BACKGROUND: Familial risks by proband status and age are useful for clinical counseling, and they can be used to calculate population-attributable fractions (PAFs), which show the proportion of disease that could be prevented if the cause could be removed. METHODS: The authors used the nationwide Swedish Family-Cancer Database on 10.2 million individuals and 182,104 fathers and 3710 sons with medically verified prostate carcinoma to calculate age specific familial standardized incidence ratios (SIRs) with 95% confidence intervals (95%CI) and familial PAFs for prostate carcinoma in sons ages 0-66 years. RESULTS: The incidence of prostate carcinoma was doubled between the years 1961 and 1998. The familial SIRs for prostate carcinoma were 2.38 (95%CI, 2.18-2.59) for men with prostate carcinoma in the father only, 3.75 (95%CI, 2.73-4.95) for men with prostate carcinoma in a brother only, and 9.44 (95%CI, 5.76-14.03) for men with prostate carcinoma in both a father and a brother. The corresponding familial PAFs were 8.86%, 1.78%, and 0.99%, respectively, yielding a total PAF of 11.63%. Age specific risks were shown for the same proband histories. The SIR was 8.05 for prostate carcinoma before age 55 if a brother had been diagnosed before that age. If, in addition, a father was diagnosed at any age, then the SIR was 33.09. CONCLUSIONS: The authors recommend that having a brother who is diagnosed with prostate carcinoma before age 55 years or having a brother and father who are diagnosed at any age are indications to screen for prostate carcinoma. The familial PAF of prostate carcinoma among a population of sons ages 0-66 years was 11.63%.
The authors used cancer registry data to assess the incidence rate of second primary cancers among chronic myeloid leukemia (CML) patients and the long-term survival of CML patients before the introduction of tyrosine kinase inhibitors. In the Swedish Cancer Registry, the authors identified 2,753 adult CML patients diagnosed between 1970 and 1995 who were followed through December 2007. Standardized incidence ratios (SIRs) and relative survival ratios were computed. With a total of 145 subsequent primary malignancies, an increased incidence rate of second malignancy was found for stomach cancer (SIR = 2.76, 95% confidence interval (CI): 1.33, 5.08), skin cancer (SIR = 5.36, 95% CI: 3.18, 8.47), urogenital tract cancer (SIR = 1.61, 95% CI: 1.15, 2.21), and lymphoid leukemia (SIR = 5.53, 95% CI: 1.79, 12.89). Long-term relative survival figures showed that CML was related, in the era prior to the introduction of imatinib, to a very steep decline in survival (2 years from diagnosis, relative survival = 51%, 95% CI: 49, 53). This was in spite of a marginal improvement after 1985, possibly related to the introduction of interferon-a for treatment. These estimates constitute a relevant reference for future studies and a benchmark for comparisons with prognosis in CML patients after chronic use of tyrosine kinase inhibitors.
Large childhood body size has been consistently shown to be associated with decreased breast cancer risk. However, it is important to consider the effects of a large childhood body size on other adult diseases. It is not clear if the associations between childhood body size and adult diseases will persist if they later attain healthy weight. The associations between body size at age 7 and 17 adverse outcomes in adulthood were examined using Cox models in a Swedish study of 65,057 women. Large body size at age 7, when compared to small body size, was associated with decreased risk for breast cancer (HR [95% CI]: 0.81 [0.70-0.93]) and increased risks for anorexia (2.13 [1.63-2.77]) and bulimia (1.91 [1.35-2.70]). Neither adjusting for adult BMI nor restricting the dataset to lean adults (BMI?
