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Multiple myeloma (MM) is the second most common hematological cancer and causes significant mortality and morbidity. Knowledge regarding modifiable risk factors for MM remains limited. This analysis of an Australian population-based case-control family study investigates whether smoking or alcohol consumption is associated with risk of MM and related diseases. Incident cases (

Nutritional epidemiology research using self-reported dietary intake is prone to measurement error. Objective methods are being explored to overcome this limitation.We aimed to examine 1) the association between plasma markers related to inflammation and derive marker scores for dietary patterns [Mediterranean dietary score (MDS), energy-adjusted Dietary Inflammatory Index (E-DIITM), Alternative Healthy Eating Index 2010 (AHEI)] and 2) the associations of these marker scores with mortality.Weighted marker scores were derived from the cross-sectional association between 30 plasma markers and each dietary score (assessed using food-frequency questionnaires) using linear regression for 770 participants in the Melbourne Collaborative Cohort Study (aged 50-82 y). Prospective associations between marker scores and mortality (n = 249 deaths) were assessed using Cox regression (median follow-up: 14.4 y).The MDS, E-DII, and AHEI were associated (P 0.05) with 9, 14, and 11 plasma markers, respectively. Healthier diets (higher MDS and AHEI, and lower anti-inflammatory, E-DII) were associated with lower concentrations of kynurenines, neopterin, IFN-γ, cytokines, and C-reactive protein. Five of 6 markers common to the 3 dietary scores were components of the kynurenine pathway. The 3 dietary-based marker scores were highly correlated (Spearman ρ: -0.74, -0.82, and 0.93). Inverse associations (for 1-SD increment) were observed with all-cause mortality for the MDS marker score (HR: 0.84; 95% CI: 0.72-0.98) and the AHEI marker score (HR: 0.76; 95% CI: 0.66-0.89), whereas a positive association was observed with the E-DII marker score (HR: 1.18; 95% CI: 1.01-1.39). The same magnitude of effect was not observed for the respective dietary patterns.Markers involved in inflammation-related processes are associated with dietary quality, including a substantial overlap between markers associated with the MDS, the E-DII, and the AHEI, especially kynurenines. Unfavorable marker scores, reflecting poorer-quality diets, were associated with increased mortality.

Background: Estimates of future burden of cancer attributable to current modifiable causal exposures can guide cancer prevention. We quantified future head and neck cancer burden in Australia attributable to individual and joint causal exposures, and assessed whether these burdens differ between population subgroups. Methods: We estimated the strength of the associations between exposures and head and neck cancer using adjusted proportional hazards models from pooled data from seven Australian cohorts (N = 367,058) linked to national cancer and death registries and estimated exposure prevalence from the 2017 to 2018 Australian National Health Survey. We calculated population attributable fractions (PAF) with 95% confidence intervals (CI), accounting for competing risk of death, and compared PAFs for population subgroups. Results: Contemporary levels of current and former smoking contribute 30.6% (95% CI, 22.7%–37.8%), alcohol consumption exceeding two standard drinks per day 12.9% (95% CI, 7.6%–17.9%), and these exposures jointly 38.5% (95% CI, 31.1%–45.0%) to the future head and neck cancer burden. Alcohol-attributable burden is triple and smoking-attributable burden is double for men compared with women. Smoking-attributable burden is also at least double for those consuming more than two alcoholic drinks daily or doing less than 150 minutes of moderate or 75 minutes of vigorous activity weekly, and for those aged under 65 years, unmarried, with low or intermediate educational attainment or lower socioeconomic status, compared with their counterparts. Conclusions: Two-fifths of head and neck cancers in Australia are preventable by investment in tobacco and alcohol control. Impact: Targeting men and other identified high-burden subgroups can help to reduce head and neck cancer burden disparities.

Background Family history of prostate cancer (PCa) is a well-known risk factor, and both common and rare genetic variants are associated with the disease. Objective To detect new genetic variants associated with PCa, capitalizing on the role of family history and more aggressive PCa. Design, setting, and participants A two-stage design was used. In stage one, whole-exome sequencing was used to identify potential risk alleles among affected men with a strong family history of disease or with more aggressive disease (491 cases and 429 controls). Aggressive disease was based on a sum of scores for Gleason score, node status, metastasis, tumor stage, prostate-specific antigen at diagnosis, systemic recurrence, and time to PCa death. Genes identified in stage one were screened in stage two using a custom-capture design in an independent set of 2917 cases and 1899 controls. Outcome measurements and statistical analysis Frequencies of genetic variants (singly or jointly in a gene) were compared between cases and controls. Results and limitations Eleven genes previously reported to be associated with PCa were detected (ATM, BRCA2, HOXB13, FAM111A, EMSY, HNF1B, KLK3, MSMB, PCAT1, PRSS3, and TERT), as well as an additional 10 novel genes (PABPC1, QK1, FAM114A1, MUC6, MYCBP2, RAPGEF4, RNASEH2B, ULK4, XPO7, and THAP3). Of these 10 novel genes, all but PABPC1 and ULK4 were primarily associated with the risk of aggressive PCa. Conclusions Our approach demonstrates the advantage of gene sequencing in the search for genetic variants associated with PCa and the benefits of sampling patients with a strong family history of disease or an aggressive form of disease. Patient summary Multiple genes are associated with prostate cancer (PCa) among men with a strong family history of this disease or among men with an aggressive form of PCa.

Background: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. Methods: We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values-8 as genome-wide significant, and p-values-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants.Results: None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values5. The strongest evidence was found for rs4674019 (p-value=2.27x10-7), which showed genome-wide significant interaction (p-value=3.8x10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. Conclusions: In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT–breast cancer risk association.

Mammograms contain information that predicts breast cancer risk. We developed two novel mammogram-based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). Their risk prediction when fitted together, and with an established measure of conventional mammographic density (Cumulus), is not known. We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen-detected cases and 1197 matched controls; and 354 younger-diagnosis cases and 944 controls frequency-matched for age at mammogram. We conducted conditional and unconditional logistic regression analyses of individually- and frequency-matched studies, respectively. We estimated measure-specific risk gradients as the change in odds per standard deviation of controls after adjusting for age and body mass index (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). For interval, screen-detected and younger-diagnosis cancer risks, the best fitting models (OPERAs [95% confidence intervals]) involved: Cumulus (1.81 [1.41-2.31]) and Cirrus (1.72 [1.38-2.14]); Cirrus (1.49 [1.32-1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27-1.68]), respectively. The AUCs were: 0.73 [0.68-0.77], 0.63 [0.60-0.66], and 0.72 [0.69-0.75], respectively. Combined, our new mammogram-based measures have twice the risk gradient for screen-detected and younger-diagnosis breast cancer (P ≤ 10-12 ), have at least the same discriminatory power as the current polygenic risk score, and are more correlated with causal factors than conventional mammographic density. Discovering more information about breast cancer risk from mammograms could help enable risk-based personalised breast screening.

This literature review provides an up-to-date overview of the evidence relating to the associations of leisure-time physical activity and sedentary behaviour with the risk of colorectal adenoma and cancer. A summary of possible biological mechanisms underpinning these associations is also presented. Leisure-time physical activity and sedentary behaviour are often conceptualised as independent risk factors for colorectal adenoma and cancer. Regular leisure-time physical activity is associated with a 20%–25% reduction in colorectal cancer risk and an estimated 16% reduction in colonic adenoma. The risk estimates are similar for males and females, and for proximal and distal colon cancers. In contrast, the evidence linking physical inactivity to rectal cancer is inconsistent. Epidemiological evidence suggests that television viewing time and occupational sitting are associated with a 54% and 24% increased risk of colon cancer, respectively. Prolonged TV viewing (a commonly measured type of sedentary behaviour) is associated with a 9–16% increased risk of colorectal adenoma, independent of leisure-time physical activity. There is convincing evidence that higher leisure-physical activity is associated with a lower risk of colorectal adenoma and proximal and distal colon cancer; no consistent association emerges for rectal cancer. There is emerging evidence linking sedentary behaviour to risk of colorectal cancer and adenoma. Epidemiological evidence suggests that there may be an interaction between leisure-time physical activity and sedentary behaviour. While it is possible that both exposures contribute to carcinogenesis through similar biological mechanisms, further mechanistic research is required to discern whether there are different biological pathways operating in response to physical activity versus sedentary behaviour.

