BACKGROUND:Multiple risk factors influence breast cancer risk, but the role of percent mammographic density (PMD) in mediating these associations remains unclear. METHODS:In this pooled analysis of women who had screening mammograms before age 50 years, we assessed whether PMD mediates associations between reproductive, structural, and lifestyle factors and breast cancer risk. Causal mediation analysis was used to estimate direct and indirect effects and the proportion mediated by PMD. RESULTS:PMD partially mediated 29% of the association between breast calcifications and breast cancer risk, with a natural indirect effect odds ratio (ORNIE) of 1.16 [95% confidence interval (CI), 1.04-1.30; P = 0.009]. A history of breast biopsies was marginally associated with increased risk (P = 0.083), with 83.1% of this effect mediated by PMD (ORNIE = 1.28; 95% CI, 1.11-1.49; P = 0.001). PMD mediated 48.6% of the reduced risk among parous versus nulliparous women (ORNIE = 0.76; 95% CI, 0.65-0.90; P = 0.001). No significant mediation by PMD was observed for first-degree family history of breast cancer, age at first live birth, or smoking. Adult body mass index showed inconsistent mediation with opposing direct and indirect effects, reducing breast cancer risk via lower PMD but increasing risk through density-independent pathways, yielding a null total effect. CONCLUSIONS:Our findings highlight PMD's important role as a mediator in linking certain reproductive and structural factors to breast cancer risk in younger women, offering insights into early-onset breast cancer. IMPACT:This underscores PMD's potential as both a biomarker and a target for risk prediction and prevention.

Supplementary Table 1. Characteristics of the Studies Included in the Male Breast Cancer Pooling Project

Supplementary Table 2. Associations between tobacco exposures and male breast cancer risk additionally adjusted for total exposure (pack-years)

Supplementary Table 3. Associations between alcohol consumption exposures and male breast cancer risk

For 50 years, the effect of age at first birth (AFB) has been thought to explain the strong association between breast cancer risk and age at first marriage (AFM), which was first reported in 1926. The independent effects of AFM, AFB and number of sexual partners adjusted for parity and other risk factors were estimated in reanalysis of a large international case-control study conducted in 1979 to 1982 (2274 breast cancers, 18209 controls) by unconditional logistic regression. Respective AFB and AFM breast cancer odds ratios (ORs) for >= 31 years relative to <= 18 years were 3.01 (95% CI 2.44-3.71; P(trend) < .0001) and 3.24 (95% CI 2.62-4.01; P(trend) < .0001) in univariate analyses. Among married parous women, these ORs fell to 1.38 (95% CI 0.98-1.95; P(trend) < .03) for AFB and 1.70 (95% CI 1.17-2.46; P(trend) < .002) for AFM when fitted together in multivariate analysis including other risk factors. A similar adjusted OR for AFM >= 31 years relative to <= 18 years was seen among married nulliparous women (OR 1.71, 95% CI 0.98-2.98; P(trend) < .001). AFM (a surrogate for age at starting prolonged cohabitation) is thus strongly associated with breast cancer risk. This suggests an effect of close contact. Identifying the (probably infective) mechanism might lead to effective prevention of breast cancer. The independent effect of AFB is smaller and could be due to residual confounding.

BACKGROUND:Endotoxin, a contaminant of cotton dust, is an experimental model for parkinsonism (PS).METHODS:We investigated associations between exposures to endotoxin, solvents, magnetic fields, and night shift work, and neurologist-determined PS among Shanghai women textile workers, including 537 retired cotton factory workers ages ≥50 years and an age-matched reference group of 286 retired textile workers not exposed to cotton dust. Repeat exams were conducted 2.5 years after enrollment among 467 cotton workers and 229 reference workers.RESULTS:We identified 39 prevalent PS cases and 784 non-cases. No consistent or statistically significant associations were observed for endotoxin, solvents, magnetic fields, or shift work with PS risk, severity, or progression.CONCLUSIONS:Despite the null findings, additional studies of endotoxin exposure and risk of PS in other well-characterized occupational cohorts are warranted in view of toxicological evidence that endotoxin is a pathogenic agent and its widespread occurrence in multiple industries worldwide.

