Physical activity during adolescence and early adulthood and breast cancer risk before age 40 years.

BACKGROUND: Breast cancer (BC) incidence is increasing in women under age 40 years, underscoring the need for research on BC risk factors for younger women. METHODS: We used data from an international family cohort (n=26,348) to examine whether recreational physical activity (RPA) during adolescence and early adulthood are associated with BC risk before age 40. The cohort includes 2,502 women diagnosed with BC before age 40, including 2,408 diagnosed before study enrollment (68% within 5 years of enrollment). Women reported their average hours-per-week of moderate and strenuous RPA during adolescence (12-17 years) and early adulthood (25-34 years), which were converted to total age-adjusted metabolic equivalents-per-week and categorized into quartiles. We conducted attained age analyses until age 40 (follow-up time began at age 18) using Cox proportional hazards regression models adjusted for study center, race and ethnicity, and education. RESULTS: Being in the highest versus lowest quartile of RPA during adolescence and early adulthood were respectively associated with 12% [HR (95% CI): 0.88 (0.78, 0.98)] and 16% [HR (95% CI): 0.84 (0.74, 0.95) lower BC risks before age 40. Being in the highest quartile of RPA during both adolescence and early adulthood (Pearson correlation=0.52) versus neither timepoint was associated with a 22% lower risk [HR (95% CI): 0.78 (0.68, 0.89)]. CONCLUSIONS: Findings suggest that RPA during adolescence and early adulthood may lower BC risk before age 40. IMPACT: Policies promoting physical activity during adolescence and early adulthood may be important for reducing the growing burden of breast cancer in younger women.

Plasma metabolomics profiles and breast cancer risk.

BACKGROUND: Breast cancer (BC) is the most common cancer in women and incidence rates are increasing; metabolomics may be a promising approach for identifying the drivers of the increasing trends that cannot be explained by changes in known BC risk factors. METHODS: We conducted a nested case-control study (median followup 6.3 years) within the New York site of the Breast Cancer Family Registry (BCFR) (n = 40 cases and 70 age-matched controls). We conducted a metabolome-wide association study using untargeted metabolomics coupling hydrophilic interaction liquid chromatography (HILIC) and C18 chromatography with high-resolution mass spectrometry (LC-HRMS) to identify BC-related metabolic features. RESULTS: We found eight metabolic features associated with BC risk. For the four metabolites negatively associated with risk, the adjusted odds ratios (ORs) ranged from 0.31 (95% confidence interval (CI): 0.14, 0.66) (L-Histidine) to 0.65 (95% CI: 0.43, 0.98) (N-Acetylgalactosamine), and for the four metabolites positively associated with risk, ORs ranged from 1.61 (95% CI: 1.04, 2.51, (m/z: 101.5813, RT: 90.4, 1,3-dibutyl-1-nitrosourea, a potential carcinogen)) to 2.20 (95% CI: 1.15, 4.23) (11-cis-Eicosenic acid). These results were no longer statistically significant after adjusting for multiple comparisons. Adding the BC-related metabolic features to a model, including age, the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk score improved the accuracy of BC prediction from an area under the curve (AUC) of 66% to 83%. CONCLUSIONS: If replicated in larger prospective cohorts, these findings offer promising new ways to identify exposures related to BC and improve BC risk prediction.

Pregnancy-Related Factors and Breast Cancer Risk for Women Across a Range of Familial Risk.

