Medicine (RMH) - Research Publications

Permanent URI for this collection

Search Results

Now showing 1 - 10 of 38
  • Item
    Thumbnail Image
    Weight is More Informative than Body Mass Index for Predicting Postmenopausal Breast Cancer Risk: Prospective Family Study Cohort (ProF-SC)
    Ye, Z ; Li, S ; Dite, GS ; Nguyen, TL ; MacInnis, RJ ; Andrulis, IL ; Buys, SS ; Daly, MB ; John, EM ; Kurian, AW ; Genkinger, JM ; Chung, WK ; Phillips, K-A ; Thorne, H ; Winship, IM ; Milne, RL ; Dugue, P-A ; Southey, MC ; Giles, GG ; Terry, MB ; Hopper, JL (AMER ASSOC CANCER RESEARCH, 2022-03)
    UNLABELLED: We considered whether weight is more informative than body mass index (BMI) = weight/height2 when predicting breast cancer risk for postmenopausal women, and if the weight association differs by underlying familial risk. We studied 6,761 women postmenopausal at baseline with a wide range of familial risk from 2,364 families in the Prospective Family Study Cohort. Participants were followed for on average 11.45 years and there were 416 incident breast cancers. We used Cox regression to estimate risk associations with log-transformed weight and BMI after adjusting for underlying familial risk. We compared model fits using the Akaike information criterion (AIC) and nested models using the likelihood ratio test. The AIC for the weight-only model was 6.22 units lower than for the BMI-only model, and the log risk gradient was 23% greater. Adding BMI or height to weight did not improve fit (ΔAIC = 0.90 and 0.83, respectively; both P = 0.3). Conversely, adding weight to BMI or height gave better fits (ΔAIC = 5.32 and 11.64; P = 0.007 and 0.0002, respectively). Adding height improved only the BMI model (ΔAIC = 5.47; P = 0.006). There was no evidence that the BMI or weight associations differed by underlying familial risk (P > 0.2). Weight is more informative than BMI for predicting breast cancer risk, consistent with nonadipose as well as adipose tissue being etiologically relevant. The independent but multiplicative associations of weight and familial risk suggest that, in terms of absolute breast cancer risk, the association with weight is more important the greater a woman's underlying familial risk. PREVENTION RELEVANCE: Our results suggest that the relationship between BMI and breast cancer could be due to a relationship between weight and breast cancer, downgraded by inappropriately adjusting for height; potential importance of anthropometric measures other than total body fat; breast cancer risk associations with BMI and weight are across a continuum.
  • Item
    Thumbnail Image
    Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing
    Southey, MC ; Dowty, JG ; Riaz, M ; Steen, JA ; Renault, A-L ; Tucker, K ; Kirk, J ; James, P ; Winship, I ; Pachter, N ; Poplawski, N ; Grist, S ; Park, DJ ; Pope, BJ ; Mahmood, K ; Hammet, F ; Mahmoodi, M ; Tsimiklis, H ; Theys, D ; Rewse, A ; Willis, A ; Morrow, A ; Speechly, C ; Harris, R ; Sebra, R ; Schadt, E ; Lacaze, P ; McNeil, JJ ; Giles, GG ; Milne, RL ; Hopper, JL ; Nguyen-Dumont, T (NATURE PORTFOLIO, 2021-12-09)
    Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing are urgently required. Most prior research has been based on women selected for high-risk features and more data is needed to make inference about breast cancer risk for women unselected for family history, an important consideration of population screening. We tested 1464 women diagnosed with breast cancer and 862 age-matched controls participating in the Australian Breast Cancer Family Study (ABCFS), and 6549 healthy, older Australian women enroled in the ASPirin in Reducing Events in the Elderly (ASPREE) study for rare germline variants using a 24-gene-panel. Odds ratios (ORs) were estimated using unconditional logistic regression adjusted for age and other potential confounders. We identified pathogenic variants in 11.1% of the ABCFS cases, 3.7% of the ABCFS controls and 2.2% of the ASPREE (control) participants. The estimated breast cancer OR [95% confidence interval] was 5.3 [2.1-16.2] for BRCA1, 4.0 [1.9-9.1] for BRCA2, 3.4 [1.4-8.4] for ATM and 4.3 [1.0-17.0] for PALB2. Our findings provide a population-based perspective to gene-panel testing for breast cancer predisposition and opportunities to improve predictors for identifying women who carry pathogenic variants in breast cancer predisposition genes.