Equol (a bacterial metabolite of the soy isoflavone daidzein) is produced by 30% to 50% of humans and may be associated with health outcomes. We hypothesized that plasma equol would be inversely associated with risks of fibrocystic breast conditions (FBC) and breast cancer (BC). Plasma from women in a breast self-examination trial in Shanghai with BC (n=269) or FBC (n=443), and age-matched controls (n=1027) was analyzed for isoflavones. Equol was grouped into categories (<20, 20-<45, and ≥45nmol/L) and, among women with daidzein ≥20nmol/L, the log10 equol:daidzein ratio was grouped into tertiles. Where available, non-cancerous tissue (NCT) adjacent to the carcinomas from women with BC were classified as non-proliferative or proliferative (n=130 and 172, respectively). The lesions from women with FBC were similarly classified (n=99 and 92, respectively). Odds ratios (OR) and 95% confidence intervals (CI) were calculated across equol categories and tertiles of log10 equol:daidzein ratio. Equol categories were not associated with FBC or BC (P>.05). For log10 equol:daidzein, compared to controls there were positive associations in the mid tertile for proliferative FBC (OR 2.06, 95% CI 1.08-3.93), BC with proliferative NCT (OR 2.95, 95% CI 1.37-6.35), and all BC regardless of histology (OR 2.37, 95% CI 1.43-3.95). However, trends in ORs with increasing plasma equol values or equol:daidzein ratios were not observed (P>.05). The results of this study do not provide evidence that equol plays a role in the etiology of these breast conditions. However, further work is needed to confirm or refute this conclusion.

The lack of breast cancer screening in low and middle‐income countries results in later stage diagnosis and worsened outcomes for women. A cluster randomized trial was performed in Bogotá, Colombia between 2008 and 2012 to evaluate effects of opportunistic breast cancer screening. Thirteen clinics were randomized to an intervention arm and 13 to a control arm. Physicians in intervention clinics were instructed to perform clinical breast examination on all women aged 50–69 years attending clinics for non‐breast health issues, and then refer them for mammographic screening. Physicians in control clinics were not explicitly instructed to perform breast screening or mammography referrals, but could do so if they thought it indicated (“usual care”). Women were followed for 2‐years postrandomization. 7,436 women were enrolled and 7,419 (99.8%) screened in intervention clinics, versus 8,419 enrolled and 1,108 (13.1%) screened in control clinics. Incidence ratios (IR) of early, advanced and all breast cancers were 2.9 (95% CI 1.1–9.2), 1.0 (0.3–3.5) and 1.9 (0.9–4.1) in the first (screening) year of the trial, and the cumulative IR for all breast cancers converged to 1.4 (0.7–2.8) by the end of follow‐up (Year 2). Eighteen (69.2%) of 26 women with early stage disease had breast conservation surgery (BCS) versus 6 (42.5%) of 14 women with late‐stage disease (p = 0.02). Fifteen (68.2%) of 22 women with breast cancer in the intervention group had BCS versus nine (50.0%) of 18 women in the control group (p = 0.34). Well‐designed opportunistic clinic‐based breast cancer screening programs may be useful for early breast cancer detection in LMICs.

No AccessNov 2015Breast CancerAuthors/Editors: Benjamin O. Anderson, Joseph Lipscomb, Raul H. Murillo, David B. ThomasBenjamin O. AndersonSearch for more papers by this author, Joseph LipscombSearch for more papers by this author, Raul H. MurilloSearch for more papers by this author, David B. ThomasSearch for more papers by this authorhttps://doi.org/10.1596/978-1-4648-0349-9_ch3AboutView ChaptersFull TextPDF (0.6 MB) ToolsAdd to favoritesDownload CitationsTrack Citations ShareFacebookTwitterLinked In Abstract: Recognizes that breast cancer is the world’s most common cancer among women, and its incidence is increasing in low- and middle-income countries (LMICs). Reducing