Prospective validation of risk models is needed to assess their clinical utility, particularly over the longer term. We evaluated the performance of six commonly used breast cancer risk models (IBIS, BOADICEA, BRCAPRO, BRCAPRO-BCRAT, BCRAT, and iCARE-lit). 15-year risk scores were estimated using lifestyle factors and family history measures from 7608 women in the Melbourne Collaborative Cohort Study who were aged 50-65 years and unaffected at commencement of follow-up two (conducted in 2003-2007), of whom 351 subsequently developed breast cancer. Risk discrimination was assessed using the C-statistic and calibration using the expected/observed number of incident cases across the spectrum of risk by age group (50-54, 55-59, 60-65 years) and family history of breast cancer. C-statistics were higher for BOADICEA (0.59, 95% confidence interval (CI) 0.56-0.62) and IBIS (0.57, 95% CI 0.54-0.61) than the other models (p-difference ��� 0.04). No model except BOADICEA calibrated well across the spectrum of 15-year risk (p-value < 0.03). The performance of BOADICEA and IBIS was similar across age groups and for women with or without a family history. For middle-aged Australian women, BOADICEA and IBIS had the highest discriminatory accuracy of the six risk models, but apart from BOADICEA, no model was well-calibrated across the risk spectrum., This work was primarily supported by grant 1129136 from the Australian National Health and Medical Research Council (NHMRC) (https://www.nhmrc.gov.au/). MCCS cohort recruitment was funded by Cancer Council Victoria (https://www.cancervic.org.au/) and VicHealth (https://www.vichealth.vic.gov.au/). The MCCS was further supported by Australian NHMRC grants 209057, 396414 and 1074383, and ongoing follow-up and data management has been funded by Cancer Council Victoria since 1995. Cases and their vital status were ascertained through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database.TN-D is a recipient of a Career Development Fellowship from the National Breast Cancer Foundation (Australia). JLH and MCS are Senior Principal and Senior Research Fellows of the National Health and Medical Research Council (Australia), respectively. ACA and AJL are supported by grants from Cancer Research UK (C12292/A20861 and PPRPGM19 Nov20\100002).

Thyroid cancer incidence and the prevalence of overweight and obesity are increasing, but the future thyroid cancer burden attributable to contemporary levels of overweight and obesity has not been evaluated before. We quantified this burden in Australia, and assessed whether the overweight/obesity-attributable burden differed by sex or other population subgroupings. We estimated the strength of the associations of overweight and obesity with thyroid cancer with adjusted proportional hazards models using pooled data from seven Australian cohorts (N=367,058) with 431 thyroid cancer cases ascertained from linked national cancer registry data during a maximum 22-year follow-up. We combined these estimates with nationally representative 2017-2018 estimates of overweight and obesity prevalence to estimate Population Attributable Fractions (PAFs) of future thyroid cancers attributable to overweight and obesity, accounting for competing risk of death, and compared PAFs for population subgroups. Contemporary levels of overweight and obesity explain 18.6% (95%CI=5.2%-30.2%), and obesity alone 13.7% (95%CI=5.2%-21.4%), of the future thyroid cancer burden. The obesity-attributable thyroid cancer burden is 21.4% (95%CI=2.8%-36.5%) for men and 10.1% (95%CI=0.8%-18.6%) for women. Were the currently obese overweight instead, 9.9% (95%CI=1.0%-18.1%) of thyroid cancers could be avoided. The relative overweight/obesity-attributable burden is higher for those consuming on average more than two alcoholic drinks per day (63.4%) and for those who are not married/co-habiting (33.2%). In conclusion, avoiding excess weight, especially obesity, should be a priority for thyroid cancer prevention. Further studies, with findings stratified by tumour size, may reveal the potential role of overdiagnosis in our results. This article is protected by copyright. All rights reserved.

Background Inflammation is a key feature of aging and a cause of numerous diseases. We investigated the association of 35 blood markers involved in inflammatory processes with age and mortality and developed a signature of ‘inflammaging’. Methods Thirty-five blood markers relating to the kynurenine pathway, vitamin status, and inflammation were measured in 976 participants in the Melbourne Collaborative Cohort Study at baseline (1990-1994, median age 59 years) and follow-up (2003-2007, median age 70 years). Associations of each marker with age and all-cause mortality were assessed using linear and Cox regression, respectively. A signature of inflammaging was obtained via Lasso regression of age on the markers and tested for association with mortality; we compared mortality associations for this signature and two weighted scores across all markers associated with age and mortality, respectively. Results Most markers (29/35) were associated with age, with strongest associations observed for cystatin C, neopterin, quinolinic acid, and the kynurenine/tryptophan ratio, PAr index, and 3-hydroxykynurenine/xanthurenic acid ratio. Many markers (14/35) showed strong associations with mortality in particular neopterin, quinolinic acid, HK/XA, PAr index, CRP, IL-6 and KTr. The inflammaging signature included six markers and showed strong association with mortality (HR = 1.5, 95%CI: 1.3-1.7), almost as strong as the association of weighted scores combining all measured markers. Conclusions Our study highlights the key role played by markers of the kynurenine pathway and vitamin B6 catabolism in aging, along with other well-established inflammation-related markers. Key messages A signature of ‘inflammaging’ based on 6 markers may be useful to better predict mortality.

Background Alcohol consumption is causally linked to several cancer sites but the evidence for stomach cancer is still inconclusive. We aimed to quantify the association between alcohol intake and risk of stomach cancer, including subtypes. Methods We pooled data from two cohort studies including 452,958 individuals enrolled in the European Prospective Investigation into Cancer in 1992-98 and 38,756 Australians enrolled in the Melbourne Collaborative Cohort Study in 1990-94. Adjusted hazard ratios (HR) and 95% confidence intervals (CI) for incident stomach cancer were estimated using Cox regression. Results 1,225 incident stomach cancers were diagnosed over 7,094,637 person-years. Alcohol intake was not associated with overall stomach cancer risk. We observed a weak positive dose-response association for lifetime intake with non-cardia stomach cancer (HR = 1.03, 95% CI: 1.00-1.06/per 10 g/day increment), which is the more common type (77.6% of cases), and a weak inverse association with cardia cancer (HR = 0.93, 95% CI: 0.87-1.00) (phomogeneity=0.006). These associations did not differ appreciably by smoking or Helicobacter pylori infection status. Differences in HRs between diffuse-type and intestinal-type cancer were minimal (phomogeneity=0.97). HRs of 1.50 (95% CI: 1.12-2.01) for non-cardia and 0.53 (95% CI: 0.27-1.02) for cardia cancer were observed for a life course trajectory characterised by sustained heavy drinking compared with light drinking (phomogeneity=0.01). Conclusions Lifetime alcohol intake was associated with increased risk of non-cardia stomach cancer. The inverse association for cardia cancer indicates aetiologic differences between subsites. Key messages Limiting long-term alcohol consumption, and avoiding heavy use in particular, might be beneficial in preventing non-cardia stomach cancer.

Background To improve melanoma early detection, tools to predict personal risk based on genetic information (polygenic risk scores, PRS) have been developed, but require external validation. Methods We analysed invasive melanoma incidence in UK Biobank (UKB; n = 395,647; 1,651 cases) and the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4,765; 303 cases). Three PRS were evaluated: 68 genetic variants (SNPs) at 54 loci from a 2020 meta-analysis (PRS68); 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50); 45 SNPs at 21 loci known pre-2020 (PRS45). 10-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment. Results All PRS were strongly associated with melanoma incidence, including after adjustment for age, sex, ethnicity, and ease of tanning. Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in UKB (ratio expected/observed cases E/O=0.65, 95% confidence interval 0.62-0.68) and MCCS (E/O=0.65, 0.57-0.73). For UKB, this was reduced by PRS-adjustment, e.g. PRS50-adjusted risks E/O=0.91 (0.87-0.95). Discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (deltaAUC 0.07-0.1, p Conclusions A PRS derived from a larger, more diverse meta-analysis improves melanoma risk prediction compared to an earlier PRS. Re-calibration of absolute risks may be necessary for application to specific populations. Key messages A genetic score can improve prediction of melanoma risk and might help tailor melanoma prevention and early detection strategies to different risk levels.

