cancer. These results can inform future studies evaluating metformin use in breast cancer management and prevention.

Qualitative age interactions (or effect modification) suggest divergent pathways for early-onset and late-onset breast cancers

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 21036-21036 ◽  
Author(s):  
W. F. Anderson ◽  
L. A. Brinton ◽  
B. Chen ◽  
S. S. Devesa
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Early Onset ◽  
Late Onset ◽  
Breast Cancer Incidence ◽  
Temporal Trends ◽  
Effect Modification ◽  
Low Grade ◽  
High Grade ◽  
Breast Cancers

21036 Background: Notwithstanding some recent declines, breast cancer incidence rates have risen for decades, though not equally for all age groups. We used the National Cancer Institute's SEER program to further explore the effect of aging upon breast cancer incidence. Materials and Methods: The SEER program collected data on n=494,543 in-situ + invasive female breast cancer cases, newly diagnosed during 1974–2003. Temporal trends by race, stage, and grade were stratified by age at diagnosis in decades: 20–29 to 80+ years. Results: We observed age interactions over time. For example, as the specification of grade improved from 1974–2003, temporal trends for high and low grade tumors varied with age. Among women ages <40 years, high grade lesions were more common than low grade tumors for all time periods. Among women ages 40+ years, high grade lesions were more common during the early years, and then rates crossed, after which low-grade tumors were more common than high grade lesions. Conclusion: Age at diagnosis was both a quantitative (non- crossover) and qualitative (crossover) effect modifier. The crossing of rates from high to low grade tumors among women ages 40+ years in the 1980s is consistent with more aggressive breast cancer screening, with mammography preferentially detecting low grade tumors among women targeted for screening, i.e., ages 40–80 years. Though once thought to be rare or artifactual, qualitative interactions or effect modification suggest etiologic heterogeneity in an otherwise homogeneous disease process. Indeed, if true, qualitative age interactions imply divergent pathways for early-onset and late-onset breast cancers. No significant financial relationships to disclose.

scholarly journals Effect of Changing Breast Cancer Incidence Rates on the Calibration of the Gail Model

2010 ◽  
Vol 28 (14) ◽  
pp. 2411-2417 ◽  
Author(s):  
Sara J. Schonfeld ◽  
David Pee ◽  
Robert T. Greenlee ◽  
Patricia Hartge ◽  
James V. Lacey ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Invasive Breast Cancer ◽  
Clinical Decision Making ◽  
Prediction Models ◽  
Breast Cancer Incidence ◽  
Incidence Rates ◽  
Breast Cancers ◽  
Gail Model ◽  
Cancer Incidence Rates

Purpose The Gail model combines relative risks (RRs) for five breast cancer risk factors with age-specific breast cancer incidence rates and competing mortality rates from the Surveillance, Epidemiology, and End Results (SEER) program from 1983 to 1987 to predict risk of invasive breast cancer over a given time period. Motivated by changes in breast cancer incidence during the 1990s, we evaluated the model's calibration in two recent cohorts. Methods We included white, postmenopausal women from the National Institutes of Health (NIH) –AARP Diet and Health Study (NIH-AARP, 1995 to 2003), and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO, 1993 to 2006). Calibration was assessed by comparing the number of breast cancers expected from the Gail model with that observed. We then evaluated calibration by using an updated model that combined Gail model RRs with 1995 to 2003 SEER invasive breast cancer incidence rates. Results Overall, the Gail model significantly underpredicted the number of invasive breast cancers in NIH-AARP, with an expected-to-observed ratio of 0.87 (95% CI, 0.85 to 0.89), and in PLCO, with an expected-to-observed ratio of 0.86 (95% CI, 0.82 to 0.90). The updated model was well-calibrated overall, with an expected-to-observed ratio of 1.03 (95% CI, 1.00 to 1.05) in NIH-AARP and an expected-to-observed ratio of 1.01 (95% CI: 0.97 to 1.06) in PLCO. Of women age 50 to 55 years at baseline, 13% to 14% had a projected Gail model 5-year risk lower than the recommended threshold of 1.66% for use of tamoxifen or raloxifene but ≥ 1.66% when using the updated model. The Gail model was well calibrated in PLCO when the prediction period was restricted to 2003 to 2006. Conclusion This study highlights that model calibration is important to ensure the usefulness of risk prediction models for clinical decision making.

scholarly journals Use of systemic glucocorticoids and risk of breast cancer in a prospective cohort of postmenopausal women

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Manon Cairat ◽  
Marie Al Rahmoun ◽  
Marc J. Gunter ◽  
Pierre-Etienne Heudel ◽  
Gianluca Severi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Postmenopausal Women ◽  
Invasive Breast Cancer ◽  
Cox Regression ◽  
Breast Cancer Incidence ◽  
Breast Cancers ◽  
Systemic Glucocorticoid ◽  
Systemic Glucocorticoids