risk factors will show little effect since most like age and genetic history cannot change. The Breast Health Global Initiative (BHGI) has developed guidelines to improve early detection and treatment which will enhance outcomes. Early detection involves mammographic screening, clinical breast examinations, breast self-examinations, and breast awareness education while diagnosis focuses on clinical evaluation, diagnostic imaging, tissue sampling, and tumor markers. Treatment such as modified radical mastectomy is the mainstay and when available, radiation therapy and systemic pharmacotherapy (including chemotherapy) may also produce positive outcomes. Before an LMIC initiates a breast cancer control program or evaluates existing programs, careful assessment of the local situation is needed to look at social and cultural barriers and identify target groups. Cost-effective interventions can be developed in LMICs as shown by Vietnam and the Republic of Korea. ReferencesAnderson, B O, S Braun, R W Carlson, J R Gralow, and M D Lagios. 2003. “Overview of Breast Health Care Guidelines for Countries with Limited Resources.” The Breast Journal 9 (Suppl. 2): S42–50. Google ScholarAnderson, B O, E Cazap, N S El Saghir, C H Yip, and H M Khaled and others. 2011. “Optimisation of Breast Cancer Management in Low-Resource and Middle-Resource Countries: Executive Summary of the Breast Health Global Initiative Consensus, 2010.” The Lancet Oncology 12 (4): 387–98. doi:S1470-2045(11)70031-6 [pii]; 10.1016/S1470-2045(11)70031-6. CrossrefGoogle ScholarAnderson, B O, R Shyyan, A Eniu, R A Smith, and C H Yip and others. 2006. “Breast Cancer in Limited-Resource Countries: An Overview of the Breast Health Global Initiative 2005 Guidelines.” The Breast Journal 12 (Suppl. 1): S3–15. doi:10.1111/j.1075-122X.2006.00199.x. Google ScholarAnderson, B O, C H Yip, R A Smith, R Shyyan, and S F Sener and others. 2008. “Guideline Implementation for Breast Healthcare in Low-Income and Middle-Income Countries: Overview of the Breast Health Global Initiative Global Summit 2007.” Cancer 113 (Suppl. 8):2221–43. doi:10.1002/cncr.23844. Google ScholarAshbury, F D, C Cameron, S L Mercer, M Fitch, and E Nielsen. 1998. “One-on-One Peer Support and Quality of Life for Breast Cancer Patients.” Patient Education and Counseling 35 (2): 89–100. doi:S0738399198000354 [pii]. CrossrefGoogle ScholarAzaiza, F, M Cohen, M Awad, and F Daoud. 2010. “Factors Associated with Low Screening for Breast Cancer in the Palestinian Authority: Relations of Availability, Environmental Barriers, and Cancer-Related Fatalism.” Cancer 116 (19): 4646–55. doi:10.1002/cncr.25378. CrossrefGoogle ScholarBai, Y, M Ye, H Cao, X Ma, and Y Xu and others. 2012. “Economic Evaluation of Radiotherapy for Early Breast Cancer after Breast-Conserving Surgery in a Health Resource-Limited Setting.” Breast Cancer Research and Treatment 136 (2): 547–57. doi:10.1007/s10549-012-2268-1. CrossrefGoogle ScholarBarlow, W E, C Chi, P A Carney, S H Taplin, and C D’Orsi, and others. 2004. “Accuracy of Screening Mammography Interpretation by Characteristics of Radiologists.” Journal of the National Cancer Institute 96 (24): 1840–50. doi:10.1093/jnci/djh333. CrossrefGoogle ScholarBaum, M 2013. “Harms from Breast Cancer Screening Outweigh Benefits If Death Caused by Treatment Is Included.” British Medical Journal 346: f385. doi:10.1136/bmj.f385. Google ScholarBerry, D A, K A Cronin, S K Plevritis, D G Fryback, and L Clarke and others. 2005. “Effect of Screening and Adjuvant Therapy on Mortality from Breast Cancer.” The New England Journal of Medicine 353 (17): 1784–92. doi:353/17/1784 [pii]; 10.1056/NEJMoa050518. CrossrefGoogle ScholarBese, N S, A Munshi, A Budrukkar, A Elzawawy, and C A Perez. 2008. “Breast Radiation Therapy Guideline Implementation in Low- and Middle-Income Countries.” Cancer 113 (Suppl. 8):2305–14. Google ScholarBray, F, J S Ren, E Masuyer, and J Ferlay. 