Background: Advanced prostate cancer etiology is poorly understood. Few studies have examined associations of anthropometric factors (e.g. early adulthood obesity) with advanced prostate cancer risk.Patients and methods: We carried out pooled analyses to examine associations between body fatness, height, and prostate cancer risk. Among 830 772 men, 51 734 incident prostate cancer cases were identified, including 4762 advanced (T4/N1/M1 or prostate cancer deaths) cases, 2915 advanced restricted (same as advanced, but excluding localized cancers that resulted in death) cases, 9489 high-grade cases, and 3027 prostate cancer deaths. Cox proportional hazards models were used to calculate study-specific hazard ratios (HR) and 95% confidence intervals (CI); results were pooled using random effects models.Results: No statistically significant associations were observed for body mass index (BMI) in early adulthood for advanced, advanced restricted, and high-grade prostate cancer, and prostate cancer mortality. Positive associations were shown for BMI at baseline with advanced prostate cancer (HR = 1.30, 95% CI = 0.95-1.78) and prostate cancer mortality (HR = 1.52, 95% CI = 1.12-2.07) comparing BMI >= 35.0 kg/m(2) with 21-22.9 kg/m(2). When considering early adulthood and baseline BMI together, a 27% higher prostate cancer mortality risk (95% CI = 9% to 49%) was observed for men with BMI = 30.0 kg/m(2) at baseline compared with BMI = 110 cm with = 1.00 with = 1.90 m withConclusion: Our findings suggest that height and total and central adiposity in mid-to-later adulthood, but not early adulthood adiposity, are associated with risk of advanced forms of prostate cancer. Thus, maintenance of healthy weight may help prevent advanced prostate cancer.

Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.

Background Self-reported physical activity is inaccurate, yet few investigators attempt to adjust for measurement error when estimating risks for health outcomes. We estimated what the association between self-reported physical activity and colorectal cancer risk would be if physical activity had been assessed using accelerometry instead. Methods We conducted a validation study in which 235 Australian adults completed a telephone-administered International Physical Activity Questionnaire (IPAQ), and wore an accelerometer (Actigraph GT3X+) for 7 days. Using accelerometer-assessed physical activity as the criterion measure, we calculated validity coefficients and attenuation factors using a structural equation model adjusted for age, sex, education and body mass index. We then used a regression calibration approach to apply the attenuation factors to data from the Melbourne Collaborative Cohort Study (MCCS) to compute bias-adjusted hazard ratios (HR) and 95% confidence intervals (CI). Results Average daily minutes of physical activity from the short form of the International Physical Activity Questionnaire (IPAQ-short) were substantially higher than accelerometer-measured duration (55 versus 32 min). The validity coefficient (0.32; 95% CI: 0.20, 0.43) and attenuation factor (0.20; 95% CI: 0.12, 0.28) were low. The HRs for colorectal cancer risk for high (75th percentile; 411 min/week) versus low (25th percentile; 62 min/week) levels of self-reported physical activity were 0.95 (95% CI: 0.87, 1.05) before and 0.78 (95% CI: 0.47, 1.28) after bias adjustment. Conclusions Over-estimation of physical activity by the IPAQ-short substantially attenuates the association between physical activity and colorectal cancer risk, suggesting that the protective effect of physical activity has been previously underestimated.

BackgroundA number of single nucleotide polymorphisms (SNPs), which are common inherited genetic variants, have been identified that are associated with risk of colorectal cancer. The aim of this study was to determine the ability of these SNPs to estimate colorectal cancer (CRC) risk for persons with and without a family history of CRC, and the screening implications.MethodsWe estimated the association with CRC of a 45 SNP-based risk using 1,181 cases and 999 controls, and its correlation (r) with CRC risk predicted from detailed family history. We estimated the predicted change in the distribution across predefined risk categories, and implications for recommended age to commence screening, from adding SNP-based risk to family history.ResultsThe inter-quintile risk ratio for colorectal cancer risk of the SNP-based risk was 2.46 (95% CI 1.91 – 3.11). SNP-based and family history-based risks were not correlated (r = 0.02). For persons with no first-degree relatives with CRC, recommended screening would commence 2 years earlier for women (4 years for men) in the highest quintile of SNP-based risk, and 12 years later for women (7 years for men) in the lowest quintile. For persons with two first-degree relatives with CRC, recommended screening would commence 15 years earlier for men and women in the highest quintile, and 8 years earlier for men and women in the lowest quintile.ConclusionsRisk reclassification by 45 SNPs could inform targeted screening for CRC prevention, particularly in clinical genetics settings when mutations in high-risk genes cannot be identified.

IntroductionProstate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets.MethodsIn total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry—the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured.ResultsThe final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively.ConclusionWe demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.

Background Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46). Materials and method 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy. Results 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer. Conclusions Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.

Alcohol consumption is a known cause of cancer, but its role in the etiology of second primary (metachronous) cancer is uncertain. Associations between alcohol intake up until study enrollment (prediagnosis) and risk of metachronous cancer were estimated using 9435 participants in the Melbourne Collaborative Cohort Study who were diagnosed with their first invasive cancer after enrollment (1990-1994). Follow-up was from date of first invasive cancer until diagnosis of metachronous cancer, death or censor date (February 2018), whichever came first. Alcohol intake for 10-year periods from age 20 until decade encompassing baseline using recalled beverage-specific frequency and quantity was used to calculate baseline and lifetime intakes, and group-based intake trajectories. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs), adjusted for potential confounders. After a mean follow-up of 7 years, 1512 metachronous cancers were identified. A 10 g/d increment in prediagnosis lifetime alcohol intake (HR = 1.03, 95% CI = 1.00-1.06; Pvalue = .02) and an intake of ≥60 g/d (HR = 1.32, 95% CI = 1.01-1.73) were associated with increased metachronous cancer risk. We observed positive associations (per 10 g/d increment) for metachronous colorectal (HR = 1.07, 95% CI = 1.00-1.14), upper aero-digestive tract (UADT) (HR = 1.16, 95% CI = 1.00-1.34) and kidney cancer (HR = 1.24, 95% CI = 1.10-1.39). Although these findings were partly explained by effects of smoking, the association for kidney cancer remained unchanged when current smokers or obese individuals were excluded. Alcohol intake trajectories over the life course confirmed associations with metachronous cancer risk. Prediagnosis long-term alcohol intake, and particularly heavy drinking, may increase the risk of metachronous cancer, particularly of the colorectum, UADT and kidney.

Background The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm and the International Breast Cancer Intervention Study breast cancer risk models are used to provide advice on screening intervals and chemoprevention. We evaluated the performance of these models, which now incorporate polygenic risk scores (PRSs), using a prospective cohort study. Methods We used a case-cohort design, involving women in the Melbourne Collaborative Cohort Study aged 50-75 years when surveyed in 2003-2007, of whom 408 had a first primary breast cancer diagnosed within 10 years (cases), and 2783 were from the subcohort. Ten-year risks were calculated based on lifestyle factors, family history data, and a 313-variant PRS. Discrimination was assessed using a C-statistic compared with 0.50 and calibration using the ratio of expected to observed number of cases (E/O). Results When the PRS was added to models with lifestyle factors and family history, the C-statistic (95% confidence interval [CI]) increased from 0.57 (0.54 to 0.60) to 0.62 (0.60 to 0.65) using IBIS and from 0.56 (0.53 to 0.59) to 0.62 (0.59 to 0.64) using BOADICEA. IBIS underpredicted risk (E/O = 0.62, 95% CI = 0.48 to 0.80) for women in the lowest risk category ( Conclusions Although the inclusion of a 313 genetic variant PRS doubles discriminatory accuracy (relative to reference 0.50), models with and without this PRS have relatively modest discrimination and might require recalibration before their clinical and wider use are promoted.

