Melbourne School of Population and Global Health - Research Publications

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    Circulating free testosterone and risk of aggressive prostate cancer: Prospective and Mendelian randomisation analyses in international consortia
    Watts, EL ; Perez-Cornago, A ; Fensom, GK ; Smith-Byrne, K ; Noor, U ; Andrews, CD ; Gunter, MJ ; Holmes, M ; Martin, RM ; Tsilidis, KK ; Albanes, D ; Barricarte, A ; Bueno-de-Mesquita, B ; Chen, C ; Cohn, BA ; Dimou, NL ; Ferrucci, L ; Flicker, L ; Freedman, ND ; Giles, GG ; Giovannucci, EL ; Goodman, GE ; Haiman, CA ; Hankey, GJ ; Huang, J ; Huang, W-Y ; Hurwitz, LM ; Kaaks, R ; Knekt, P ; Kubo, T ; Langseth, H ; Laughlin, G ; Le Marchand, L ; Luostarinen, T ; MacInnis, RJ ; Maenpaa, HO ; Mannisto, S ; Metter, JE ; Mikami, K ; Mucci, LA ; Olsen, AW ; Ozasa, K ; Palli, D ; Penney, KL ; Platz, EA ; Rissanen, H ; Sawada, N ; Schenk, JM ; Stattin, P ; Tamakoshi, A ; Thysell, E ; Tsai, CJ ; Tsugane, S ; Vatten, L ; Weiderpass, E ; Weinstein, SJ ; Wilkens, LR ; Yeap, BB ; Allen, NE ; Key, TJ ; Travis, RC (WILEY, 2022-06-07)
    Previous studies had limited power to assess the associations of testosterone with aggressive disease as a primary endpoint. Further, the association of genetically predicted testosterone with aggressive disease is not known. We investigated the associations of calculated free and measured total testosterone and sex hormone-binding globulin (SHBG) with aggressive, overall and early-onset prostate cancer. In blood-based analyses, odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression from prospective analysis of biomarker concentrations in the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group (up to 25 studies, 14 944 cases and 36 752 controls, including 1870 aggressive prostate cancers). In Mendelian randomisation (MR) analyses, using instruments identified using UK Biobank (up to 194 453 men) and outcome data from PRACTICAL (up to 79 148 cases and 61 106 controls, including 15 167 aggressive cancers), ORs were estimated using the inverse-variance weighted method. Free testosterone was associated with aggressive disease in MR analyses (OR per 1 SD = 1.23, 95% CI = 1.08-1.40). In blood-based analyses there was no association with aggressive disease overall, but there was heterogeneity by age at blood collection (OR for men aged <60 years 1.14, CI = 1.02-1.28; Phet  = .0003: inverse association for older ages). Associations for free testosterone were positive for overall prostate cancer (MR: 1.20, 1.08-1.34; blood-based: 1.03, 1.01-1.05) and early-onset prostate cancer (MR: 1.37, 1.09-1.73; blood-based: 1.08, 0.98-1.19). SHBG and total testosterone were inversely associated with overall prostate cancer in blood-based analyses, with null associations in MR analysis. Our results support free testosterone, rather than total testosterone, in the development of prostate cancer, including aggressive subgroups.
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    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, 2022-03-01)
    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.
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    Circulating insulin-like growth factors and risks of overall, aggressive and early-onset prostate cancer: a collaborative analysis of 20 prospective studies and Mendelian randomization analysis
    Watts, EL ; Perez-Cornago, A ; Fensom, GK ; Smith-Byrne, K ; Noor, U ; Andrews, CD ; Gunter, MJ ; Holmes, M ; Martin, RM ; Tsilidis, KK ; Albanes, D ; Barricarte, A ; Bueno-de-Mesquita, HB ; Cohn, BA ; Deschasaux-Tanguy, M ; Dimou, NL ; Ferrucci, L ; Flicker, L ; Freedman, ND ; Giles, GG ; Giovannucci, EL ; Haiman, CA ; Hankey, GJ ; Holly, JMP ; Huang, J ; Huang, W-Y ; Hurwitz, LM ; Kaaks, R ; Kubo, T ; Le Marchand, L ; MacInnis, RJ ; Mannisto, S ; Metter, EJ ; Mikami, K ; Mucci, LA ; Olsen, AW ; Ozasa, K ; Palli, D ; Penney, KL ; Platz, EA ; Pollak, MN ; Roobol, MJ ; Schaefer, CA ; Schenk, JM ; Stattin, P ; Tamakoshi, A ; Thysell, E ; Tsai, CJ ; Touvier, M ; Van Den Eeden, SK ; Weiderpass, E ; Weinstein, SJ ; Wilkens, LR ; Yeap, BB ; Allen, NE ; Key, TJ ; Travis, RC (OXFORD UNIV PRESS, 2022-06-21)