2013. “Global Estimates of Cancer Prevalence for 27 Sites in the Adult Population in 2008.” International Journal of Cancer 132 (5): 1133–45. doi:10.1002/ijc.27711. CrossrefGoogle ScholarBreast Screening Frequency Trial Group. 2002. “The Frequency of Breast Cancer Screening: Results from the UKCCCR Randomised Trial. United Kingdom Co-Ordinating Committee on Cancer Research.” European Journal of Cancer 38 (11): 1458–64. CrossrefGoogle ScholarBrown, M L, S I Goldie, G Draisma, J Harford, and J Lipscomb. 2006. “Health Service Interventions for Cancer Control in Developing Countries.” In Disease Control Priorities in Developing Countries, 2nd edition, edited by Jamison, D T, J G Breman, A R Measham, G Alleyne, M Claeson, D B Evans, P Jha, A Mills, and P Musgrove 569–89. Washington, DC: World Bank and Oxford University Press. Google ScholarCardoso, F, N Bese, S R Distelhorst, J L Bevilacqua, and O Ginsburg and others. 2013. “Supportive Care During Treatment for Breast Cancer: Resource Allocations in Low- and Middle-Income Countries: A Breast Health Global Initiative 2013 Consensus Statement.” Breast 22 (5): 593–605. doi:10.1016/j.breast.2013.07.050. CrossrefGoogle ScholarChia, K S, M Reilly, C S Tan, J Lee, and Y Pawitan and others. 2005. “Profound Changes in Breast Cancer Incidence May Reflect Changes into a Westernized Lifestyle: A Comparative Population-Based Study in Singapore and Sweden.” International Journal of Cancer 113 (2): 302–06. CrossrefGoogle ScholarChopra, R 2001. “The Indian Scene.” Journal of Clinical Oncology 19 (Suppl. 18): 106S–111S. Google ScholarChu, K C, C R Smart, and R E Tarone. 1988. “Analysis of Breast Cancer Mortality and Stage Distribution by Age for the Health Insurance Plan Clinical Trial.” Journal of the National Cancer Institute 80 (14): 1125–32. CrossrefGoogle ScholarClarke, M 2006. “Meta-Analyses of Adjuvant Therapies for Women with Early Breast Cancer: The Early Breast Cancer Trialists’ Collaborative Group Overview.” Annals of Oncology 17 (Suppl. 10): x59–62. CrossrefGoogle ScholarCleary, J, H Ddungu, S R Distelhorst, C Ripamonti, and G M Rodin. and others. 2013. “Supportive and Palliative Care for Metastatic Breast Cancer: Resource Allocations in Low- and Middle-Income Countries: A Breast Health Global Initiative 2013 Consensus Statement.” Breast 22 (5): 616–27. doi:10.1016/j.breast.2013.07.052. CrossrefGoogle ScholarCurado, M P, B Edwards, H R Shin, J H Storm, and J Ferlay, and others. 2007. “Cancer Incidence in Five Continents.” Vol. 9, IARC Scientific Publication 160, IARC Press, Lyon. Google ScholarDevi, B C, T S Tang, and M Corbex. 2007. “Reducing by Half the Percentage of Late-Stage Presentation for Breast and Cervix Cancer over 4 Years: A Pilot Study of Clinical Downstaging in Sarawak, Malaysia.” Annals of Oncology 18 (7): 1172–76. doi:mdm105 [pii]; 10.1093/annonc/mdm105. CrossrefGoogle ScholarEniu, A, R W Carlson, N S El Saghir, J Bines, and N S Bese and others. 2008. “Guideline Implementation for Breast Healthcare in Low- and Middle-Income Countries: Treatment Resource Allocation.” Cancer 113 (Suppl. 8):2269–81. doi:10.1002/cncr.23843. CrossrefGoogle ScholarEvans, D B, T T Edejer, T Adam, and S S Lim 2005. “Methods to Assess the Costs and Health Effects of Interventions for Improving Health in Developing Countries.” British Medical Journal 331 (7525): 1137–40. doi:10.1136/bmj.331.7525.1137. CrossrefGoogle ScholarFerlay, J, I Soerjomataram, M Ervik, R Dikshit, and S Eser and others. 2013. “GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide.” IARC CancerBase No. 11 [Internet]. International Agency for Research on Cancer. http://globocan.iarc.fr. Google ScholarFonseca, M, G T Araujo, and E D Saad. 2009. “Cost-Effectiveness of Anastrozole, in Comparison with Tamoxifen, in the Adjuvant Treatment of Early Breast Cancer in Brazil.” Revista da Associação Médica Brasileira 55 (4): 410–15. CrossrefGoogle ScholarForouzanfar, M H, K J Foreman, A M Delossantos, R Lozano, and A D Lopez, and others. 