Importance Women with pathogenic variants in BRCA1 and BRCA2 are at high risk of developing breast and ovarian cancers. They usually undergo intensive cancer surveillance and may also consider surgical interventions, such as risk-reducing mastectomy or risk-reducing salpingo-oophorectomy (RRSO). Risk-reducing salpingo-oophorectomy has been shown to reduce ovarian cancer risk, but its association with breast cancer risk is less clear. Objective To assess the association of RRSO with the risk of breast cancer in women with BRCA1 and BRCA2 pathogenic variants. Design, setting, and participants This case series included families enrolled in the Breast Cancer Family Registry between 1996 and 2000 that carried an inherited pathogenic variant in BRCA1 (498 families) or BRCA2 (378 families). A survival analysis approach was used that was designed specifically to assess the time-varying association of RRSO with breast cancer risk and accounting for other potential biases. Data were analyzed from August 2019 to November 2020. Exposure Risk-reducing salpingo-oophorectomy. Main outcomes and measures In all analyses, the primary end point was the time to a first primary breast cancer. Results A total of 876 families were evaluated, including 498 with BRCA1 (2650 individuals; mean [SD] event age, 55.8 [19.1] years; 437 White probands [87.8%]) and 378 with BRCA2 (1925 individuals; mean [SD] event age, 57.0 [18.6] years; 299 White probands [79.1%]). Risk-reducing salpingo-oophorectomy was associated with a reduced risk of breast cancer for BRCA1 and BRCA2 pathogenic variant carriers within 5 years after surgery (hazard ratios [HRs], 0.28 [95% CI, 0.10-0.63] and 0.19 [95% CI, 0.06-0.71], respectively), whereas the corresponding HRs were weaker after 5 years postsurgery (HRs, 0.64 [95% CI, 0.38-0.97] and 0.99 [95% CI; 0.84-1.00], respectively). For BRCA1 and BRCA2 pathogenic variant carriers who underwent RRSO at age 40 years, the cause-specific cumulative risk of breast cancer was 49.7% (95% CI, 40.0-60.3) and 52.7% (95% CI, 47.9-58.7) by age 70 years, respectively, compared with 61.0% (95% CI, 56.7-66.0) and 54.0% (95% CI, 49.3-60.1), respectively, for women without RRSO. Conclusions and relevance Although the primary indication for RRSO is the prevention of ovarian cancer, it is also critical to assess its association with breast cancer risk in order to guide clinical decision-making about RRSO use and timing. The results of this case series suggest a reduced risk of breast cancer associated with RRSO in the immediate 5 years after surgery in women carrying BRCA1 and BRCA2 pathogenic variants, and a longer-term association with cumulative breast cancer risk in women carrying BRCA1 pathogenic variants.

In the version of this article originally published, the names of the equally contributing authors and jointly supervising authors were switched. The correct affiliations are: “These authors contributed equally: David V. Conti, Burcu F. Darst. These authors jointly supervised this work: David V. Conti, Rosalind A. Eeles, Zsofia Kote-Jarai, Christopher A. Haiman.” The error has been corrected in the HTML and PDF versions of the article.

Alcohol consumption is causally linked to several cancers but the evidence for stomach cancer is inconclusive. In our study, the association between long-term alcohol intake and risk of stomach cancer and its subtypes was evaluated. We performed a pooled analysis of data collected at baseline from 491 714 participants in the European Prospective Investigation into Cancer and Nutrition and the Melbourne Collaborative Cohort Study. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for incident stomach cancer in relation to lifetime alcohol intake and group-based life course intake trajectories, adjusted for potential confounders including Helicobacter pylori infection. In all, 1225 incident stomach cancers (78% noncardia) were diagnosed over 7 094 637 person-years; 984 in 382 957 study participants with lifetime alcohol intake data (5 455 507 person-years). Although lifetime alcohol intake was not associated with overall stomach cancer risk, we observed a weak positive association with noncardia cancer (HR = 1.03, 95% CI: 1.00-1.06 per 10 g/d increment), with a HR of 1.50 (95% CI: 1.08-2.09) for ≥60 g/d compared to 0.1 to 4.9 g/d. A weak inverse association with cardia cancer (HR = 0.93, 95% CI: 0.87-1.00) was also observed. HRs of 1.48 (95% CI: 1.10-1.99) for noncardia and 0.51 (95% CI: 0.26-1.03) for cardia cancer were observed for a life course trajectory characterized by heavy decreasing intake compared to light stable intake (Phomogeneity = .02). These associations did not differ appreciably by smoking or H pylori infection status. Limiting alcohol use during lifetime, particularly avoiding heavy use during early adulthood, might help prevent noncardia stomach cancer. Heterogeneous associations observed for cardia and noncardia cancers may indicate etiologic differences., National Health and Medical Research Council of Australia 1074383 209057 396414 GNT1163120, Canadian Institutes of Health Research (CIHR) Cancer Council Victoria, Cancer Research UK C570/A16491 C8221/A19170 C864/A14136, Catalan Institute of Oncology - ICO (Spain), Danish Cancer Society, Deutsche Krebshilfe, Deutsches Krebsforschungszentrum (Germany), Dutch Ministry of Public Health, Welfare and Sports, European Commission European Commission Joint Research Centre, Foundation for Alcohol Research and Education (Australia), French Ministry of Health GR-IARC-2003-09-12-01, Health Research Fund (FIS) -Instituto de Salud Carlos III (ISCIII), Junta de Andalucía, Regional Government of Asturias, Basque Government, Regional Government of Murcia, Regional Government of Navarra, Hellenic Health Foundation (Greece), Hellenic Ministry of Health and Social Solidarity (Greece), Institut National de la Sante et de la Recherche Medicale (Inserm), Consiglio Nazionale delle Ricerche (CNR), Associazione Italiana per la Ricerca sul Cancro (AIRC), Ligue Contre le Cancer (France), LK Research Funds, Dutch Prevention Funds, Netherlands Organization for Scientific Research (NWO), UK Research & Innovation (UKRI) Medical Research Council UK (MRC) MC-UU_12015/1 MR/M012190/1 MR/N003284/, Mutuelle Generale de l'Education Nationale, National Institute for Public Health and the Environment (RIVM) (the Netherlands), Netherlands Cancer Registry, Stavros Niarchos Foundation (Greece), Stroke Association (UK), British Heart Foundation, Department of Health (UK), Food Standards Agency (UK), Wellcome Trust, Swedish Cancer Society, Swedish Scientific Council (Sweden), Regional Government of Skane (Sweden), Federal Ministry of Education & Research (BMBF), VicHealth (Australia), World Cancer Research Fund and Statistics Netherlands (the Netherlands), Institut Gustave Roussy

Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.

While gene panel sequencing is becoming widely used for cancer risk prediction, its clinical utility with respect to predicting aggressive prostate cancer (PrCa) is limited by our current understanding of the genetic risk factors associated with predisposition to this potentially lethal disease phenotype. This study included 837 men diagnosed with aggressive PrCa and 7261 controls (unaffected men and men who did not meet criteria for aggressive PrCa). Rare germline pathogenic variants (including likely pathogenic variants) were identified by targeted sequencing of 26 known or putative cancer predisposition genes. We found that 85 (10%) men with aggressive PrCa and 265 (4%) controls carried a pathogenic variant (p &lt, 0.0001). Aggressive PrCa odds ratios (ORs) were estimated using unconditional logistic regression. Increased risk of aggressive PrCa (OR (95% confidence interval)) was identified for pathogenic variants in BRCA2 (5.8 (2.7–12.4)), BRCA1 (5.5 (1.8–16.6)), and ATM (3.8 (1.6–9.1)). Our study provides further evidence that rare germline pathogenic variants in these genes are associated with increased risk of this aggressive, clinically relevant subset of PrCa. These rare genetic variants could be incorporated into risk prediction models to improve their precision to identify men at highest risk of aggressive prostate cancer and be used to identify men with newly diagnosed prostate cancer who require urgent treatment.

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.