  • Item
    Thumbnail Image
    Population-based estimates of age-specific cumulative risk of breast cancer for pathogenic variants in ATM
    Renault, A-L ; Dowty, JG ; Steen, JA ; Li, S ; Winship, IM ; Giles, GG ; Hopper, JL ; Southey, MC ; Nguyen-Dumont, T (BMC, 2022-04-01)
    BACKGROUND: Multigene panel tests for breast cancer predisposition routinely include ATM as it is now a well-established breast cancer predisposition gene. METHODS: We included ATM in a multigene panel test applied to the Australian Breast Cancer Family Registry (ABCFR), a population-based case-control-family study of breast cancer, with the purpose of estimating the prevalence and penetrance of heterozygous ATM pathogenic variants from the family data, using segregation analysis. RESULTS: The estimated breast cancer hazard ratio for carriers of pathogenic ATM variants in the ABCFR was 1.32 (95% confidence interval 0.45-3.87; P = 0.6). The estimated cumulative risk of breast cancer to age 80 years for heterozygous ATM pathogenic variant carriers was estimated to be 13% (95% CI 4.6-30). CONCLUSIONS: Although ATM has been definitively identified as a breast cancer predisposition gene, further evidence, such as variant-specific penetrance estimates, are needed to inform risk management strategies for carriers of pathogenic variants to increase the clinical utility of population testing of this gene.
  • Item
    Thumbnail Image
    Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models
    Li, SX ; Milne, RL ; Nguyen-Dumont, T ; English, DR ; Giles, GG ; Southey, MC ; Antoniou, AC ; Lee, A ; Winship, I ; Hopper, JL ; Terry, MB ; MacInnis, RJ (MDPI, 2021-10)
    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.
  • Item
    Thumbnail Image
    Mendelian randomisation study of smoking exposure in relation to breast cancer risk
    Park, HA ; Neumeyer, S ; Michailidou, K ; Bolla, MK ; Wang, Q ; Dennis, J ; Ahearn, TU ; Andrulis, IL ; Anton-Culver, H ; Antonenkova, NN ; Arndt, V ; Aronson, KJ ; Augustinsson, A ; Baten, A ; Freeman, LEB ; Becher, H ; Beckmann, MW ; Behrens, S ; Benitez, J ; Bermisheva, M ; Bogdanova, N ; Bojesen, SE ; Brauch, H ; Brenner, H ; Brucker, SY ; Burwinkel, B ; Campa, D ; Canzian, F ; Castelao, JE ; Chanock, SJ ; Chenevix-Trench, G ; Clarke, CL ; Conroy, DM ; Couch, FJ ; Cox, A ; Cross, SS ; Czene, K ; Daly, MB ; Devilee, P ; Dork, T ; Dos-Santos-Silva, I ; Dwek, M ; Eccles, DM ; Eliassen, AH ; Engel, C ; Eriksson, M ; Evans, DG ; Fasching, PA ; Flyger, H ; Fritschi, L ; Garcia-Closas, M ; Garcia-Saenz, JA ; Gaudet, MM ; Giles, GG ; Glendon, G ; Goldberg, MS ; Goldgar, DE ; Gonzalez-Neira, A ; Grip, M ; Guenel, P ; Hahnen, E ; Haiman, CA ; Hakansson, N ; Hall, P ; Hamann, U ; Han, S ; Harkness, EF ; Hart, SN ; He, W ; Heemskerk-Gerritsen, BAM ; Hopper, JL ; Hunter, DJ ; Jager, A ; Jakubowska, A ; John, EM ; Jung, A ; Kaaks, R ; Kapoor, PM ; Keeman, R ; Khusnutdinova, E ; Kitahara, CM ; Koppert, LB ; Koutros, S ; Kristensen, VN ; Kurian, AW ; Lacey, J ; Lambrechts, D ; LeMarchand, L ; Lo, W-Y ; Mannermaa, A ; Manoochehri, M ; Margolin, S ; ElenaMartinez, M ; Mavroudis, D ; Meindl, A ; Menon, U ; Milne, RL ; Muranen, TA ; Nevanlinna, H ; Newman, WG ; Nordestgaard, BG ; Offit, K ; Olshan, AF ; Olsson, H ; Park-Simon, T-W ; Peterlongo, P ; Peto, J ; Plaseska-Karanfilska, D ; Presneau, N ; Radice, P ; Rennert, G ; Rennert, HS ; Romero, A ; Saloustros, E ; Sawyer, EJ ; Schmidt, MK ; Schmutzler, RK ; Schoemaker, MJ ; Schwentner, L ; Scott, C ; Shah, M ; Shu, X-O ; Simard, J ; Smeets, A ; Southey, MC ; Spinelli, JJ ; Stevens, V ; Swerdlow, AJ ; Tamimi, RM ; Tapper, WJ ; Taylor, JA ; Terry, MB ; Tomlinson, I ; Troester, MA ; Truong, T ; Vachon, CM ; van Veen, EM ; Vijai, J ; Wang, S ; Wendt, C ; Winqvist, R ; Wolk, A ; Ziogas, A ; Dunning, AM ; Pharoah, PDP ; Easton, DF ; Zheng, W ; Kraft, P ; Chang-Claude, J (SPRINGERNATURE, 2021-10-12)
    BACKGROUND: Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk. METHODS: We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy. RESULTS: Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07-1.30, P = 0.11 × 10-2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78-1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect. CONCLUSION: Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.
  • Item
    Thumbnail Image
    DNA Methylation Signatures and the Contribution of Age-Associated Methylomic Drift to Carcinogenesis in Early-Onset Colorectal Cancer
    Joo, JE ; Clendenning, M ; Wong, EM ; Rosty, C ; Mahmood, K ; Georgeson, P ; Winship, IM ; Preston, SG ; Win, AK ; Dugue, P-A ; Jayasekara, H ; English, D ; Macrae, FA ; Hopper, JL ; Jenkins, MA ; Milne, RL ; Giles, GG ; Southey, MC ; Buchanan, DD (MDPI, 2021-06)
    We investigated aberrant DNA methylation (DNAm) changes and the contribution of ageing-associated methylomic drift and age acceleration to early-onset colorectal cancer (EOCRC) carcinogenesis. Genome-wide DNAm profiling using the Infinium HM450K on 97 EOCRC tumour and 54 normal colonic mucosa samples was compared with: (1) intermediate-onset CRC (IOCRC; diagnosed between 50-70 years; 343 tumour and 35 normal); and (2) late-onset CRC (LOCRC; >70 years; 318 tumour and 40 normal). CpGs associated with age-related methylation drift were identified using a public dataset of 231 normal mucosa samples from people without CRC. DNAm-age was estimated using epiTOC2. Common to all three age-of-onset groups, 88,385 (20% of all CpGs) CpGs were differentially methylated between tumour and normal mucosa. We identified 234 differentially methylated genes that were unique to the EOCRC group; 13 of these DMRs/genes were replicated in EOCRC compared with LOCRCs from TCGA. In normal mucosa from people without CRC, we identified 28,154 CpGs that undergo ageing-related DNAm drift, and of those, 65% were aberrantly methylated in EOCRC tumours. Based on the mitotic-based DNAm clock epiTOC2, we identified age acceleration in normal mucosa of people with EOCRC compared with normal mucosa from the IOCRC, LOCRC groups (p = 3.7 × 10-16) and young people without CRC (p = 5.8 × 10-6). EOCRC acquires unique DNAm alterations at 234 loci. CpGs associated with ageing-associated drift were widely affected in EOCRC without needing the decades-long accrual of DNAm drift as commonly seen in intermediate- and late-onset CRCs. Accelerated ageing in normal mucosa from people with EOCRC potentially underlies the earlier age of diagnosis in CRC carcinogenesis.