Importance: Few studies have investigated whether the associations between pregnancy-related factors and breast cancer (BC) risk differ by underlying BC susceptibility. Evidence regarding variation in BC risk is critical to understanding BC causes and for developing effective risk-based screening guidelines. Objective: To examine the association between pregnancy-related factors and BC risk, including modification by a of BC where scores are based on age and BC family history. Design, Setting, and Participants: This cohort study included participants from the prospective Family Study Cohort (ProF-SC), which includes the 6 sites of the Breast Cancer Family Registry (US, Canada, and Australia) and the Kathleen Cuningham Foundation Consortium (Australia). Analyses were performed in a cohort of women enrolled from 1992 to 2011 without any personal history of BC who were followed up through 2017 with a median (range) follow-up of 10 (1-23) years. Data were analyzed from March 1992 to March 2017. Exposures: Parity, number of full-term pregnancies (FTP), age at first FTP, years since last FTP, and breastfeeding. Main Outcomes and Measures: BC diagnoses were obtained through self-report or report by a first-degree relative and confirmed through pathology and data linkages. Cox proportional hazards regression models estimated hazard ratios (HR) and 95% CIs for each exposure, examining modification by PARS of BC. Differences were assessed by estrogen receptor (ER) subtype. Results: The study included 17 274 women (mean [SD] age, 46.7 [15.1] years; 791 African American or Black participants [4.6%], 1399 Hispanic or Latinx participants [8.2%], and 13 790 White participants [80.7%]) with 943 prospectively ascertained BC cases. Compared with nulliparous women, BC risk was higher after a recent pregnancy for those women with higher PARS (last FTP 0-5 years HR for interaction, 1.53; 95% CI, 1.13-2.07; P for interaction < .001). Associations between other exposures were limited to ER-negative disease. ER-negative BC was positively associated with increasing PARS and increasing years since last FTP (P for interaction < .001) with higher risk for recent pregnancy vs nulliparous women (last FTP 0-5 years HR for interaction, 1.54; 95% CI, 1.03-2.31). ER-negative BC was positively associated with increasing PARS and being aged 20 years or older vs less than 20 years at first FTP (P for interaction = .002) and inversely associated with multiparity vs nulliparity (P for interaction = .01). Conclusions and Relevance: In this cohort study of women with no prior BC diagnoses, associations between pregnancy-related factors and BC risk were modified by PARS, with greater associations observed for ER-negative BC.

Astrocytic LRP1 enables mitochondria transfer to neurons and mitigates brain ischemic stroke by suppressing ARF1 lactylation.

Low-density lipoprotein receptor-related protein-1 (LRP1) is an endocytic/signaling cell-surface receptor that regulates diverse cellular functions, including cell survival, differentiation, and proliferation. LRP1 has been previously implicated in the pathogenesis of neurodegenerative disorders, but there are inconsistencies in its functions. Therefore, whether and how LRP1 maintains brain homeostasis remains to be clarified. Here, we report that astrocytic LRP1 promotes astrocyte-to-neuron mitochondria transfer by reducing lactate production and ADP-ribosylation factor 1 (ARF1) lactylation. In astrocytes, LRP1 suppressed glucose uptake, glycolysis, and lactate production, leading to reduced lactylation of ARF1. Suppression of astrocytic LRP1 reduced mitochondria transfer into damaged neurons and worsened ischemia-reperfusion injury in a mouse model of ischemic stroke. Furthermore, we examined lactate levels in human patients with stroke. Cerebrospinal fluid (CSF) lactate was elevated in stroke patients and inversely correlated with astrocytic mitochondria. These findings reveal a protective role of LRP1 in brain ischemic stroke by enabling mitochondria-mediated astrocyte-neuron crosstalk.

Adherence to the 2020 American Cancer Society Guideline for Cancer Prevention and risk of breast cancer for women at increased familial and genetic risk in the Breast Cancer Family Registry: an evaluation of the weight, physical activity, and alcohol consumption recommendations.

PURPOSE: The American Cancer Society (ACS) published an updated Guideline for Cancer Prevention (ACS Guideline) in 2020. Research suggests that adherence to the 2012 ACS Guideline might lower breast cancer risk, but there is limited evidence that this applies to women at increased familial and genetic risk of breast cancer. METHODS: Using the Breast Cancer Family Registry (BCFR), a cohort enriched for increased familial and genetic risk of breast cancer, we examined adherence to three 2020 ACS Guideline recommendations (weight management (body mass index), physical activity, and alcohol consumption) with breast cancer risk in 9615 women. We used Cox proportional hazard regression modeling to calculate hazard ratios (HRs) and 95% confidence intervals (CI) overall and stratified by BRCA1 and BRCA2 pathogenic variant status, family history of breast cancer, menopausal status, and estrogen receptor-positive (ER +) breast cancer. RESULTS: We observed 618 incident invasive or in situ breast cancers over a median 12.9 years. Compared with being adherent to none (n = 55 cancers), being adherent to any ACS recommendation (n = 563 cancers) was associated with a 27% lower breast cancer risk (HR = 0.73, 95% CI: 0.55-0.97). This was evident for women with a first-degree family history of breast cancer (HR = 0.68, 95% CI: 0.50-0.93), women without BRCA1 or BRCA2 pathogenic variants (HR = 0.71, 95% CI: 0.53-0.95), postmenopausal women (HR = 0.63, 95% CI: 0.44-0.89), and for risk of ER+ breast cancer (HR = 0.63, 95% CI: 0.40-0.98). DISCUSSION: Adherence to the 2020 ACS Guideline recommendations for BMI, physical activity, and alcohol consumption could reduce breast cancer risk for postmenopausal women and women at increased familial risk.