    BACKGROUND: Previous studies had limited power to assess the associations of circulating insulin-like growth factors (IGFs) and IGF-binding proteins (IGFBPs) with clinically relevant prostate cancer as a primary endpoint, and the association of genetically predicted IGF-I with aggressive prostate cancer is not known. We aimed to investigate the associations of IGF-I, IGF-II, IGFBP-1, IGFBP-2 and IGFBP-3 concentrations with overall, aggressive and early-onset prostate cancer. METHODS: Prospective analysis of biomarkers using the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group dataset (up to 20 studies, 17 009 prostate cancer cases, including 2332 aggressive cases). Odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression. For IGF-I, two-sample Mendelian randomization (MR) analysis was undertaken using instruments identified using UK Biobank (158 444 men) and outcome data from PRACTICAL (up to 85 554 cases, including 15 167 aggressive cases). Additionally, we used colocalization to rule out confounding by linkage disequilibrium. RESULTS: In observational analyses, IGF-I was positively associated with risks of overall (OR per 1 SD = 1.09: 95% CI 1.07, 1.11), aggressive (1.09: 1.03, 1.16) and possibly early-onset disease (1.11: 1.00, 1.24); associations were similar in MR analyses (OR per 1 SD = 1.07: 1.00, 1.15; 1.10: 1.01, 1.20; and 1.13; 0.98, 1.30, respectively). Colocalization also indicated a shared signal for IGF-I and prostate cancer (PP4: 99%). Men with higher IGF-II (1.06: 1.02, 1.11) and IGFBP-3 (1.08: 1.04, 1.11) had higher risks of overall prostate cancer, whereas higher IGFBP-1 was associated with a lower risk (0.95: 0.91, 0.99); these associations were attenuated following adjustment for IGF-I. CONCLUSIONS: These findings support the role of IGF-I in the development of prostate cancer, including for aggressive disease.
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    Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction
    Li, S ; MacInnis, RJ ; Lee, A ; Nguyen-Dumont, T ; Dorling, L ; Carvalho, S ; Dite, GS ; Shah, M ; Luccarini, C ; Wang, Q ; Milne, RL ; Jenkins, MA ; Giles, GG ; Dunning, AM ; Pharoah, PDP ; Southey, MC ; Easton, DF ; Hopper, JL ; Antoniou, AC (CELL PRESS, 2022-10-06)
    Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20-29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%-5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%-95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%-1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20-29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age.
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    Two-stage Study of Familial Prostate Cancer by Whole-exome Sequencing and Custom Capture Identifies 10 Novel Genes Associated with the Risk of Prostate Cancer
    Schaid, DJ ; McDonnell, SK ; FitzGerald, LM ; DeRycke, L ; Fogarty, Z ; Giles, GG ; MacInnis, RJ ; Southey, MC ; Nguyen-Dumont, T ; Cancel-Tassin, G ; Cussenot, O ; Whittemore, AS ; Sieh, W ; Ioannidis, NM ; Hsieh, C-L ; Stanford, JL ; Schleutker, J ; Cropp, CD ; Carpten, J ; Hoegel, J ; Eeles, R ; Kote-Jarai, Z ; Ackerman, MJ ; Klein, CJ ; Mandal, D ; Cooney, KA ; Bailey-Wilson, JE ; Helfand, B ; Catalona, WJ ; Wiklund, F ; Riska, S ; Bahetti, S ; Larson, MC ; Albright, LC ; Teerlink, C ; Xu, J ; Isaacs, W ; Ostrander, EA ; Thibodeau, SN (ELSEVIER, 2021-02-11)
    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.
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    Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women.
    Wang, X ; Kapoor, PM ; Auer, PL ; Dennis, J ; Dunning, AM ; Wang, Q ; Lush, M ; Michailidou, K ; Bolla, MK ; Aronson, KJ ; Murphy, RA ; Brooks-Wilson, A ; Lee, DG ; Cordina-Duverger, E ; Guénel, P ; Truong, T ; Mulot, C ; Teras, LR ; Patel, AV ; Dossus, L ; Kaaks, R ; Hoppe, R ; Lo, W-Y ; Brüning, T ; Hamann, U ; Czene, K ; Gabrielson, M ; Hall, P ; Eriksson, M ; Jung, A ; Becher, H ; Couch, FJ ; Larson, NL ; Olson, JE ; Ruddy, KJ ; Giles, GG ; MacInnis, RJ ; Southey, MC ; Le Marchand, L ; Wilkens, LR ; Haiman, CA ; Olsson, H ; Augustinsson, A ; Krüger, U ; Wagner, P ; Scott, C ; Winham, SJ ; Vachon, CM ; Perou, CM ; Olshan, AF ; Troester, MA ; Hunter, DJ ; Eliassen, HA ; Tamimi, RM ; Brantley, K ; Andrulis, IL ; Figueroa, J ; Chanock, SJ ; Ahearn, TU ; García-Closas, M ; Evans, GD ; Newman, WG ; van Veen, EM ; Howell, A ; Wolk, A ; Håkansson, N ; Anton-Culver, H ; Ziogas, A ; Jones, ME ; Orr, N ; Schoemaker, MJ ; Swerdlow, AJ ; Kitahara, CM ; Linet, M ; Prentice, RL ; Easton, DF ; Milne, RL ; Kraft, P ; Chang-Claude, J ; Lindström, S (Springer Science and Business Media LLC, 2022-04-13)
    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. 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 < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. 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-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) 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. 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.