Affiliations of authors: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Sciences, Rockville, MD (XRY, SC, JF, LBr, MES, MG-C); Section of Epidemiology and Genetics, Institute of Cancer Research, Sutton, Surrey, UK (MG-C); Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany (JC-C, RH, AV); Department of Health Sciences Research (ELG, FJC, JEO, VC, ZF, MKo, CV); Department of Laboratory Medicine and Pathology (FJC, XW), Mayo Clinic, Rochester, MN; Department of Obstetrics and Gynecology (HN, THe), Department of Clinical Genetics (KA), Department of Pathology (PHe), and Department of Oncology (CB), Helsinki University Central Hospital, Helsinki, Finland; Genetic and Molecular Epidemiology Group (RLM), Human Cancer Genetic Group (JB), Spanish National Cancer Research Centre (CNIO), Madrid, Spain; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY (MGa); Amsterdam Breast Cancer Study, Netherlands Cancer Institute, Amsterdam, the Netherlands (MKS, AB, LJVV, FEvL); Institute for Cancer Studies, Department of Oncology (AC, DC,HEC), Academic Unit of Pathology (SCC), Academic Unit of Surgical Oncology, Department of Oncology (SPB, MWRR), University of Sheffield Medical School, Sheffield, UK; Division of Hematology and Oncology, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA (PAF); Department of Gynecology and Obstetrics, (MWB, SBW, SMJ, CRL), Institute of Pathology (AHa, DLW), University Breast Center Franconia, University Breast Center, University Hospital Erlangen, Erlangen, Germany; The Queensland Institute of Medical Research Post Office, Royal Brisbane Hospital, Herston, Queensland, Australia (ABS, HH, GC-T); Department of Oncology, University of Cambridge, Cambridge, UK (FB, KD, MKH, DE, PP, MG-C); Department of Medical Biometrics and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (DF-J, JH); Department of Pathology, University Hospital, Heidelberg, Germany (PS); Department of Cancer Epidemiology and Prevention, Cancer Center and M. Sklodowska-Curie Institute of Oncology, Warsaw, Poland (JLi); Department of Occupational and Environmental Epidemiology Nofer Institute of Occupational Medicine, Lodz, Poland (BP); Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden (PHa, KC, KH, HD); Human Genetics, Genome Institute of Singapore, Singapore, Singapore (JLi); Ontario Cancer Genetics Network (OCGN), Cancer Care Ontario, Toronto, ON, Canada (ILA, GG, NW); Departments of Molecular Genetics and Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada (ILA); Dalla Lana School of Public Health, University of Toronto, Prosserman Centre for Health Research, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, ON, Canada (JAK); Keenan Research Centre, Li Ka Shing Knowledge Institute of St. Michael's Hospital, and Laboratory Medicine and Pathobiology (AMM), Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, and Laboratory Medicine and Pathobiology (FPOM), University of Toronto, Toronto, Ontario, Canada Northern California Cancer Center, Fremont, CA (EMJ); Department of Health Research and Policy, Stanford University School of Medicine and Stanford Cancer Center, Stanford, CA (EMJ); Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia (LB, DRE, GGG, GS); Centre for Molecular, Environmental, Genetic, and Analytic Epidemiology, The University of Melbourne, Melbourne, Australia (LBa, DRE, GGG, GS, GSD, CA, JLH); The Alfred Hospital, Melbourne, Australia (CAM); Vesalius Research Center, KU Leuven and VIB, Leuven, Belgium (DL); Department of Radiotherapy, University Hospitals, Leuven, Belgium (TV, CW, RP, AS, PN, HW); Department of Obstetrics and Gynaecology (TD, AA, T-WP-S, PH), Department of Radiation Oncology (MB, AM, JHK), Hanover Medical School, Hanover, Germany (TD, MBr, AMe, JHK, AA, T-WP-S, PHi); Servicio Cirugía General (JIAP), Servicio de Anatomía Patológica (PMR), Hospital