Recreational Physical Activity and Outcomes After Breast Cancer in Women at High Familial Risk.

Background: Recreational physical activity (RPA) is associated with improved survival after breast cancer (BC) in average-risk women, but evidence is limited for women who are at increased familial risk because of a BC family history or BRCA1 and BRCA2 pathogenic variants (BRCA1/2 PVs). Methods: We estimated associations of RPA (self-reported average hours per week within 3 years of BC diagnosis) with all-cause mortality and second BC events (recurrence or new primary) after first invasive BC in women in the Prospective Family Study Cohort (n = 4610, diagnosed 1993-2011, aged 22-79 years at diagnosis). We fitted Cox proportional hazards regression models adjusted for age at diagnosis, demographics, and lifestyle factors. We tested for multiplicative interactions (Wald test statistic for cross-product terms) and additive interactions (relative excess risk due to interaction) by age at diagnosis, body mass index, estrogen receptor status, stage at diagnosis, BRCA1/2 PVs, and familial risk score estimated from multigenerational pedigree data. Statistical tests were 2-sided. Results: We observed 1212 deaths and 473 second BC events over a median follow-up from study enrollment of 11.0 and 10.5 years, respectively. After adjusting for covariates, RPA (any vs none) was associated with lower all-cause mortality of 16.1% (95% confidence interval [CI] = 2.4% to 27.9%) overall, 11.8% (95% CI = -3.6% to 24.9%) in women without BRCA1/2 PVs, and 47.5% (95% CI = 17.4% to 66.6%) in women with BRCA1/2 PVs (RPA*BRCA1/2 multiplicative interaction P = .005; relative excess risk due to interaction = 0.87, 95% CI = 0.01 to 1.74). RPA was not associated with risk of second BC events. Conclusion: Findings support that RPA is associated with lower all-cause mortality in women with BC, particularly in women with BRCA1/2 PVs.

Nucleo-cytoplasmic RNA distribution responsible for maintaining neuroinflammatory microenvironment.

Subcellular localization of transcripts is highly associated with regulation of gene expression, synthesis of protein, and also the development of the human brain cortex. Although many mechanisms are prevalent in the occurrence of neuroinflammation, the mechanisms based on differences in subcellular localization of transcripts have not been explored. To characterize the dynamic profile of nuclear and cytoplasmic transcripts during the progress of haemorrhage-induced neuroinflammation, we isolated nucleo-cytoplasmic RNA fractions of oxyhaemoglobin (oxy-Hb) treated microglia cells and sequenced both fractions. We discovered that cytoplasmic retained genes were the major forces to maintain the neuroinflammatory microenvironment with 10 hub genes and 40 conserved genes were identified. Moreover, antisense RNA Gm44096 and lincRNA Gm47270, which co-expressed with a crowd of inflammatory genes in the cytoplasm, were discovered as regulatory strategies for sustaining the neuroinflammatory microenvironment. Thus, our study provides a new perspective on understanding haemorrhage-induced neuroinflammation and also reveals a mechanism of lncRNA responsible for maintaining the neuroinflammatory microenvironment.

Ponesimod protects against neuronal death by suppressing the activation of A1 astrocytes in early brain injury after experimental subarachnoid hemorrhage.