Background In the era of widespread prostate-specific antigen testing, it is important to focus etiologic research on the outcome of aggressive prostate cancer, but studies have defined this outcome differently. We aimed to develop an evidence-based consensus definition of aggressive prostate cancer using clinical features at diagnosis for etiologic epidemiologic research. Methods Among prostate cancer cases diagnosed in 2007 in the National Cancer Institute’s Surveillance, Epidemiology, and End Results-18 database with follow-up through 2017, we compared the performance of categorizations of aggressive prostate cancer in discriminating fatal prostate cancer within 10 years of diagnosis, placing the most emphasis on sensitivity and positive predictive value (PPV). Results In our case population (n = 55 900), 3073 men died of prostate cancer within 10 years. Among 12 definitions that included TNM staging and Gleason score, sensitivities ranged from 0.64 to 0.89 and PPVs ranged from 0.09 to 0.23. We propose defining aggressive prostate cancer as diagnosis of category T4 or N1 or M1 or Gleason score of 8 or greater prostate cancer, because this definition had one of the higher PPVs (0.23, 95% confidence interval = 0.22 to 0.24) and reasonable sensitivity (0.66, 95% confidence interval = 0.64 to 0.67) for prostate cancer death within 10 years. Results were similar across sensitivity analyses. Conclusions We recommend that etiologic epidemiologic studies of prostate cancer report results for this definition of aggressive prostate cancer. We also recommend that studies separately report results for advanced category (T4 or N1 or M1), high-grade (Gleason score ≥8), and fatal prostate cancer. Use of this comprehensive set of endpoints will facilitate comparison of results from different studies and help elucidate prostate cancer etiology.

Background There is an urgent need to identify factors specifically associated with aggressive prostate cancer (PCa) risk. We investigated whether rare pathogenic, likely pathogenic, or deleterious (P/LP/D) germline variants in DNA repair genes are associated with aggressive PCa risk in a case-case study of aggressive vs nonaggressive disease. Methods Participants were 5545 European-ancestry men, including 2775 nonaggressive and 2770 aggressive PCa cases, which included 467 metastatic cases (16.9%). Samples were assembled from 12 international studies and germline sequenced together. Rare (minor allele frequency Results BRCA2 and PALB2 had the most statistically significant gene-based associations, with 2.5% of aggressive and 0.8% of nonaggressive cases carrying P/LP/D BRCA2 alleles (odds ratio [OR] = 3.19, 95% confidence interval [CI] = 1.94 to 5.25, P = 8.58 × 10-7) and 0.65% of aggressive and 0.11% of nonaggressive cases carrying P/LP/D PALB2 alleles (OR = 6.31, 95% CI = 1.83 to 21.68, P = 4.79 × 10-4). ATM had a nominal association, with 1.6% of aggressive and 0.8% of nonaggressive cases carrying P/LP/D ATM alleles (OR = 1.88, 95% CI = 1.10 to 3.22, P = .02). In aggregate, P/LP/D alleles within 24 literature-curated candidate PCa DNA repair genes were more common in aggressive than nonaggressive cases (carrier frequencies = 14.2% vs 10.6%, respectively; P = 5.56 × 10-5). However, this difference was non-statistically significant (P = .18) on excluding BRCA2, PALB2, and ATM. Among these 24 genes, P/LP/D carriers had a 1.06-year younger diagnosis age (95% CI = -1.65 to 0.48, P = 3.71 × 10-4). Conclusions Risk conveyed by DNA repair genes is largely driven by rare P/LP/D alleles within BRCA2, PALB2, and ATM. These findings support the importance of these genes in both screening and disease management considerations.

Purpose Using the Melbourne Collaborative Cohort Study, we examined the associations of occupation, household, transport, and leisure physical activity with pain interference with normal work and muscle pain after activity. Methods This cross-sectional analysis included 7655 working and 11,766 nonworking participants. Physical activity was assessed using the long-form International Physical Activity Questionnaire. Pain interference was assessed with the Short-Form 12-Item Health Survey version 2.0, and muscle pain after activity was assessed using the 12-item Somatic and Psychological Health Report. Ordered logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI), and restricted cubic splines were used to graphically represent the shape of associations. Results All physical activity domain-pain outcome associations were nonlinear. Compared with participants who reported the lowest level of activity, participants who reported the median level of transport physical activity (10 MET·h·wk) reported less pain interference (workers: OR, 0.86 [95% CI, 0.77-0.97]; nonworkers: OR, 0.88 [95% CI, 0.79-0.97]) and muscle pain after activity (workers: OR, 0.81 [95% CI, 0.70-0.95]; nonworkers: OR, 0.86 [95% CI, 0.77-0.95]). Higher levels of leisure time activity (20 MET·h·wk) were associated with less pain interference in nonworkers (OR, 0.87; 95% CI, 0.77-0.98) and muscle pain after activity in workers (OR, 0.67; 95% CI, 0.56-0.80). Workers who reported the median level of household activity (16 MET·h·wk) had increased pain interference (OR, 1.19; 95% CI, 1.07-1.32) and muscle pain after activity (OR, 1.23; 95% CI, 1.06-1.42) than did those who reported the least household activity. Conclusions Associations between domain-specific physical activity and pain outcomes were not uniform. Within the transport and leisure domains, physical activity was inversely associated with pain-related outcomes, whereas household physical activity was positively associated with pain scores within the working sample.

BackgroundPolygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).Materials and Method180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.Results166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.ConclusionIncorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.

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

Background: iPrevent (https://www.petermac.org/iprevent) provides women with highly-tailored risk management information after first estimating their breast cancer (BC) risk using the established risk prediction models, IBIS and BOADICEA. iPrevent has an internal switching algorithm that governs which model is used for each woman, depending on her risk factor data (i.e. LCIS/atypical hyperplasia status, BRCA status, and cancer family history). This study assessed the calibration and discriminatory accuracy of the 10-year BC risk estimates provided by iPrevent. Methods: Subjects were 16,574 women in the ProF-SC, aged 18-70 years and without BC or bilateral mastectomy at recruitment. After 10 years follow-up, 655 women (4%) were diagnosed with invasive BC. A “batch mode” for iPrevent is not available, so the iPrevent-assigned cumulative 10-year invasive BC risks were calculated by entering self-reported risk factors at cohort entry into either the IBIS (10,169 women) or BOADICEA (6,405 women) software packages (according to the iPrevent switching algorithm). To assess calibration, the mean iPrevent-assigned risk was compared with the mean 10-year observed invasive BC incidence, using a chi-squared goodness-of-fit statistic for the whole cohort, and by quartiles of risk. To evaluate discriminatory accuracy, the overall area under the receiver operating characteristic curve (AUC) for the development of invasive BC within 10 years was computed. Data were censored at date of invasive or in situ BC diagnosis, bilateral mastectomy, death, loss to follow-up, or at 10 years of follow-up. Results: For the whole cohort, iPrevent assigned risk was well-calibrated – 690 expected BCs (E) 655 observed (O) (E/O=1.05, 95% CI: 0.98-1.14), although for women in the highest risk quartile, i.e. >6% 10-year risk, E/O=1.19, 95% CI: 1.07-1.32. The AUC was 0.70, 95% CI: 0.68-0.72. Conclusions: iPrevent is well calibrated overall and has good discriminatory accuracy for predicting 10-year BC risk, thus justifying its clinical use. Citation Format: Phillips K-A, Liao Y, Collins IM, Buchsbaum R, Weideman P, Bickerstaffe A, MacInnis RJ, kConFab Investigators, Cuzick J, Antoniou A, Andrulis IL, John EM, Daly MB, Buys SS, Hopper JL, Terry MB. Validation of iPrevent using the prospective family study cohort (ProF-SC) [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-09-02.