Monte Naranco, Oviedo, Spain Servicio de Oncología Médica, Hospital La Paz, Madrid, Spain (PZ); CIBERER, Madrid, Spain (JB); Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany (Y-DK); Institute of Pathology, Medical Faculty of the University of Bonn, Bonn, Germany (H-PF); Molecular Genetics of Breast Cancer, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany (UH); Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA), Bochum, Germany (BP, TBr ); Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany (CJ, HB); University of Tübingen, Tübingen, Germany (CJ, HB); University of Southampton School of Medicine, Southampton University Hospitals NHS Trust, Southampton (DME, WJT, SMG); Guy's, King's, St Thomas' Cancer Centre, Guy's Hospital, London, UK (EJS); Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK (EJS, IPT, AJo, NMc); Clinical Science Institute, University College Hospital, Galway, Ireland (MKe, NMc, NMi); Department of Epidemiology, University of California Irvine, Irvine (HA-C, AZ); Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan (C-YS, C-NH, P-EW, S-LY); Graduate Institute of Environmental Science, China Medical University, Taichung, Taiwan (C-YS); Department of Surgery (J-CY), Department of Radiology (G-CH), Tri-Service General Hospital, Taipei, Taiwan (J-CY, G-CH); Department of Surgery, Changhua Christian Hospital, Changhua, Taiwan (S-TC); Department of Preventive Medicine, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA (CAH, BEH); Epidemiology Program, Cancer Research Center, University of Hawaii, Honolulu, HI (LLM, LNK); Department of Molecular Medicine and Surgery (AL), Department of Oncology and Pathology (SMa), Karolinska Institutet, Stockholm, Sweden; International Hereditary Cancer Centre, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland (AJa, JLu, THu, TBy, BG, JG); Department of Medical Oncology Rotterdam Family Cancer Clinic, Erasmus University Medical Center, Rotterdam, the Netherlands (MJH, AHo, AMWvdO, AJa, MKr, MMAT-L, MC); Department of Obstetrics and Gynecology, University of Ulm, Ulm, Germany (SW-G); University of Oulu, Oulu University Hospital, Oulu, Finland (KP, AJ-V, KM, MGr, PHi, RW); Department of Pathology, Institute of Clinical Medicine, University of Eastern Finland and Kuopio University Hospital; Biocenter Kuopio, Kuopio, Finland (AMa, V-MK, JK, YS, RS); Department of Oncology, Vaasa Central Hospital, Vaasa, Finland (VK); Department of Oncology, Kuopio University Hospital, Kuopio, Finland (PA); The Peter MacCallum Cancer Centre, East Melbourne, Australia (kConFab); Department of Clinical Biochemistry and Department of Breast Surgery, Herlev University Hospital, University of Copenhagen, Copenhagen, Denmark (SEB, DDØ, DK-K, HF, BGN); Unit of Medical Genetics, Department of Preventive and Predictive Medicine (SMa), Unit of Genetic Susceptibility to Cancer, Department of Experimental Oncology and Molecular Medicine (PR), Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy; Division of Cancer Prevention and Genetics, Istituto Europeo di Oncologia (IEO), Milan, Italy (MBa); Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (SEH, DJH, RT); Department of Epidemiology, Harvard School of Public Health, Boston, MA (SEH, DJH, RT); Molecular Epidemiology Unit, National Cancer Institute, Ratchathewi, Bangkok, Thailand (SS); International Agency for Research on Cancer, Lyon, France (PB, JM, FO, VG); Department of Human Genetics (PD), Department of Pathology (PD), Department of Clinical Genetics (PEAH), Department of Surgical Oncology (RAEMT), Leiden University Medical Center, Leiden, the Netherlands; Department of Medical Oncology, Rotterdam Family Cancer Clinic, Erasmus MC-Daniel den Hoed Cancer Center, Rotterdam, the Netherlands (CS); The Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Victoria, Australia (FH, HT, LDS, MCS).