As an important initiator and responder of brain inflammation in the central nervous system (CNS), astrocytes transform into two new reactive phenotypes with changed morphology, altered gene expression and secretion profiles, termed detrimental A1 and beneficial A2. Inflammatory events have been shown to occur during the phase of early brain injury (EBI) after subarachnoid hemorrhage (SAH). However, the phenotype transformation of astrocytes as well as its potential contribution to inflammatory status in the EBI of SAH has yet to be determined. In the present study, both in vivo and in vitro models of SAH were established, and the polarization of astrocytes after SAH was analyzed by RNA-seq, western blotting, and immunofluorescence staining. The effect of astrocytic phenotype transformation on neuroinflammation was examined by real-time quantitative PCR (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA). We demonstrated that astrocytes were transformed into A1 astrocytes and caused neuronal death through the release of pro-inflammatory factors in EBI after SAH. Importantly, Ponesimod, an S1PR1 specific modulator, exerted neuroprotective effects through the prevention of astrocytic polarization to the A1 phenotype as proved by immunofluorescence, neurological tests, and TUNEL study. We also revealed the role of Ponesimod in modulating astrocytic response was mediated by the signal transducer and activator of transcription 3 (STAT3) signaling. Our study suggested that Ponesimod may be a promising therapeutic target for the treatment of brain injury following SAH.

Comparing 5-Year and Lifetime Risks of Breast Cancer using the Prospective Family Study Cohort.

BACKGROUND: Clinical guidelines often use predicted lifetime risk from birth to define criteria for making decisions regarding breast cancer screening rather than thresholds based on absolute 5-year risk from current age. METHODS: We used the Prospective Family Cohort Study of 14 657 women without breast cancer at baseline in which, during a median follow-up of 10 years, 482 women were diagnosed with invasive breast cancer. We examined the performances of the International Breast Cancer Intervention Study (IBIS) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk models when using the alternative thresholds by comparing predictions based on 5-year risk with those based on lifetime risk from birth and remaining lifetime risk. All statistical tests were 2-sided. RESULTS: Using IBIS, the areas under the receiver-operating characteristic curves were 0.66 (95% confidence interval = 0.63 to 0.68) and 0.56 (95% confidence interval = 0.54 to 0.59) for 5-year and lifetime risks, respectively (Pdiff < .001). For equivalent sensitivities, the 5-year incidence almost always had higher specificities than lifetime risk from birth. For women aged 20-39 years, 5-year risk performed better than lifetime risk from birth. For women aged 40 years or older, receiver-operating characteristic curves were similar for 5-year and lifetime IBIS risk from birth. Classifications based on remaining lifetime risk were inferior to 5-year risk estimates. Results were similar using BOADICEA. CONCLUSIONS: Our analysis shows that risk stratification using clinical models will likely be more accurate when based on predicted 5-year risk compared with risks based on predicted lifetime and remaining lifetime, particularly for women aged 20-39 years.

Biglycan regulates neuroinflammation by promoting M1 microglial activation in early brain injury after experimental subarachnoid hemorrhage.

Neuroinflammation can be caused by various factors in early brain injury after subarachnoid hemorrhage (SAH). One of the most important features of this process is M1 microglial activation. In turn, the TLR4/NF-κB pathway plays an essential role in activating M1 phenotypic microglia. Biglycan, a small leucine-rich proteoglycan, functions as an endogenous ligand of TLR4 and TLR2 in macrophages. However, the underlying mechanisms associated with microglial activation in stroke pathogenesis are poorly understood. Here, we aimed to identify the role of biglycan in neuroinflammation following SAH. In our study, SAH was induced by endovascular perforation in young male C57BL/6J mice. Lentiviral vector was administered intracerebroventricularly to knock down Biglycan. Post-SAH assessments included neurobehavioral tests, immunofluorescence, western blot, qRT-PCR, Co-IP, flow cytometry, and ELISA. The biglycan level was markedly elevated following SAH in vivo. Of particularly note, knockdown of biglycan significantly improved neurological outcomes. TLR4 was bound with soluble biglycan in vitro. In addition, biglycan down-regulation suppressed the expression of phosphorylated-NF-κB p65 (p-NF-κB) and inducible nitric oxide synthase (iNOS), as well as the cytokine (TNF-α, IL-1ß, and IL-6) production in vivo and in vitro. Moreover, we detected a decreased expression of CD16/32 and CD86, M1 markers when biglycan was inhibited in vitro. Our work suggests that biglycan can induce neuroinflammation by promoting M1 microglial activation at least in part through TLR4/NF-κB signaling pathway after experimental SAH. Targeting biglycan may be a promising strategy for the clinical management of SAH.