2011. “Breast and Cervical Cancer in 187 Countries between 1980 and 2010: A Systematic Analysis.” The Lancet 378 (9801): 1461–84. doi:S0140-6736(11)61351-2 [pii]; 10.1016/S0140-6736(11)61351-2. CrossrefGoogle ScholarFreedman, L S, B K Edwards, L A Ries, and J L G Young. 2006. Cancer Incidence in Four Member Countries (Cyprus, Egypt, Israel, and Jordan) of the Middle East Cancer Consortium (MECC) Compared with US SEER. NIH Pub No, 06-5873. Bethesda, MD: National Cancer Institute. Google ScholarGanz, P A, C H Yip, J R Gralow, S R Distelhorst, and K S Albain and others. 2013. “Supportive Care after Curative Treatment for Breast Cancer (Survivorship Care): Resource Allocations in Low- and Middle-Income Countries: A Breast Health Global Initiative 2013 Consensus Statement.” Breast 22 (5): 606–15. doi:10.1016/j.breast.2013.07.049. CrossrefGoogle ScholarGinsberg, G M, J A Lauer, S Zelle, S Baeten, and R Baltussen. 2012. “Cost Effectiveness of Strategies to Combat Breast, Cervical, and Colorectal Cancer in Sub-Saharan Africa and South East Asia: Mathematical Modelling Study.” British Medical Journal 344: e614. doi:10.1136/bmj.e614. CrossrefGoogle ScholarGold, M R, J E Siegel, L B Russell, and M C Weinstein 1996. Cost-Effectiveness in Health and Medicine, 1st edition. New York: Oxford University Press. Google ScholarGotzsche, P C, K J Jorgensen, P H Zahl, and J Maehlen. 2012. “Why Mammography Screening Has Not Lived up to Expectations from the Randomised Trials.” Cancer Causes Control 23 (1): 15–21. doi:10.1007/s10552-011-9867-8. CrossrefGoogle ScholarGreenlee, R T, T Murray, S Bolden, and P A Wingo. 2000. “Cancer Statistics, 2000.” CA: A Cancer Journal for Clinicians 50 (1): 7–33. CrossrefGoogle ScholarGroot, M T, R Baltussen, C A Uyl-de, B O Groot Anderson, and G N Hortobagyi. 2006. “Costs and Health Effects of Breast Cancer Interventions in Epidemiologically Different Regions of Africa, North America, and Asia.” The Breast Journal 12 (Suppl. 1): S81–90. CrossrefGoogle ScholarHammond, M E, D F Hayes, M Dowsett, D C Allred, and K L Hagerty, and others. 2010. “American Society of Clinical Oncology/College of American Pathologists Guideline Recommendations for Immunohistochemical Testing of Estrogen and Progesterone Receptors in Breast Cancer.” Archives of Pathology & Laboratory Medicine 134 (6): 907–22. doi:10.1043/1543-2165-134.6.907. Google ScholarHarford, J B, I V Otero, B O Anderson, E Cazap, and W J Gradishar and others. 2011. “Problem Solving for Breast Health Care Delivery in Low and Middle Resource Countries (LMCs): Consensus Statement from the Breast Health Global Initiative.” Breast 20 (Suppl. 2): S20–29. CrossrefGoogle ScholarHisham, A N and C H Yip. 2003. “Spectrum of Breast Cancer in Malaysian Women: Overview.” World Journal of Surgery 27 (8): 921–23. CrossrefGoogle ScholarHowell, A, E Anderson, R Blamey, R B Clarke, and J M Dixon, and others. 1998. “The Primary Use of Endocrine Therapies.” Recent Results in Cancer Research 152 227–44. CrossrefGoogle ScholarHumphrey, L L, M Helfand, B K Chan, and S H Woolf. 2002. “Breast Cancer Screening: A Summary of the Evidence for the U.S. Preventive Services Task Force.” Annals of Internal Medicine 137 (5 Part 1):347–60. CrossrefGoogle ScholarIARC (International Agency for Research on Cancer). 2008. “Screening for Breast Cancer.” In World Cancer Report, edited by P. Boyle LevinB296–301. Lyon: IARC. Google ScholarIchikawa, L E, W E Barlow, M L Anderson, S H Taplin, and B M Geller, and others. 2010. “Time Trends in Radiologists’ Interpretive Performance at Screening Mammography from the Community-Based Breast Cancer Surveillance Consortium, 1996–2004.” Radiology 256 (1): 74–82. doi:10.1148/radiol.10091881. CrossrefGoogle ScholarInstituto Nacional de Cancerología. 2006. Recomendaciones para la detección temprana de cáncer de mama en Colombia. Guía de práctica clínica No.1. Bogotá: Instituto Nacional de Cancerología. Google ScholarJemal, A, R Siegel, E Ward, Y Hao, and J Xu, and others. 