Background Previous studies have suggested that breast cancer risk factors are associated with estrogen receptor (ER) and progesterone receptor (PR) expression status of the tumors. Methods We pooled tumor marker and epidemiological risk factor data from 35?568 invasive breast cancer case patients from 34 studies participating in the Breast Cancer Association Consortium. Logistic regression models were used in case-case analyses to estimate associations between epidemiological risk factors and tumor subtypes, and case-control analyses to estimate associations between epidemiological risk factors and the risk of developing specific tumor subtypes in 12 population-based studies. All statistical tests were two-sided. Results In case-case analyses, of the epidemiological risk factors examined, early age at menarche (=12 years) was less frequent in case patients with PR(-) than PR(+) tumors (P = .001). Nulliparity (P = 3 × 10(-6)) and increasing age at first birth (P = 2 × 10(-9)) were less frequent in ER(-) than in ER(+) tumors. Obesity (body mass index [BMI] = 30 kg/m(2)) in younger women (=50 years) was more frequent in ER(-)/PR(-) than in ER(+)/PR(+) tumors (P = 1 × 10(-7)), whereas obesity in older women (>50 years) was less frequent in PR(-) than in PR(+) tumors (P = 6 × 10(-4)). The triple-negative (ER(-)/PR(-)/HER2(-)) or core basal phenotype (CBP; triple-negative and cytokeratins [CK]5/6(+) and/or epidermal growth factor receptor [EGFR](+)) accounted for much of the heterogeneity in parity-related variables and BMI in younger women. Case-control analyses showed that nulliparity, increasing age at first birth, and obesity in younger women showed the expected associations with the risk of ER(+) or PR(+) tumors but not triple-negative (nulliparity vs parity, odds ratio [OR] = 0.94, 95% confidence interval [CI] = 0.75 to 1.19, P = .61; 5-year increase in age at first full-term birth, OR = 0.95, 95% CI = 0.86 to 1.05, P = .34; obesity in younger women, OR = 1.36, 95% CI = 0.95 to 1.94, P = .09) or CBP tumors. Conclusions This study shows that reproductive factors and BMI are most clearly associated with hormone receptor-positive tumors and suggest that triple-negative or CBP tumors may have distinct etiology.
The association between established risk factors for breast cancer and subtypes or prognosis of the disease is not well known. We analyzed whether the Tyrer-Cuzick-predicted 10-year breast cancer risk score (TCRS), mammographic density (MD), and a 77-single nucleotide polymorphism polygenic risk score (PRS) were associated with breast cancer tumor prognosticators and risk of distant metastasis.
We used a case-only design in a population-based cohort of 5,500 Swedish patients with breast cancer. Logistic and multinomial logistic regression of outcomes, estrogen receptor (ER) status, lymph node involvement, tumor size, and grade was performed with TCRS, PRS, and percent MD as exposures. Cox proportional hazard models were used to estimate hazard ratios (HRs) of distant metastasis.
Women at high risk for breast cancer based on PRS and/or TCRS were significantly more likely to be diagnosed with favorable prognosticators, such as ER-positive and low-grade tumors. In contrast, PRS weighted on ER-negative disease was associated with ER-negative tumors. When stratifying by age, the associations of TCRS with favorable prognosticators were restricted to women younger than age 50. Women scoring high in both TCRS and PRS had a lower risk of distant metastasis (HR, 0.69; 95% CI, 0.49 to 0.98). MD was not associated with any of the examined prognosticators.
Women at high risk for breast cancer based on genetic and lifestyle factors were significantly more likely to be diagnosed with breast cancers with a favorable prognosis. Better knowledge of subtype-specific risk factors could be vital for the success of prevention programs aimed at lowering mortality.