BackgroundMammograms contain information that predicts breast cancer risk. We recently discovered two novel mammogram-based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). It is not known whether these measures improve risk prediction when fitted together, and with an established measure of mammographic density (Cumulus).MethodsWe used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen-detected cases and 1,197 matched controls; and 354 younger-diagnosis cases and 944 frequency-matched controls. We conducted conditional and unconditional logistic regression analyses of individually-and frequency-matched studies, respectively. We reported risk gradients as change in odds ratio per standard deviation of controls after adjusting for age and body mass index (OPERA). For models involving multiple measures, we calculated the OPERA equivalent to the area under the receiver operating characteristic curve.ResultsFor interval, screen-detected and younger-diagnosis cancer, the best fitting models (OPERAs [95% confidence intervals]) were: Cumulus (1.81 [1.41 to 2.31]) and Cirrus (1.7 [1.38 to 2.14]); Cirrus (1.49 [1.32 to 1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27 to 1.68]), respectively. Their OPERA equivalents were: 2.35, 1.58, and 2.28, respectively.ConclusionsOur mammogram-based measures improved risk prediction beyond and, except for interval cancers, negated the influence of conventional mammographic density. Combined, these new mammogram-based risk measures are at least as accurate as the current polygenetic risk scores (OPERA ~ 1.6) in predicting, on a population basis, women who will be diagnosed with breast cancer.

The original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.

Purpose: Reducing colorectal cancer incidence and mortality through early detection would improve efficacy if targeted. We developed a colorectal cancer risk prediction model incorporating personal, family, genetic, and environmental risk factors to enhance prevention. Methods: A familial risk profile (FRP) was calculated to summarize individuals' risk based on detailed cancer family history (FH), family structure, probabilities of mutation in major colorectal cancer susceptibility genes, and a polygenic component. We developed risk models, including individuals' FRP or binary colorectal cancer FH, and colorectal cancer risk factors collected at enrollment using population-based colorectal cancer cases (N = 4,445) and controls (N = 3,967) recruited by the Colon Cancer Family Registry Cohort (CCFRC). Model validation used CCFRC follow-up data for population-based (N = 12,052) and clinic-based (N = 5,584) relatives with no cancer history at recruitment to assess model calibration [expected/observed rate ratio (E/O)] and discrimination [area under the receiver-operating-characteristic curve (AUC)]. Results: The E/O [95% confidence interval (CI)] for FRP models for population-based relatives were 1.04 (0.74–1.45) for men and 0.86 (0.64–1.20) for women, and for clinic-based relatives were 1.15 (0.87–1.58) for men and 1.04 (0.76–1.45) for women. The age-adjusted AUCs (95% CI) for FRP models for population-based relatives were 0.69 (0.60–0.78) for men and 0.70 (0.62–0.77) for women, and for clinic-based relatives were 0.77 (0.69–0.84) for men and 0.68 (0.60–0.76) for women. The incremental values of AUC for FRP over FH models for population-based relatives were 0.08 (0.01–0.15) for men and 0.10 (0.04–0.16) for women, and for clinic-based relatives were 0.11 (0.05–0.17) for men and 0.11 (0.06–0.17) for women. Conclusions: Both models calibrated well. The FRP-based model provided better risk stratification and risk discrimination than the FH-based model. Impact: Our findings suggest detailed FH may be useful for targeted risk-based screening and clinical management.

There remains debate about whether risk-reducing salpingo-oophorectomy (RRSO), which reduces ovarian cancer risk, also reduces breast cancer risk. We examined the association between RRSO and breast cancer risk using a prospective cohort of 17 917 women unaffected with breast cancer at baseline (7.2% known carriers of BRCA1 or BRCA2 mutations). During a median follow-up of 10.7 years, 1046 women were diagnosed with incident breast cancer. Modeling RRSO as a time-varying exposure, there was no association with breast cancer risk overall (hazard ratio [HR] = 1.04, 95% confidence interval [CI] = 0.87 to 1.24) or by tertiles of predicted absolute risk based on family history (HR = 0.68, 95% CI = 0.32 to 1.47, HR = 0.94, 95% CI = 0.70 to 1.26, and HR = 1.10, 95% CI = 0.88 to 1.39, for lowest, middle, and highest tertile of risk, respectively) or for BRCA1 and BRCA2 mutation carriers when examined separately. There was also no association after accounting for hormone therapy use after RRSO. These findings suggest that RRSO should not be considered efficacious for reducing breast cancer risk. ispartof: Jnci-Journal Of The National Cancer Institute vol:111 issue:3 pages:331-334 ispartof: location:United States status: published

Background Physical activity reduces the risk of colorectal cancer (CRC), but the relevant evidence derives primarily from self-reported recreational and occupational activity. Less is known about the contribution of other domains of physical activity, such as transport and household. We examined associations between domain-specific physical activities and CRC risk within the Melbourne Collaborative Cohort Study. Methods Analyses included 23,586 participants who were free from invasive colorectal cancer and had completed the International Physical Activity Questionnaire-Long Form at follow-up 2 (2003–2007). Cox regression, with age as the time metric, was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for ordinal categories of each physical activity domain. Results Adjusted HRs for the highest versus the lowest categories of physical activity were 0.71 (95% CI: 0.51–0.98; ptrend = 0.03) for recreational activity; 0.80 (95% CI: 0.49–1.28; ptrend = 0.38) for occupational activity; 0.90 (95% CI: 0.68–1.19; ptrend = 0.20) for transport activity; and 1.07 (95% CI: 0.82–1.40; ptrend = 0.46) for household activity. Conclusions Recreational activity was associated with reduced CRC risk. A non-significant, inverse association was observed for occupational activity, whereas no association was found for transport or household domains. Electronic supplementary material The online version of this article (10.1186/s12885-018-4961-x) contains supplementary material, which is available to authorized users.

Background and aims In Australia, as in many countries, alcohol consumption increased dramatically during the second half of the 20th century, with increased availability of alcohol, relaxation of attitudes towards drinking and shifting roles and opportunities for women as facilitating factors. We sought to investigate drinking trends by gender and birth cohort in Australia during this period. Design Retrospective cohort study. Setting, participants and measurements Using the usual frequency and quantity of beverage-specific alcohol intake for 10-year periods from age 20, reported retrospectively from 40 789 participants aged 40-69 years (born 1920-49) at recruitment to the Melbourne Collaborative Cohort Study in 1990-94, we compared trends in alcohol consumption by sex in Australia between 1950 and 1990. Participants' average daily consumption for age decades were transformed to estimated intakes for 1950, 1960, 1970, 1980 and 1990. Findings Alcohol consumption was higher for men than women during each decade. Alcohol consumption increased for both sexes in the 1950s, 1960s and 1970s, and fell after 1980. The rise before 1980 was roughly equal in absolute terms for both sexes, but much greater relative to 1950 for women. Women born during 1930-39 and 1940-49 drank more alcohol during early-middle adulthood (ages 20-40) than women born during 1920-29. In the 1980s, the fall was greater in absolute terms for men, but roughly equal relative to 1950 for both sexes. In both sexes, the decline in drinking in the 1980s for birth-decade cohorts was roughly in parallel. Conclusions Specific birth cohorts were influential in the rise in alcohol consumption by Australian women born in 1920-49 after World War II. Much of the convergence with men's drinking after 1980 reflects large reductions in drinking among men.

Purpose The incidence of renal cell carcinoma (RCC) is rising. Use of analgesics such as non-steroidal anti-inflammatory drugs (NSAIDs) and paracetamol may affect renal function. The aim of this study was to assess associations between analgesic use and risk of RCC. Methods A population-based case-control family design was used. Cases were recruited via two Australian state cancer registries. Controls were siblings or partners of cases. Analgesic use was captured by self-completed questionnaire. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for RCC risk associated with regular analgesic use (at least 5 times per month for 6 months or more) and duration and frequency of use. Results The analysis included 1064 cases and 724 controls. Regular use of paracetamol was associated with an increased risk of RCC (OR 1.41, 95%CI 1.13–1.77). Regular use of NSAIDs was associated with increased risk of RCC for women (OR 1.71, 95% CI 1.23–2.39) but not men (OR 0.83, 95% CI 0.58–1.18; p-interaction=0.003). There was no evidence of a dose-response for duration of use of paracetamol (linear trend p = 0.77) and weak evidence for non- aspirin NSAID use by women (linear trend p = 0.054). Conclusion This study found that regular use of paracetamol was associated with increased risk of RCC. NSAID use was associated with increased risk only for women.