Recreational Physical Activity Is Associated with Reduced Breast Cancer Risk in Adult Women at High Risk for Breast Cancer: A Cohort Study of Women Selected for Familial and Genetic Risk.

Although physical activity is associated with lower breast cancer risk for average-risk women, it is not known if this association applies to women at high familial/genetic risk. We examined the association of recreational physical activity (self-reported by questionnaire) with breast cancer risk using the Prospective Family Study Cohort, which is enriched with women who have a breast cancer family history (N = 15,550). We examined associations of adult and adolescent recreational physical activity (quintiles of age-adjusted total metabolic equivalents per week) with breast cancer risk using multivariable Cox proportional hazards regression, adjusted for demographics, lifestyle factors, and body mass index. We tested for multiplicative interactions of physical activity with predicted absolute breast cancer familial risk based on pedigree data and with BRCA1 and BRCA2 mutation status. Baseline recreational physical activity level in the highest four quintiles compared with the lowest quintile was associated with a 20% lower breast cancer risk (HR, 0.80; 95% confidence interval, 0.68-0.93). The association was not modified by familial risk or BRCA mutation status (P interactions >0.05). No overall association was found for adolescent recreational physical activity. Recreational physical activity in adulthood may lower breast cancer risk for women across the spectrum of familial risk. SIGNIFICANCE: These findings suggest that physical activity might reduce breast cancer risk by about 20% for women across the risk continuum, including women at higher-than-average risk due to their family history or genetic susceptibility.See related commentary by Niehoff et al., p. 23.

Considerations When Using Breast Cancer Risk Models for Women with Negative BRCA1/BRCA2 Mutation Results.

The performance of breast cancer risk models for women with a family history but negative BRCA1 and/or BRCA2 mutation test results is uncertain. We calculated the cumulative 10-year invasive breast cancer risk at cohort entry for 14 657 unaffected women (96.1% had an affected relative) not known to carry BRCA1 or BRCA2 mutations at baseline using three pedigree-based models (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, BRCAPRO, and International Breast Cancer Intervention Study). During follow-up, 482 women were diagnosed with invasive breast cancer. Mutation testing was conducted independent of incident cancers. All models underpredicted risk by 26.3%-56.7% for women who tested negative but whose relatives had not been tested (n = 1363; 63 breast cancers). Although replication studies with larger sample sizes are needed, until these models are recalibrated for women who test negative and have no relatives tested, caution should be used when considering changing the breast cancer risk management intensity of such women based on risk estimates from these models.

Accuracy of Risk Estimates from the iPrevent Breast Cancer Risk Assessment and Management Tool.

BACKGROUND: iPrevent is an online breast cancer (BC) risk management decision support tool. It uses an internal switching algorithm, based on a woman's risk factor data, to estimate her absolute BC risk using either the International Breast Cancer Intervention Study (IBIS) version 7.02, or Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm version 3 models, and then provides tailored risk management information. This study assessed the accuracy of the 10-year risk estimates using prospective data. METHODS: iPrevent-assigned 10-year invasive BC risk was calculated for 15 732 women aged 20-70 years and without BC at recruitment to the Prospective Family Study Cohort. Calibration, the ratio of the expected (E) number of BCs to the observed (O) number and discriminatory accuracy were assessed. RESULTS: During the 10 years of follow-up, 619 women (3.9%) developed BC compared with 702 expected (E/O = 1.13; 95% confidence interval [CI] =1.05 to 1.23). For women younger than 50 years, 50 years and older, and BRCA1/2-mutation carriers and noncarriers, E/O was 1.04 (95% CI = 0.93 to 1.16), 1.24 (95% CI = 1.11 to 1.39), 1.13 (95% CI = 0.96 to 1.34), and 1.13 (95% CI = 1.04 to 1.24), respectively. The C-statistic was 0.70 (95% CI = 0.68 to 0.73) overall and 0.74 (95% CI = 0.71 to 0.77), 0.63 (95% CI = 0.59 to 0.66), 0.59 (95% CI = 0.53 to 0.64), and 0.65 (95% CI = 0.63 to 0.68), respectively, for the subgroups above. Applying the newer IBIS version 8.0b in the iPrevent switching algorithm improved calibration overall (E/O = 1.06, 95% CI = 0.98 to 1.15) and in all subgroups, without changing discriminatory accuracy. CONCLUSIONS: For 10-year BC risk, iPrevent had good discriminatory accuracy overall and was well calibrated for women aged younger than 50 years. Calibration may be improved in the future by incorporating IBIS version 8.0b.