2009. “Cancer Statistics, 2009.” CA: A Cancer Journal for Clinicians 59 (4): 225–49. doi:caac.20006 [pii];10.3322/caac.20006. CrossrefGoogle ScholarJemal, A, A Thomas, T Murray, and M Thun. 2002. “Cancer Statistics, 2002.” CA: A Cancer Journal for Clinicians 52 (1): 23–47. CrossrefGoogle ScholarJohannesson, M and M C Weinstein. 1993. “On the Decision Rules of Cost-Effectiveness Analysis.” Journal of Health Economics 12 (4): 459–67. CrossrefGoogle ScholarKalager, M, M Zelen, F Langmark, and H O Adami. 2010. “Effect of Screening Mammography on Breast-Cancer Mortality in Norway.” The New England Journal of Medicine 363 (13): 1203–10. doi:10.1056/NEJMoa1000727. CrossrefGoogle ScholarKanemura, S, I Tsuji, N Ohuchi, H Takei, and T Yokoe and others. 1999. “A Case Control Study on the Effectiveness of Breast Cancer Screening by Clinical Breast Examination in Japan.” Japanese Journal of Cancer Research 90 (6): 607–13. CrossrefGoogle ScholarKardinah, D, B O Anderson, C Duggan, I A Ali, and D B Thomas. 2014. “Short Report: Limited Effectiveness of Screening Mammography in Addition to Clinical Breast Examination by Trained Nurse Midwives in Rural Jakarta, Indonesia.” International Journal of Cancer 134 (5): 1250–55. doi:10.1002/ijc.28442. CrossrefGoogle ScholarKuroishi, T, K Hirose, T Suzuki, and S Tominaga. 2000. “Effectiveness of Mass Screening for Breast Cancer in Japan.” Breast Cancer 7 (1): 1–8. CrossrefGoogle ScholarLee, S G, Y G Jee, H C Chung, S B Kim, and J Ro, and others. 2009. “Cost-Effectiveness Analysis of Adjuvant Therapy for Node Positive Breast Cancer in Korea: Docetaxel, Doxorubicin and Cyclophosphamide (TAC) Versus Fluorouracil, Doxorubicin and Cyclophosphamide (FAC).” Breast Cancer Research and Treatment 114 (3): 589–95. doi:10.1007/s10549-008-0035-0. CrossrefGoogle ScholarLee, S Y, S H Jeong, Y N Kim, J Kim, and D R Kang, and others. 2009. “Cost-Effective Mammography Screening in Korea: High Incidence of Breast Cancer in Young Women.” Cancer Science 100 (6): 1105–11. doi:10.1111/j.1349-7006.2009.01147.x. CrossrefGoogle ScholarLiubao, P, W Xiaomin, T Chongqing, J Kamon, and C Gannong and others. 2009. “Cost-Effectiveness Analysis of Adjuvant Therapy for Operable Breast Cancer from a Chinese Perspective: Doxorubicin Plus Cyclophosphamide versus Docetaxel Plus Cyclophosphamide.” Pharmacoeconomics 27 (10): 873–86. CrossrefGoogle ScholarLove, R R, N B Duc, D C Allred, N C Binh, and N V Dinh, and others. 2002. “Oophorectomy and Tamoxifen Adjuvant Therapy in Premenopausal Vietnamese and Chinese Women with Operable Breast Cancer.” Journal of Clinical Oncology 20 (10): 2559–66. CrossrefGoogle ScholarMasood, S, L Vass, J A Ibarra, Jr, B M Ljung, and H Stalsberg and others. 2008. “Breast Pathology Guideline Implementation in Low- and Middle-Income Countries.” Cancer 113 (Suppl. 8):2297–304. doi:10.1002/cncr.23833. CrossrefGoogle ScholarMcCannon, C J, D M Berwick, and M R Massoud. 2007. “The Science of Large-Scale Change in Global Health.” Journal of the American Medical Association 298 (16): 1937–39. CrossrefGoogle ScholarMcTiernan, A, P Porter, and J D Potter. 2008. “Breast Cancer Prevention in Countries with Diverse Resources.” Cancer 113 (Suppl. 8):2325–30. doi:10.1002/cncr.23829. Google ScholarMittra, I, G A Mishra, S Singh, S Aranke, and P Notani and others. 2010. “A Cluster Randomized, Controlled Trial of Breast and Cervix Cancer Screening in Mumbai, India: Methodology and Interim Results after Three Rounds of Screening.” International Journal of Cancer 126 (4): 976–84. doi:10.1002/ijc.24840. Google ScholarMorrow, M, E A Strom, L W Bassett, D D Dershaw, and B Fowble and others. 2002. “Standard for Breast Conservation Therapy in the Management of Invasive Breast Carcinoma.” CA: A Cancer Journal for Clinicians 52 (5): 277–300. CrossrefGoogle ScholarMurillo, R, S Díaz, O Sánchez, F Perry, and M Piñeros and others. 