Background: Whether risk-reducing salpingo oophorectomy (RRSO) reduces breast cancer risk in addition to reducing ovarian cancer risk is controversial with some arguing that the previous evidence of a reduction in breast cancer risk from RRSO was due to bias. Evidence from independent prospective cohorts of high-risk women is needed to resolve this controversy. Methods: Using a prospective family study cohort of 17,810 women unaffected with breast cancer at baseline, we examined the association between RRSO and breast cancer risk using Cox Proportional Hazards models. We compared results estimating RRSO as a non-time-dependent variable to results treating RRSO as a time-dependent variable, because failing to account for the time-varying nature of a covariate person- time prior to RRSO, should it exist, will incorrectly attribute the cancer-free person-time to RRSO. We separately examined the association with RRSO in BRCA1 and BRCA2 mutation carriers and non-carriers, and further performed gene-stratified analyses in women with BRCA1 and BRCA2 only. We also assessed multiplicative interactions with underlying familial risk profile (FRP), defined as total lifetime risk estimated from the Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) model. Results: During a median 10.7 years of follow-up (maximum 23.7 years), we observed 1,040 incident cases of breast cancer with an average age at diagnosis of 55.8 years and average age at enrollment into the cohort of 46.8 years. A total of 2434 (14%) women reported at baseline having a RRSO. We observed decreased risk of breast cancer associated with RRSO for both BRCA1(N= 650) and BRCA2(N=557) mutation carriers when RRSO was treated as a fixed covariate (HR= 0.60, 95% CI=0.40-0.92 and HR= 0.40, 95%CI = 0.23-0.69, respectively). In contrast, when we treated RRSO as a time-varying covariate, for both BRCA1 and BRCA2 carriers, we no longer observed a decreased risk for BRCA1 and BRCA2 carriers (HR= 1.67, 95% CI=1.05-2.67 and HR= 0.97, 95%CI = 0.53-1.80, respectively). There was no association between RRSO and breast cancer risk for non-carriers (N=16,603), whether we treated RRSO as a fixed or time varying covariate (HR= 0.88, 95% CI=0.72-1.08 and HR= 1.06, 95%CI = 0.85-1.30, respectively). Conclusions: Our findings provide an independent replication that the reduced risk of breast cancer previously observed in BRCA1 and BRCA2 mutation carrier women may be from bias in counting person-time. Clinical management of high-risk women should counsel based on the reduced risk of ovarian cancer from RRSO, but not breast cancer. Citation Format: Terry MB, Phillips KA, Daly MB, Andrulis IL, Liao Y, Ma X, Zeinomar N, MacInnis RJ, Dite GS, John EM, Buys SS, Hopper JL. Risk-reducing oophorectomy and breast cancer risk across the spectrum of familial risk using a prospective family study cohort (ProF-SC) [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P6-09-01.

Background: Benign breast disease (BBD) is one of the strongest risk factors for breast cancer but it is unclear whether the strength of the association with BBD and breast cancers varies by breast cancer family history. Few studies of BBD enrich specifically for putative genetic factors by over-sampling based on family history let alone evaluate potential interactions with measures of underlying familial risk. The aim of this study was to evaluate how risk associated with BBD is modified by underlying familial risk so as to guide clinical management and risk assessment of women with BBD. Methods: Using a prospective family study cohort of 17,154 women unaffected with breast cancer at baseline and followed by questionnaire at regular intervals, we examined the association between BBD and breast cancer risk using Cox Proportional Hazards models. We classified women as having BBD if they reported at baseline having been told by a doctor that they had BBD, such as a non-cancerous cyst or breast lump. We did not have information on histologic sub-type. We confirmed self-reported diagnosis of BBD with pathology reports in a subset of the New York cohort and found high agreement between self-reported and pathologically confirmed BBD (93.5%). We assessed multiplicative and additive interactions with underlying familial risk profile (FRP) defined as either fixed-time horizon of 1-year, or total lifetime risk, estimated from the Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) model. Results: During 176,756 person-years of follow-up (mean 10.2, maximum 23.7 years), we observed 968 incident breast cancers cases with an average age at diagnosis of 55.8 years and average age at enrollment into the cohort of 46.8 years. At baseline, 4,704 (27%) women reported having a previous diagnosis of BBD. Compared to women with no history of BBD, breast cancer risk was increased in women of all ages (HR: 1.37, 95% CI: 1.19,1.56), and in women up to age 45 years (using attained age models) (HR: 1.40, 95% CI: 1.01,1.93). In terms of recency of BBD, we found that the increased risk associated with BBD remained 21 years or more after the initial BBD diagnosis (HR: 1.37, 95% CI: 1.11, 1.68). We found no evidence for multiplicative interactions with FRP, which implies that the increase in absolute risk associated with BBD depends on a woman's FRP (Table 1). Conclusions: Women with a history of BBD have an increased risk of breast cancer that multiplies their underlying familial risk (FRP). These results could prove to be valuable for risk counseling and clinical management. Table 1: Cumulative Incidence of Breast Cancer to age 45, 55, and 65 by BBD and underlying FRP as measured by 10-year BOADICEA score.AgeNo BBD, Citation Format: Zeinomar N, Phillips KA, Liao Y, MacInnis RJ, Dite GS, Daly MB, John EM, Andrulis IL, Buys SS, Hopper JL, Terry MB. Benign breast disease and breast cancer risk across the spectrum of familial risk using a prospective family study cohort (ProF-SC) [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P6-09-04.

We aimed to evaluate the associations between androgenetic alopecia at a young age and subsequent development of aggressive prostate cancer (PC). Using a case–control design with self-administered questionnaire, we evaluated the association between aggressive PC and very early-onset balding at age 20, and early-onset balding at age 40 years in 1,941 men. Cases were men with high-grade and/or advanced stage cancer and controls were clinic based men who had undergone biopsy and were found to be histologically cancer negative. Additionally, for cases we assessed whether early-onset balding was associated with earlier onset of disease. Men with very early-onset balding at age 20 years were at increased risk for subsequent aggressive PC [odds ratio (OR) 1.51, 95% confidence interval (CI) 1.07–2.12] after adjustment for age at baseline, family history of PC, smoking status, alcohol intake, body shape, timing of growth spurt and ejaculatory frequency. Additionally, these men were diagnosed with PC approximately 16 months earlier than cases without the exposure. The effect was present particularly for men with advanced stage pT3+ disease (OR 1.68, 95% CI 1.14–2.47) while men with organ-confined high-grade (8–10) PC did not exhibit the same relationship. No significant associations were observed for men who were balding at age 40 years, given no balding at age 20. Men with androgenetic alopecia at age 20 years are at increased risk of advanced stage PC. This small subset of men are potentially candidates for earlier screening and urological follow-up.

The influence of lifestyle factors on survival following a diagnosis of colorectal cancer (CRC) is not well established. We examined associations between lifestyle factors measured before diagnosis and CRC survival. The Melbourne Collaborative Cohort Study collected data on alcohol intake, cigarette smoking and physical activity, and body measurements at baseline (1990-1994) and wave 2 (2003-2007). We included participants diagnosed to 31 August 2015 with incident stages I-III CRC within 10-years post exposure assessment. Information on tumor characteristics and vital status was obtained. Tumor DNA was tested for microsatellite instability (MSI) and somatic mutations in oncogenes BRAF (V600E) and KRAS. We estimated hazard ratios (HRs) for associations between lifestyle factors and overall and CRC-specific mortality using Cox regression. Of 724 eligible CRC cases, 339 died (170 from CRC) during follow-up (average 9.0 years). Exercise (non-occupational/leisure-time) was associated with higher CRC-specific survival for stage II (HR = 0.25, 95% CI: 0.10-0.60) but not stages I/III disease (p for interaction = 0.01), and possibly for colon and KRAS wild-type tumors. Waist circumference was inversely associated with CRC-specific survival (HR = 1.25 per 10 cm increment, 95% CI: 1.08-1.44), independent of stage, anatomic site and tumor molecular status. Cigarette smoking was associated with lower overall survival, with suggestive evidence of worse survival for BRAF mutated CRC, but not with CRC-specific survival. Alcohol intake was not associated with survival. Survival did not differ by MSI status. We have identified pre-diagnostic predictors of survival following CRC that may have clinical and public health relevance.