Alcohol consumption, cigarette smoking, and familial breast cancer risk: findings from the Prospective Family Study Cohort (ProF-SC).

BACKGROUND: Alcohol consumption and cigarette smoking are associated with an increased risk of breast cancer (BC), but it is unclear whether these associations vary by a woman's familial BC risk. METHODS: Using the Prospective Family Study Cohort, we evaluated associations between alcohol consumption, cigarette smoking, and BC risk. We used multivariable Cox proportional hazard models to estimate hazard ratios (HR) and 95% confidence intervals (CI). We examined whether associations were modified by familial risk profile (FRP), defined as the 1-year incidence of BC predicted by Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), a pedigree-based algorithm. RESULTS: We observed 1009 incident BC cases in 17,435 women during a median follow-up of 10.4 years. We found no overall association of smoking or alcohol consumption with BC risk (current smokers compared with never smokers HR 1.02, 95% CI 0.85-1.23; consuming ≥ 7 drinks/week compared with non-regular drinkers HR 1.10, 95% CI 0.92-1.32), but we did observe differences in associations based on FRP and by estrogen receptor (ER) status. Women with lower FRP had an increased risk of ER-positive BC associated with consuming ≥ 7 drinks/week (compared to non-regular drinkers), whereas there was no association for women with higher FRP. For example, women at the 10th percentile of FRP (5-year BOADICEA = 0.15%) had an estimated HR of 1.46 (95% CI 1.07-1.99), whereas there was no association for women at the 90th percentile (5-year BOADICEA = 4.2%) (HR 1.07, 95% CI 0.80-1.44). While the associations with smoking were not modified by FRP, we observed a positive multiplicative interaction by FRP (pinteraction = 0.01) for smoking status in women who also consumed alcohol, but not in women who were non-regular drinkers. CONCLUSIONS: Moderate alcohol intake was associated with increased BC risk, particularly for women with ER-positive BC, but only for those at lower predicted familial BC risk (5-year BOADICEA < 1.25). For women with a high FRP (5-year BOADICEA ≥ 6.5%) who also consumed alcohol, being a current smoker was associated with increased BC risk.

Regular use of aspirin and other non-steroidal anti-inflammatory drugs and breast cancer risk for women at familial or genetic risk: a cohort study.

BACKGROUND: The use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been associated with reduced breast cancer risk, but it is not known if this association extends to women at familial or genetic risk. We examined the association between regular NSAID use and breast cancer risk using a large cohort of women selected for breast cancer family history, including 1054 BRCA1 or BRCA2 mutation carriers. METHODS: We analyzed a prospective cohort (N = 5606) and a larger combined, retrospective and prospective, cohort (N = 8233) of women who were aged 18 to 79 years, enrolled before June 30, 2011, with follow-up questionnaire data on medication history. The prospective cohort was further restricted to women without breast cancer when medication history was asked by questionnaire. Women were recruited from seven study centers in the United States, Canada, and Australia. Associations were estimated using multivariable Cox proportional hazards regression models adjusted for demographics, lifestyle factors, family history, and other medication use. Women were classified as regular or non-regular users of aspirin, COX-2 inhibitors, ibuprofen and other NSAIDs, and acetaminophen (control) based on self-report at follow-up of ever using the medication for at least twice a week for ≥1 month prior to breast cancer diagnosis. The main outcome was incident invasive breast cancer, based on self- or relative-report (81% confirmed pathologically). RESULTS: From fully adjusted analyses, regular aspirin use was associated with a 39% and 37% reduced risk of breast cancer in the prospective (HR = 0.61; 95% CI = 0.33-1.14) and combined cohorts (HR = 0.63; 95% CI = 0.57-0.71), respectively. Regular use of COX-2 inhibitors was associated with a 61% and 71% reduced risk of breast cancer (prospective HR = 0.39; 95% CI = 0.15-0.97; combined HR = 0.29; 95% CI = 0.23-0.38). Other NSAIDs and acetaminophen were not associated with breast cancer risk in either cohort. Associations were not modified by familial risk, and consistent patterns were found by BRCA1 and BRCA2 carrier status, estrogen receptor status, and attained age. CONCLUSION: Regular use of aspirin and COX-2 inhibitors might reduce breast cancer risk for women at familial or genetic risk.