Population attributable factions (PAFs) show the proportion of the disease that could be prevented if the cause could be removed. The PAF for familial breast cancer has not been precisely determined. We used the nationwide Swedish Family-Cancer Database on 10.2 million individuals and 190,000 mothers' and 26,000 daughters' breast cancers to calculate familial standardized incidence ratios (SIRs), proportion of cases with a family history and familial PAFs for all invasive and in situ and morphology-specific breast cancers in daughters who were 0-66 years old. The data were calculated by mother only, sister only or both as probands. More than 5,500 familial breast cancers were recorded. The familial SIRs for all invasive breast cancer were 1.79 by breast cancer in the mother only, 2.03 by breast cancer in a sister only and 2.82 by breast cancer in both a mother and sister. The familial PAFs were 3.61, 3.01 and 0.43%, respectively, giving a total PAF of 7.05%. Age-specific risks were shown for the mother and sister history of breast cancer. The PAF values decreased by age when the daughter had a mother history of breast cancer but not when she had a sister history. PAFs did not depend on the morphologic type of breast cancer. The data show that the familial PAF of breast cancer among a 0-66-year-old population of daughters was 7% and independent of the morphologic type. If contribution from the paternal side was allowed for, the PAF would be 11%.
Comment In: Int J Cancer. 2002 Dec 10;102(5):548-912432562
Population attributable faction (PAF) shows the proportion of the disease that could be prevented if the cause could be removed. PAFs for most types of familial cancer have not been determined. We used the Swedish Family-Cancer Database on 10.2 million individuals and 688,537 parental and 116,741 offspring cancers to calculate familial risks, proportions of affected individuals, and familial PAFs for 28 neoplasms among 0-66-year-old offspring. The data were calculated by an exact proband status in the nuclear families. The familial risks for offspring cancer were increased at 23 of 28 sites from the same cancer in only the parent, at 17 sites from a sibling proband and at 12 sites from a parent and sibling proband. The highest PAFs by parent were for prostate (9.01%), breast (3.67%), and colorectal (5.15%) cancer. However, considering that in gender-specific cancers, the familial effect may originate from grandparents, the PAFs for prostate and breast cancer could be multiplied by 2. The PAFs for the sibling history of prostate, breast, and colorectal cancers were 1.55, 2.85, and 1.23% and for the parent and sibling history 0.99, 0.42, and 0.48%, respectively. Because of mutually exclusive proband definition, the PAFs were additive, giving a total PAF of 20.55% for prostate, 10.61% for breast, and 6.87% for colorectal cancer. The present PAF values give an estimate of the heritable single locus or additive effects for cancer in nuclear families. The data show that the familial PAF of prostate cancer was 20.55%, and breast cancer 10.61%, but for most other sites, it was between 1 and 3%.
Mammographic density is a strong risk factor for breast cancer and an important determinant of screening sensitivity, but its clinical utility is hampered due to the lack of objective and automated measures. We evaluated the performance of a fully automated volumetric method (Volpara).
A prospective cohort study included 41,102 women attending mammography screening, of whom 206 were diagnosed with breast cancer after a median follow-up of 15.2 months. Percent and absolute dense volumes were estimated from raw digital mammograms. Genotyping was performed in a subset of the cohort (N = 2,122). We examined the agreement by side and view and compared density distributions across different mammography systems. We also studied associations with established density determinants and breast cancer risk.
The method showed good agreement by side and view, and distributions of percent and absolute dense volume were similar across mammography systems. Volumetric density was positively associated with nulliparity, age at first birth, hormone use, benign breast disease, and family history of breast cancer, and negatively with age and postmenopausal status. Associations were also observed with rs10995190 in the ZNF365 gene (P
High physical activity has been shown to decrease the risk of breast cancer, potentially by a mechanism that also reduces mammographic density. We tested the hypothesis that the risk of developing breast cancer in the next 10 years according to the Tyrer-Cuzick prediction model influences the association between physical activity and mammographic density.
We conducted a population-based cross-sectional study of 38,913 Swedish women aged 40-74 years. Physical activity was assessed using the validated web-questionnaire Active-Q and mammographic density was measured by the fully automated volumetric Volpara method. The 10-year risk of breast cancer was estimated using the Tyrer-Cuzick (TC) prediction model. Linear regression analyses were performed to assess the association between physical activity and volumetric mammographic density and the potential interaction with the TC breast cancer risk.
Overall, high physical activity was associated with lower absolute dense volume. As compared to women with the lowest total activity level (
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