Background: After adjusting for age and body mass index (BMI), mammographic measures—dense area (DA), percent dense area (PDA), and nondense area (NDA)—are associated with breast cancer risk. Our aim was to use longitudinal data to estimate the extent to which these risk-predicting measures track over time. Methods: We collected 4,320 mammograms (age range, 24–83 years) from 970 women in the Melbourne Collaborative Cohort Study and the Australian Breast Cancer Family Registry. Women had on average 4.5 mammograms (range, 1–14). DA, PDA, and NDA were measured using the Cumulus software and normalized using the Box–Cox method. Correlations in the normalized risk-predicting measures over time intervals of different lengths were estimated using nonlinear mixed-effects modeling of Gompertz curves. Results: Mean normalized DA and PDA were constant with age to the early 40s, decreased over the next two decades, and were almost constant from the mid-60s onward. Mean normalized NDA increased nonlinearly with age. After adjusting for age and BMI, the within-woman correlation estimates for normalized DA were 0.94, 0.93, 0.91, 0.91, and 0.91 for mammograms taken 2, 4, 6, 8, and 10 years apart, respectively. Similar correlations were estimated for the age- and BMI-adjusted normalized PDA and NDA. Conclusions: The mammographic measures that predict breast cancer risk are highly correlated over time. Impact: This has implications for etiologic research and clinical management whereby women at increased risk could be identified at a young age (e.g., early 40s or even younger) and recommended appropriate screening and prevention strategies. Cancer Epidemiol Biomarkers Prev; 26(4); 651–60. ©2017 AACR.

BACKGROUND & AIMS: Early-onset colorectal cancer (CRC, in persons younger than 50 years old) is increasing in incidence; yet, in the absence of a family history of CRC, this population lacks harmonized recommendations for prevention. We aimed to determine whether a polygenic risk score (PRS) developed from 95 CRC-associated common genetic risk variants was associated with risk for early-onset CRC. METHODS: We studied risk for CRC associated with a weighted PRS in 12,197 participants younger than 50 years old vs 95,865 participants 50 years or older. PRS was calculated based on single nucleotide polymorphisms associated with CRC in a large-scale genome-wide association study as of January 2019. Participants were pooled from 3 large consortia that provided clinical and genotyping data: the Colon Cancer Family Registry, the Colorectal Transdisciplinary Study, and the Genetics and Epidemiology of Colorectal Cancer Consortium and were all of genetically defined European descent. Findings were replicated in an independent cohort of 72,573 participants. RESULTS: Overall associations with CRC per standard deviation of PRS were significant for early-onset cancer, and were stronger compared with late-onset cancer (P for interaction = .01); when we compared the highest PRS quartile with the lowest, risk increased 3.7-fold for early-onset CRC (95% CI 3.28-4.24) vs 2.9-fold for late-onset CRC (95% CI 2.80-3.04). This association was strongest for participants without a first-degree family history of CRC (P for interaction = 5.61 × 10-5). When we compared the highest with the lowest quartiles in this group, risk increased 4.3-fold for early-onset CRC (95% CI 3.61-5.01) vs 2.9-fold for late-onset CRC (95% CI 2.70-3.00). Sensitivity analyses were consistent with these findings. CONCLUSIONS: In an analysis of associations with CRC per standard deviation of PRS, we found the cumulative burden of CRC-associated common genetic variants to associate with early-onset cancer, and to be more strongly associated with early-onset than late-onset cancer, particularly in the absence of CRC family history. Analyses of PRS, along with environmental and lifestyle risk factors, might identify younger individuals who would benefit from preventive measures.

Adiposity increases estrogen receptor (ER)-positive postmenopausal breast cancer risk. While mechanisms underlying this relationship are uncertain, dysregulated sex-steroid hormone production and insulin signaling are likely pathways. Our aim was to quantify mediating effects of fasting insulin and free estradiol in the adiposity and ER-positive postmenopausal breast cancer association. We used data from a case–cohort study of sex hormones and insulin signaling nested within the Melbourne Collaborative Cohort Study. Eligible women, at baseline, were not diagnosed with cancer, were postmenopausal, did not use hormone therapy and had no history of diabetes or diabetes medication use. Women with ER-negative disease or breast cancer diagnosis within the first follow-up year were excluded. We analyzed the study as a cumulative sampling case–control study with 149 cases and 1,029 controls. Missing values for insulin and free estradiol were multiply imputed with chained equations. Interventional direct (IDE) and indirect (IIE) effects were estimated using regression-based multiple-mediator approach. For women with body mass index (BMI) >30 kg/m2 compared to women with BMI 18.5–25 kg/m2, the risk ratio (RR) of breast cancer was 1.75 (95% confidence interval [CI] 1.05–2.91). The estimated IDE (RR) not through the mediators was 1.03 (95% CI 0.43–2.48). Percentage mediated effect through free estradiol was 72% (IIE-RR 1.56; 95% CI 1.11–2.19). There was no evidence for an indirect effect through insulin (IIE-RR 1.12; 95% CI 0.68–1.84; 28% mediated). Our results suggest that circulating free estradiol plays an important mediating role in the adiposity–breast cancer relationship but does not explain all of the association. Refereed/Peer-reviewed

We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer. ispartof: JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE vol:113 issue:3 pages:329-337 ispartof: location:United States status: published

Few genetic risk factors have been demonstrated to be specifically associated with aggressive prostate cancer (PrCa). Here, we report a case-case study of PrCa comparing the prevalence of germline pathogenic/likely pathogenic (P/LP) genetic variants in 787 men with aggressive disease and 769 with nonaggressive disease. Overall, we observed P/LP variants in 11.4% of men with aggressive PrCa and 9.8% of men with nonaggressive PrCa (two-tailed Fisher's exact tests, P = .28). The proportion of BRCA2 and ATM P/LP variant carriers in men with aggressive PrCa exceeded that observed in men with nonaggressive PrCa; 18/787 carriers (2.3%) and 4/769 carriers (0.5%), P = .004, and 14/787 carriers (0.02%) and 5/769 carriers (0.01%), P = .06, respectively. Our findings contribute to the extensive international effort to interpret the genetic variation identified in genes included on gene-panel tests, for which there is currently an insufficient evidence-base for clinical translation in the context of PrCa risk.

PURPOSERisk-stratified breast cancer prevention requires accurate identification of women at sufficiently different levels of risk. We conducted a comprehensive evaluation of a model integrating classical risk factors and a recently developed 313-variant polygenic risk score (PRS) to predict breast cancer risk.METHODSFifteen prospective cohorts from six countries with 237,632 women (7,529 incident breast cancer patients) of European ancestry aged 19-75 years at baseline were included. Calibration of five-year risk was assessed by comparing predicted and observed proportions of cases overall and within risk categories. Risk stratification for women of European ancestry aged 50-70 years in those countries was evaluated by the proportion of women and future breast cancer cases crossing clinically-relevant risk thresholds.RESULTSThe model integrating classical risk factors and PRS accurately predicted five-year risk. For women younger than 50 years, median (range) expected-to-observed ratio across the cohorts was 0.94 (0.72 to 1.01) overall and 0.9 (0.7 to 1.4) at the highest risk decile. For women 50 years or older, these ratios were 1.04 (0.73 to 1.31) and 1.2 (0.7 to 1.6), respectively. The proportion of women in the general population identified above the 3% five-year risk threshold (used for recommending risk-reducing medications in the US) ranged from 7.0% in Germany (∼841,000 of 12 million) to 17.7% in the US (∼5.3 of 30 million). At this threshold, 14.7% of US women were re-classified by the addition of PRS to classical risk factors, identifying 12.2% additional future breast cancer cases.CONCLUSIONEvaluation across multiple prospective cohorts demonstrates that integrating a 313-SNP PRS into a risk model substantially improves its ability to stratify women of European ancestry for applying current breast cancer prevention guidelines.