2008. “Pilot Implementation of Breast Cancer Early Detection Programs in Colombia.” Breast Care 3 29–32. CrossrefGoogle ScholarMurray, C J L and A D Lopez. 1996. “The Global Burden of Disease: A Comprehensive Assessment of Mortality and Disability from Diseases, Injuries, and Risk Factors in 1990 and Projected to 2020.” In Global Burden of Disease and Injury. Cambridge, MA: Harvard School of Public Health. Google ScholarNelson, H D, K Tyne, A Naik, C Bougatsos, and B K Chan and others. 2009. “Screening for Breast Cancer: An Update for the U.S. Preventive Services Task Force.” Annals of Internal Medicine 151 (10): 727–37, W237–42. doi:10.7326/0003-4819-151-10-200911170-00009. CrossrefGoogle ScholarNguyen, L H, W Laohasiriwong, J F Stewart, P Wright, and Y T B Nguyen. and others. 2013. “Cost-Effectiveness Analysis of a Screening Program for Breast Cancer in Vietnam.” Value in Health Regional Issues 2(1):21–28. CrossrefGoogle ScholarOkonkwo, Q L, G Draisma, A der Kinderen, M L Brown, and H J de. Koning. 2008. “Breast Cancer Screening Policies in Developing Countries: A Cost-Effectiveness Analysis for India.” Journal of the National Cancer Institute 100 (18): 1290–300. doi:10.1093/jnci/djn292. CrossrefGoogle ScholarParkin, D M and L M Fernandez. 2006. “Use of Statistics to Assess the Global Burden of Breast Cancer.” The Breast Journal 12 (Suppl. 1): S70–80. CrossrefGoogle ScholarPerloff, M, G J Lesnick, A Korzun, F Chu, and J F Holland, and others. 1988. “Combination Chemotherapy with Mastectomy or Radiotherapy for Stage III Breast Carcinoma: A Cancer and Leukemia Group B Study.” Journal of Clinical Oncology 6 (2): 261–69. Google ScholarPinto, A C, F Ades, E de Azambuja, and M Piccart-Gebhart. 2013. “Trastuzumab for Patients with HER2 Positive Breast Cancer: Delivery, Duration and Combination Therapies.” Breast 22 (Suppl. 2): S152–55. doi:10.1016/j.breast.2013.07.029. Google ScholarPisani, P, D M Parkin, C Ngelangel, D Esteban, and L Gibson and others. 2006. “Outcome of Screening by Clinical Examination of the Breast in a Trial in the Philippines.” International Journal of Cancer 118 (1): 149–54. CrossrefGoogle ScholarPoon, D, B O Anderson, L T Chen, K Tanaka, and W Y Lau, and others. 2009. “Management of Hepatocellular Carcinoma in Asia: Consensus Statement from the Asian Oncology Summit 2009.” The Lancet Oncology 10 (11): 1111–18. doi:S1470-2045(09)70241-4 [pii]; 10.1016/S1470-2045(09)70241-4. CrossrefGoogle ScholarPorter, P 2008. “‘Westernizing’ Women’s Risks? Breast Cancer in Lower-Income Countries.” The New England Journal of Medicine 358 (3): 213–16. CrossrefGoogle ScholarSalomon, J A, N Carvalho, C Gutierrez-Delgado, R Orozco, and A Mancuso and others. 2012. “Intervention Strategies to Reduce the Burden of Non-Communicable Diseases in Mexico: Cost Effectiveness Analysis.” British Medical Journal 344: e355. doi:10.1136/bmj.e355. CrossrefGoogle ScholarSant, M, C Allemani, F Berrino, M P Coleman, and T Aareleid and others. 2004. “Breast Carcinoma Survival in Europe and the United States.” Cancer 100 (4): 715–22. CrossrefGoogle ScholarSchmidt, C 2009. “Komen/ASCO Program Aims to Swell Ranks of Minority Oncologists.” Journal of the National Cancer Institute 101 (4): 224–25, a227. CrossrefGoogle ScholarSemiglazov, V F, V M Moiseyenko, A G Manikhas, S A Protsenko, and R S Kharikova, and others. 1999. “Role of Breast Self-Examination in Early Detection of Breast Cancer: Russia/WHO Prospective Randomized Trial in St. Petersburg.” Cancer Strategy 1 145–51. Google ScholarShyyan, R, S F Sener, B O Anderson, L M Garrote, and G N Hortobagyi, and others. 2008. “Guideline Implementation for Breast Healthcare in Low- and Middle-Income Countries: Diagnosis Resource Allocation.” Cancer 113 (Suppl. 8):2257–68. doi:10.1002/cncr.23840. Google ScholarSmith, R A 2000. “Breast Cancer Screening among Women Younger Than Age 50: A Current Assessment of the Issues.” CA: A Cancer Journal for Clinicians 50 (5): 312–36. CrossrefGoogle ScholarSoo, R A, B O Anderson, B C Cho, C H Yang, and M Liao and others. 