10-year performance of four models of breast cancer risk: a validation study.

BACKGROUND: Independent validation is essential to justify use of models of breast cancer risk prediction and inform decisions about prevention options and screening. Few independent validations had been done using cohorts for common breast cancer risk prediction models, and those that have been done had small sample sizes and short follow-up periods, and used earlier versions of the prediction tools. We aimed to validate the relative performance of four commonly used models of breast cancer risk and assess the effect of limited data input on each one's performance. METHODS: In this validation study, we used the Breast Cancer Prospective Family Study Cohort (ProF-SC), which includes 18 856 women from Australia, Canada, and the USA who did not have breast cancer at recruitment, between March 17, 1992, and June 29, 2011. We selected women from the cohort who were 20-70 years old and had no previous history of bilateral prophylactic mastectomy or ovarian cancer, at least 2 months of follow-up data, and information available about family history of breast cancer. We used this selected cohort to calculate 10-year risk scores and compare four models of breast cancer risk prediction: the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm model (BOADICEA), BRCAPRO, the Breast Cancer Risk Assessment Tool (BCRAT), and the International Breast Cancer Intervention Study model (IBIS). We compared model calibration based on the ratio of the expected number of breast cancer cases to the observed number of breast cancer cases in the cohort, and on the basis of their discriminatory ability to separate those who will and will not have breast cancer diagnosed within 10 years as measured with the concordance statistic (C-statistic). We did subgroup analyses to compare the performance of the models at 10 years in BRCA1 or BRCA2 mutation carriers (ie, BRCA-positive women), tested non-carriers and untested participants (ie, BRCA-negative women), and participants younger than 50 years at recruitment. We also assessed the effect that limited data input (eg, restriction of the amount of family history and non-genetic information included) had on the models' performance. FINDINGS: After median follow-up of 11·1 years (IQR 6·0-14·4), 619 (4%) of 15 732 women selected from the ProF-SC cohort study were prospectively diagnosed with breast cancer after recruitment, of whom 519 (84%) had histologically confirmed disease. BOADICEA and IBIS were well calibrated in the overall validation cohort, whereas BRCAPRO and BCRAT underpredicted risk (ratio of expected cases to observed cases 1·05 [95% CI 0·97-1·14] for BOADICEA, 1·03 [0·96-1·12] for IBIS, 0·59 [0·55-0·64] for BRCAPRO, and 0·79 [0·73-0·85] for BRCAT). The estimated C-statistics for the complete validation cohort were 0·70 (95% CI 0·68-0·72) for BOADICEA, 0·71 (0·69-0·73) for IBIS, 0·68 (0·65-0·70) for BRCAPRO, and 0·60 (0·58-0·62) for BCRAT. In subgroup analyses by BRCA mutation status, the ratio of expected to observed cases for BRCA-negative women was 1·02 (95% CI 0·93-1·12) for BOADICEA, 1·00 (0·92-1·10) for IBIS, 0·53 (0·49-0·58) for BRCAPRO, and 0·97 (0·89-1·06) for BCRAT. For BRCA-positive participants, BOADICEA and IBIS were well calibrated, but BRCAPRO underpredicted risk (ratio of expected to observed cases 1·17 [95% CI 0·99-1·38] for BOADICEA, 1·14 [0·96-1·35] for IBIS, and 0·80 [0·68-0·95] for BRCAPRO). We noted similar patterns of calibration for women younger than 50 years at recruitment. Finally, BOADICEA and IBIS predictive scores were not appreciably affected by limiting input data to family history for first-degree and second-degree relatives. INTERPRETATION: Our results suggest that models that include multigenerational family history, such as BOADICEA and IBIS, have better ability to predict breast cancer risk, even for women at average or below-average risk of breast cancer. Although BOADICEA and IBIS performed similarly, further improvements in the accuracy of predictions could be possible with hybrid models that incorporate the polygenic risk component of BOADICEA and the non-family-history risk factors included in IBIS. FUNDING: US National Institutes of Health, National Cancer Institute, Breast Cancer Research Foundation, Australian National Health and Medical Research Council, Victorian Health Promotion Foundation, Victorian Breast Cancer Research Consortium, Cancer Australia, National Breast Cancer Foundation, Queensland Cancer Fund, Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and Cancer Foundation of Western Australia.