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    Common variants in breast cancer risk loci predispose to distinct tumor subtypes
    Ahearn, TU ; Zhang, H ; Michailidou, K ; Milne, RL ; Bolla, MK ; Dennis, J ; Dunning, AM ; Lush, M ; Wang, Q ; Andrulis, IL ; Anton-Culver, H ; Arndt, V ; Aronson, KJ ; Auer, PL ; Augustinsson, A ; Baten, A ; Becher, H ; Behrens, S ; Benitez, J ; Bermisheva, M ; Blomqvist, C ; Bojesen, SE ; Bonanni, B ; Borresen-Dale, A-L ; Brauch, H ; Brenner, H ; Brooks-Wilson, A ; Bruening, T ; Burwinkel, B ; Buys, SS ; Canzian, F ; Castelao, JE ; Chang-Claude, J ; Chanock, SJ ; Chenevix-Trench, G ; Clarke, CL ; Collee, JM ; Cox, A ; Cross, SS ; Czene, K ; Daly, MB ; Devilee, P ; Dork, T ; Dwek, M ; Eccles, DM ; Evans, DG ; Fasching, PA ; Figueroa, J ; Floris, G ; Gago-Dominguez, M ; Gapstur, SM ; Garcia-Saenz, JA ; Gaudet, MM ; Giles, GG ; Goldberg, MS ; Gonzalez-Neira, A ; Alnaes, GIG ; Grip, M ; Guenel, P ; Haiman, CA ; Hall, P ; Hamann, U ; Harkness, EF ; Heemskerk-Gerritsen, BAM ; Holleczek, B ; Hollestelle, A ; Hooning, MJ ; Hoover, RN ; Hopper, JL ; Howell, A ; Jakimovska, M ; Jakubowska, A ; John, EM ; Jones, ME ; Jung, A ; Kaaks, R ; Kauppila, S ; Keeman, R ; Khusnutdinova, E ; Kitahara, CM ; Ko, Y-D ; Koutros, S ; Kristensen, VN ; Kruger, U ; Kubelka-Sabit, K ; Kurian, AW ; Kyriacou, K ; Lambrechts, D ; Lee, DG ; Lindblom, A ; Linet, M ; Lissowska, J ; Llaneza, A ; Lo, W-Y ; MacInnis, RJ ; Mannermaa, A ; Manoochehri, M ; Margolin, S ; Martinez, ME ; McLean, C ; Meindl, A ; Menon, U ; Nevanlinna, H ; Newman, WG ; Nodora, J ; Offit, K ; Olsson, H ; Orr, N ; Park-Simon, T-W ; Patel, A ; Peto, J ; Pita, G ; Plaseska-Karanfilska, D ; Prentice, R ; Punie, K ; Pylkas, K ; Radice, P ; Rennert, G ; Romero, A ; Ruediger, T ; Saloustros, E ; Sampson, S ; Sandler, DP ; Sawyer, EJ ; Schmutzler, RK ; Schoemaker, MJ ; Schottker, B ; Sherman, ME ; Shu, X-O ; Smichkoska, S ; Southey, MC ; Spinelli, JJ ; Swerdlow, AJ ; Tamimi, RM ; Tapper, WJ ; Taylor, JA ; Teras, LR ; Terry, MB ; Torres, D ; Troester, MA ; Vachon, CM ; van Deurzen, CHM ; van Veen, EM ; Wagner, P ; Weinberg, CR ; Wendt, C ; Wesseling, J ; Winqvist, R ; Wolk, A ; Yang, XR ; Zheng, W ; Couch, FJ ; Simard, J ; Kraft, P ; Easton, DF ; Pharoah, PDP ; Schmidt, MK ; Garcia-Closas, M ; Chatterjee, N (BMC, 2022-01-04)
    BACKGROUND: Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. METHODS: Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. RESULTS: Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. CONCLUSION: This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.