  • Item
    Thumbnail Image
    Prospective Evaluation of the Addition of Polygenic Risk Scores to Breast Cancer Risk Models
    Li, SX ; Milne, RL ; Nguyen-Dumont, T ; Wang, X ; English, DR ; Giles, GG ; Southey, MC ; Antoniou, AC ; Lee, A ; Li, S ; Winship, I ; Hopper, JL ; Terry, MB ; MacInnis, RJ (OXFORD UNIV PRESS, 2021-06)
    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 (<1.7%) and overpredicted risk (E/O = 1.40, 95% CI = 1.18 to 1.67) in the highest risk category (≥5%), using the Hosmer-Lemeshow test for calibration in quantiles of risk and a 2-sided P value less than  .001. BOADICEA underpredicted risk (E/O = 0.82, 95% CI = 0.67 to 0.99) in the second highest risk category (3.4%-5%); the Hosmer-Lemeshow test and a 2-sided P value was equal to .02. 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.
  • Item
    Thumbnail Image
    Population-Based Estimates of the Age-Specific Cumulative Risk of Breast Cancer for Pathogenic Variants in CHEK2: Findings from the Australian Breast Cancer Family Registry
    Nguyen-Dumont, T ; Dowty, JG ; Steen, JA ; Renault, A-L ; Hammet, F ; Mahmoodi, M ; Theys, D ; Rewse, A ; Tsimiklis, H ; Winship, IM ; Giles, GG ; Milne, RL ; Hopper, JL ; Southey, MC (MDPI, 2021-03)
    Case-control studies of breast cancer have consistently shown that pathogenic variants in CHEK2 are associated with about a 3-fold increased risk of breast cancer. Information about the recurrent protein-truncating variant CHEK2 c.1100delC dominates this estimate. There have been no formal estimates of age-specific cumulative risk of breast cancer for all CHEK2 pathogenic (including likely pathogenic) variants combined. We conducted a population-based case-control-family study of pathogenic CHEK2 variants (26 families, 1071 relatives) and estimated the age-specific cumulative risk of breast cancer using segregation analysis. The estimated hazard ratio for carriers of pathogenic CHEK2 variants (combined) was 4.9 (95% CI 2.5-9.5) relative to non-carriers. The HR for carriers of the CHEK2 c.1100delC variant was estimated to be 3.5 (95% CI 1.02-11.6) and the HR for carriers of all other CHEK2 variants combined was estimated to be 5.7 (95% CI 2.5-12.9). The age-specific cumulative risk of breast cancer was estimated to be 18% (95% CI 11-30%) and 33% (95% CI 21-48%) to age 60 and 80 years, respectively. These findings provide important information for the clinical management of breast cancer risk for women carrying pathogenic variants in CHEK2.
  • Item
    Thumbnail Image
    CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers
    Johnson, N ; Maguire, S ; Morra, A ; Kapoor, PM ; Tomczyk, K ; Jones, ME ; Schoemaker, MJ ; Gilham, C ; Bolla, MK ; Wang, Q ; Dennis, J ; Ahearn, TU ; Andrulis, IL ; Anton-Culver, H ; Antonenkova, NN ; Arndt, V ; Aronson, KJ ; Augustinsson, A ; Baynes, C ; Freeman, LEB ; Beckmann, MW ; Benitez, J ; Bermisheva, M ; Blomqvist, C ; Boeckx, B ; Bogdanova, NV ; Bojesen, SE ; Brauch, H ; Brenner, H ; Burwinkel, B ; Campa, D ; Canzian, F ; Castelao, JE ; Chanock, SJ ; Chenevix-Trench, G ; Clarke, CL ; Conroy, DM ; Couch, FJ ; Cox, A ; Cross, SS ; Czene, K ; Doerk, T ; Eliassen, AH ; Engel, C ; Evans, DG ; Fasching, PA ; Figueroa, J ; Floris, G ; Flyger, H ; Gago-Dominguez, M ; Gapstur, SM ; Garcia-Closas, M ; Gaudet, MM ; Giles, GG ; Goldberg, MS ; Gonzalez-Neira, A ; Guenel, P ; Hahnen, E ; Haiman, CA ; Hakansson, N ; Hall, P ; Hamann, U ; Harrington, PA ; Hart, SN ; Hooning, MJ ; Hopper, JL ; Howell, A ; Hunter, DJ ; Jager, A ; Jakubowska, A ; John, EM ; Kaaks, R ; Keeman, R ; Khusnutdinova, E ; Kitahara, CM ; Kosma, V-M ; Koutros, S ; Kraft, P ; Kristensen, VN ; Kurian, AW ; Lambrechts, D ; Le Marchand, L ; Linet, M ; Lubinski, J ; Mannermaa, A ; Manoukian, S ; Margolin, S ; Martens, JWM ; Mavroudis, D ; Mayes, R ; Meindl, A ; Milne, RL ; Neuhausen, SL ; Nevanlinna, H ; Newman, WG ; Nielsen, SF ; Nordestgaard, BG ; Obi, N ; Olshan, AF ; Olson, JE ; Olsson, H ; Orban, E ; Park-Simon, T-W ; Peterlongo, P ; Plaseska-Karanfilska, D ; Pylkas, K ; Rennert, G ; Rennert, HS ; Ruddy, KJ ; Saloustros, E ; Sandler, DP ; Sawyer, EJ ; Schmutzler, RK ; Scott, C ; Shu, X-O ; Simard, J ; Smichkoska, S ; Sohn, C ; Southey, MC ; Spinelli, JJ ; Stone, J ; Tamimi, RM ; Taylor, JA ; Tollenaar, RAEM ; Tomlinson, I ; Troester, MA ; Truong, T ; Vachon, CM ; van Veen, EM ; Wang, SS ; Weinberg, CR ; Wendt, C ; Wildiers, H ; Winqvist, R ; Wolk, A ; Zheng, W ; Ziogas, A ; Dunning, AM ; Pharoah, PDP ; Easton, DF ; Howie, AF ; Peto, J ; dos-Santos-Silva, I ; Swerdlow, AJ ; Chang-Claude, J ; Schmidt, MK ; Orr, N ; Fletcher, O (SPRINGERNATURE, 2021-02-16)
    BACKGROUND: Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk. METHODS: We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry. RESULTS: For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10-18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10-8). CONCLUSIONS: The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.
  • Item
    Thumbnail Image
    Morphological predictors of BRCA1 germline mutations in young women with breast cancer
    Southey, MC ; Ramus, SJ ; Dowty, JG ; Smith, LD ; Tesoriero, AA ; Wong, EEM ; Dite, GS ; Jenkins, MA ; Byrnes, GB ; Winship, I ; Phillips, K-A ; Giles, GG ; Hopper, JL (NATURE PUBLISHING GROUP, 2011-03-15)
    BACKGROUND: Knowing a young woman with newly diagnosed breast cancer has a germline BRCA1 mutation informs her clinical management and that of her relatives. We sought an optimal strategy for identifying carriers using family history, breast cancer morphology and hormone receptor status data. METHODS: We studied a population-based sample of 452 Australian women with invasive breast cancer diagnosed before age 40 years for whom we conducted extensive germline mutation testing (29 carried a BRCA1 mutation) and a systematic pathology review, and collected three-generational family history and tumour ER and PR status. Predictors of mutation status were identified using multiple logistic regression. Areas under receiver operator characteristic (ROC) curves were estimated using five-fold stratified cross-validation. RESULTS: The probability of being a BRCA1 mutation carrier increased with number of selected histology features even after adjusting for family history and ER and PR status (P<0.0001). From the most parsimonious multivariate model, the odds ratio for being a carrier were: 9.7 (95% confidence interval: 2.6-47.0) for trabecular growth pattern (P=0.001); 7.8 (2.7-25.7) for mitotic index over 50 mitoses per 10 high-powered field (P=0.0003); and 2.7 (1.3-5.9) for each first-degree relative with breast cancer diagnosed before age 60 years (P=0.01).The area under the ROC curve was 0.87 (0.83-0.90). CONCLUSION: Pathology review, with attention to a few specific morphological features of invasive breast cancers, can identify almost all BRCA1 germline mutation carriers among women with early-onset breast cancer without taking into account family history.