Abstract Background Glucocorticoids could theoretically decrease breast cancer risk through their anti-inflammatory effects or increase risk through immunosuppression. However, epidemiological evidence is limited regarding the associations between glucocorticoid use and breast cancer risk. Methods We investigated the association between systemic glucocorticoid use and breast cancer incidence in the E3N cohort, which includes 98,995 women with information on various characteristics collected from repeated questionnaires complemented with drug reimbursement data available from 2004. Women with at least two reimbursements of systemic glucocorticoids in any previous 3-month period since January 1, 2004, were defined as exposed. We considered exposure as a time-varying parameter, and we used multivariable Cox regression models to estimate hazard ratios (HRs) of breast cancer. We performed a competing risk analysis using a cause-specific hazard approach to study the heterogeneity by tumour subtype/stage/grade. Results Among 62,512 postmenopausal women (median age at inclusion of 63 years old), 2864 developed breast cancer during a median follow-up of 9 years (between years 2004 and 2014). Compared with non-exposure, glucocorticoid exposure was not associated with overall breast cancer risk [HR = 0.94 (0.85–1.05)]; however, it was associated with a higher risk of in situ breast cancer and a lower risk of invasive breast cancer [HRinsitu = 1.34 (1.01–1.78); HRinvasive = 0.86 (0.76–0.97); Phomogeneity = 0.01]. Regarding the risk of invasive breast cancer, glucocorticoid exposure was inversely associated with oestrogen receptor (ER)-positive breast cancer [HRER+ = 0.82 (0.72–0.94); HRER− = 1.21 (0.88–1.66); Phomogeneity = 0.03]; it was also inversely associated with the risk of stage 1 or stage 2 tumours but positively associated with the risk of stage 3/4 breast cancers [HRstage1 = 0.87 (0.75–1.01); HRstage2 = 0.67 (0.52–0.86); HRstage3/4 = 1.49 (1.02–2.20); Phomogeneity = 0.01]. Conclusion This study suggests that the association between systemic glucocorticoid use and breast cancer risk may differ by tumour subtype and stage.

scholarly journals Characterization of Potential Driver Genes Involved in Human Breast Cancer in Maysan Province, Iraq

2021 ◽  
Author(s):  
Zainab Zamil gataa Allami ◽  
Maytham A Dragh
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Breast Cancer Incidence ◽  
Brca1 Gene ◽  
Receptor Expression ◽  
Breast Cancers ◽  
Driver Genes ◽  
Healthy Control ◽  
Hormone Receptor Expression ◽  
The Relationship

Abstract Background: Breast cancer is a heterogeneous disease regarding its morphology, invasive behaviour, metastatic capacity, hormone receptor expression and clinical outcome. There are many risk factors for breast cancer, including genetic factors that account for 25-30% of the incidence; from this percentage, only 15-30% of the heritable component of breast cancer is due to known familiar highly penetrating genes, and the others are sporadic.Methods: This study was the first to include amplified genes as PCR templates to determine the relationship between their polymorphism and breast cancer incidence using RAPD of amplified genes. The study was designed first to evaluate the association of ABCG2, ABCB1 and BRCA1 gene polymorphisms in addition to miRNA-152 and ER-a using the RAPD technique with breast cancer incidence in Maysan Province women and second to use those genes as indicators for breast cancer prediction and diagnosis. The study included 100 patients with breast cancer and 30 healthy control women, and then all samples were amplified by conventional PCR with specific F and R primers for ABCG2, ABCB1, BRCA1, ER-α, and miRNA-152 genes. Then, the best PCR product (20) was chosen as the template for the RAPD technique.Results: The results revealed that all RAPD primers showed polymorphisms with higher values and more specific bands in patient samples. Our study proved the relationship between genetic polymorphisms of breast cancer-related genes and a higher incidence of cancer.Conclusion: The current study recommends employing these results for the future prediction and diagnosis of breast cancers.

scholarly journals Breast Cancer beyond the Age of Mutation

Gerontology ◽  
2015 ◽  
Vol 62 (4) ◽  
pp. 434-442 ◽  
Author(s):  
Mark A. LaBarge ◽  
E. Lorena Mora-Blanco ◽  
Susan Samson ◽  
Masaru Miyano
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Breast Tissue ◽  
Breast Cancer Incidence ◽  
Epigenetic Changes ◽  
Breast Cancers ◽  
Age Related ◽  
Age Dependent ◽  
Tissue Changes ◽  
Cellular Phenotypes

Age is the greatest risk factor for breast cancer, but the reasons underlying this association are unclear. While there is undeniably a genetic component to all cancers, the accumulation of mutations with age is insufficient to explain the age-dependent increase in breast cancer incidence. In this viewpoint, we propose a multilevel framework to better understand the respective roles played by somatic mutation, microenvironment, and epigenetics making women more susceptible to breast cancer with age. The process of aging is associated with gradual breast tissue changes that not only corrupt the tumor-suppressive activity of normal tissue but also impose age-specific epigenetic changes that alter gene expression, thus reinforcing cellular phenotypes that are associated with a continuum of age-related tissue microenvironments. The evidence discussed here suggests that while the riddle of whether epigenetics drives microenvironmental changes, or whether changes in the microenvironment alter heritable cellular memory has not been solved, a path has been cleared enabling functional analysis leading to the prediction of key nodes in the network that link the microenvironment with the epigenome. The hypothesis that the accumulation of somatic mutations with age drives the age-related increase in breast cancer incidence, if correct, has a somewhat nihilistic conclusion, namely that cancers will be impossible to avoid. Alternatively, if microenvironment-driven epigenetic changes are the key to explaining susceptibility to age-related breast cancers, then there is hope that primary prevention is possible because epigenomes are relatively malleable.

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