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    Recreational Physical Activity and Outcomes After Breast Cancer in Women at High Familial Risk
    Kehm, RD ; MacInnis, RJ ; John, EM ; Liao, Y ; Kurian, AW ; Genkinger, JM ; Knight, JA ; Colonna, S ; Chung, WK ; Milne, R ; Zeinomar, N ; Dite, GS ; Southey, MC ; Giles, GG ; Mclachlan, S-A ; Whitaker, KD ; Friedlander, ML ; Weideman, PC ; Glendon, G ; Nesci, S ; Investigators, K ; Phillips, K-A ; Andrulis, IL ; Buys, SS ; Daly, MB ; Hopper, JL ; Terry, MB (OXFORD UNIV PRESS, 2021-12-08)
    Background: Recreational physical activity (RPA) is associated with improved survival after breast cancer (BC) in average-risk women, but evidence is limited for women who are at increased familial risk because of a BC family history or BRCA1 and BRCA2 pathogenic variants (BRCA1/2 PVs). Methods: We estimated associations of RPA (self-reported average hours per week within 3 years of BC diagnosis) with all-cause mortality and second BC events (recurrence or new primary) after first invasive BC in women in the Prospective Family Study Cohort (n = 4610, diagnosed 1993-2011, aged 22-79 years at diagnosis). We fitted Cox proportional hazards regression models adjusted for age at diagnosis, demographics, and lifestyle factors. We tested for multiplicative interactions (Wald test statistic for cross-product terms) and additive interactions (relative excess risk due to interaction) by age at diagnosis, body mass index, estrogen receptor status, stage at diagnosis, BRCA1/2 PVs, and familial risk score estimated from multigenerational pedigree data. Statistical tests were 2-sided. Results: We observed 1212 deaths and 473 second BC events over a median follow-up from study enrollment of 11.0 and 10.5 years, respectively. After adjusting for covariates, RPA (any vs none) was associated with lower all-cause mortality of 16.1% (95% confidence interval [CI] = 2.4% to 27.9%) overall, 11.8% (95% CI = -3.6% to 24.9%) in women without BRCA1/2 PVs, and 47.5% (95% CI = 17.4% to 66.6%) in women with BRCA1/2 PVs (RPA*BRCA1/2 multiplicative interaction P = .005; relative excess risk due to interaction = 0.87, 95% CI = 0.01 to 1.74). RPA was not associated with risk of second BC events. Conclusion: Findings support that RPA is associated with lower all-cause mortality in women with BC, particularly in women with BRCA1/2 PVs.
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    Alcohol and tobacco use and risk of multiple myeloma: A case‐control study
    Cheah, S ; Bassett, JK ; Bruinsma, FJ ; Cozen, W ; Hopper, JL ; Jayasekara, H ; Joshua, D ; MacInnis, RJ ; Prince, HM ; Vajdic, CM ; Leeuwen, MT ; Doo, NW ; Harrison, SJ ; English, DR ; Giles, GG ; Milne, RL (Wiley, 2022-02)
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    Physical activity and glioma: a case-control study with follow-up for survival
    Basiri, Z ; Yang, Y ; Bruinsma, FJ ; Nowak, AK ; McDonald, KL ; Drummond, KJ ; Rosenthal, MA ; Koh, E-S ; Harrup, R ; Hovey, E ; Joseph, D ; Benke, G ; Leonard, R ; MacInnis, RJ ; Milne, RL ; Giles, GG ; Vajdic, CM ; Lynch, BM (SPRINGER, 2022-02-20)
    PURPOSE: High-grade disease accounts for ~ 70% of all glioma, and has a high mortality rate. Few modifiable exposures are known to be related to glioma risk or mortality. METHODS: We examined associations between lifetime physical activity and physical activity at different ages (15-18 years, 19-29 years, 30-39 years, last 10 years) with the risk of glioma diagnosis, using data from a hospital-based family case-control study (495 cases; 371 controls). We followed up cases over a median of 25 months to examine whether physical activity was associated with all-cause mortality. Physical activity and potential confounders were assessed by self-administered questionnaire. We examined associations between physical activity (metabolic equivalent [MET]-h/wk) and glioma risk using unconditional logistic regression and with all-cause mortality in cases using Cox regression. RESULTS: We noted a reduced risk of glioma for the highest (≥ 47 MET-h/wk) versus lowest (< 24 METh/wk) category of physical activity for lifetime activity (OR = 0.58, 95% CI: 0.38-0.89) and at 15-18 years (OR = 0.57, 95% CI: 0.39-0.83). We did not observe any association between physical activity and all-cause mortality (HR for lifetime physical activity = 0.91, 95% CI: 0.64-1.29). CONCLUSION: Our findings are consistent with previous research that suggested physical activity during adolescence might be protective against glioma. Engaging in physical activity during adolescence has many health benefits; this health behavior may also offer protection against glioma.