Benign breast disease increases breast cancer risk independent of underlying familial risk profile: Findings from a Prospective Family Study Cohort.

Benign breast disease (BBD) is an established breast cancer (BC) risk factor, but it is unclear whether the magnitude of the association applies to women at familial or genetic risk. This information is needed to improve BC risk assessment in clinical settings. Using the Prospective Family Study Cohort, we used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of BBD with BC risk. We also examined whether the association with BBD differed by underlying familial risk profile (FRP), calculated using absolute risk estimates from the Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) model. During 176,756 person-years of follow-up (median: 10.9 years, maximum: 23.7) of 17,154 women unaffected with BC at baseline, we observed 968 incident cases of BC. A total of 4,704 (27%) women reported a history of BBD diagnosis at baseline. A history of BBD was associated with a greater risk of BC: HR = 1.31 (95% CI: 1.14-1.50), and did not differ by underlying FRP, with HRs of 1.35 (95% CI: 1.11-1.65), 1.26 (95% CI: 1.00-1.60), and 1.40 (95% CI: 1.01-1.93), for categories of full-lifetime BOADICEA score <20%, 20 to <35%, ≥35%, respectively. There was no difference in the association for women with BRCA1 mutations (HR: 1.64; 95% CI: 1.04-2.58), women with BRCA2 mutations (HR: 1.34; 95% CI: 0.78-2.3) or for women without a known BRCA1 or BRCA2 mutation (HR: 1.31; 95% CI: 1.13-1.53) (pinteraction = 0.95). Women with a history of BBD have an increased risk of BC that is independent of, and multiplies, their underlying familial and genetic risk.

Age-specific breast cancer risk by body mass index and familial risk: prospective family study cohort (ProF-SC).

BACKGROUND: The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman's familial risk. METHODS: We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline. RESULTS: The strength and direction of the BMI risk association depended on baseline menopausal status (P < 0.001); after adjusting for menopausal status, the association did not depend on age at baseline (P = 0.6). In terms of absolute risk, the negative association with BMI for premenopausal women has a much smaller influence than the positive association with BMI for postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk. CONCLUSIONS: The greater a woman's familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. Given that age-adjusted BMI is correlated across adulthood, maintaining a healthy weight throughout adult life is particularly important for women with a family history of breast cancer.

Validation of the IBIS breast cancer risk evaluator for women with lobular carcinoma in-situ.

BACKGROUND: Management advice for women with lobular carcinoma in situ (LCIS) is hampered by the lack of accurate personalised risk estimates for subsequent invasive breast cancer (BC). Prospective validation of the only tool that estimates individual BC risk for a woman with LCIS, the International Breast Cancer Intervention Study Risk Evaluation Tool (IBIS-RET), is lacking. METHODS: Using population-based cancer registry data for 732 women with LCIS, the calibration and discrimination accuracy of IBIS-RET Version 7.2 were assessed. RESULTS: The mean observed 10-year risk of invasive BC was 14.1% (95% CI:11.3%-17.5%). IBIS-RET overestimated invasive BC risk (p = 0.0003) and demonstrated poor discriminatory accuracy (AUC 0.54, 95% CI: 0.48 - 0.62). CONCLUSIONS: Clinicians should understand that IBIS-RET Version 7.2 may overestimate 10-year invasive BC risk for Australian women with LCIS. The newer IBIS-RET Version 8.0, released September 2017, includes mammographic density and may perform better, but validation is needed.