2009. “First-Line Systemic Treatment of Advanced Stage Non-Small-Cell Lung Cancer in Asia: Consensus Statement from the Asian Oncology Summit 2009.” The Lancet Oncology 10 (11): 1102–10. doi:10.1016/S1470-2045(09)70238-4. CrossrefGoogle ScholarTan-Torres Edejer, T, R Baltussen, T Adam, R Hutubessy, and A Acharya and others. 2003. Making Choices in Health: WHO Guide to Cost-Effectiveness Analysis. Geneva: WHO. Google ScholarTangjitgamol, S, B O Anderson, H T See, C Lertbutsayanukul, and N Sirisabya, and others. 2009. “Management of Endometrial Cancer in Asia: Consensus Statement from the Asian Oncology Summit 2009.” The Lancet Oncology 10 (11): 1119–27. doi:10.1016/S1470-2045(09)70290-6. CrossrefGoogle ScholarTheriault, R L, R W Carlson, C Allred, B O Anderson, and H J Burstein, and others. 2013. “Breast Cancer, Version 3.2013: Featured Updates to the NCCN Guidelines.” Journal of the National Comprehensive Cancer Network 11 (7): 753–60; quiz 761. Google ScholarThomas, D B, D L Gao, R M Ray, W W Wang, and C J Allison and others. 2002. “Randomized Trial of Breast Self-Examination in Shanghai: Final Results.” Journal of the National Cancer Institute 94 (19): 1445–57. CrossrefGoogle ScholarThomas, D B, R H Murillo Kardinah, and B O Anderson. 2013. “Breast Cancer Early Detection and Clinical Guidelines.” In Cancer Epidemiology: Low and Middle Income Countries and Special Populations, edited by Soliman, A S, D Schottenfeld, and P Boffetta 378–95. New York: Oxford University Press. Google ScholarThorat, M A, A Rangole, M S Nadkarni, V Parmar, and R A Badwe. 2008. “Revision Surgery for Breast Cancer: Single-Institution Experience.” Cancer 113 (Suppl. 8):2347–52. doi:10.1002/cncr.23839. CrossrefGoogle ScholarThornton, H 2014. “Bringing an End to Mandatory Breast Cancer Screening in Uruguay.” British Medical Journal 348: g390. doi:10.1136/bmj.g390. Google ScholarU.S. Preventive Services Task Force. 2009. “Screening for Breast Cancer: U.S. Preventive Services Task Force Recommendation Statement.” Annals of Internal Medicine 151 (10): 716–26, W-236. doi:151/10/716 [pii]; 10.1059/0003-4819-151-10-200911170-00008. CrossrefGoogle ScholarVisco, F 2007. “The National Breast Cancer Coalition: Setting the Standard for Advocate Collaboration in Clinical Trials.” Cancer Treatment and Research 132 143–56. CrossrefGoogle ScholarWee, J T, B O Anderson, J Corry, A D’Cruz, and K C Soo and others. 2009. “Management of the Neck after Chemoradiotherapy for Head and Neck Cancers in Asia: Consensus Statement from the Asian Oncology Summit 2009.” The Lancet Oncology 10 (11): 1086–92. doi:S1470-2045(09)70266-9 [pii]; 10.1016/S1470-2045(09)70266-9. CrossrefGoogle ScholarWeir, H K, M J Thun, B F Hankey, L A Ries, and H L Howe, and others. 2003. “Annual Report to the Nation on the Status of Cancer, 1975–2000, Featuring the Uses of Surveillance Data for Cancer Prevention and Control.” Journal of the National Cancer Institute 95 (17): 1276–99. CrossrefGoogle ScholarWinn, R J and W Z Botnick. 1997. “The NCCN Guideline Program: A Conceptual Framework.” Oncology (Williston Park) 11 (11A):25–32. Google ScholarWHO (World Health Organization). 2001. Macroeconomics and Health: Investing in Health for Economic Development. Geneva: WHO. Google ScholarWHO (World Health Organization). 2002. “Executive Summary.” In National Cancer Control Programmes: Policies and Managerial Guidelines,1–24. Geneva: WHO. Google ScholarWong, N S, B O Anderson, K S Khoo, P T Ang, and C H Yip, and others. 2009. “Management of HER2-Positive Breast Cancer in Asia: Consensus Statement from the Asian Oncology Summit 2009.” The Lancet Oncology 10 (11): 1077–85. doi:10.1016/S1470-2045(09)70230-X. CrossrefGoogle ScholarWong, I O, B J Cowling, C M Schooling, and G M Leung. 2007. “Age-Period-Cohort Projections of Breast Cancer Incidence in a Rapidly Transitioning Chinese Population.” International Journal of Cancer 121 (7): 1556–63. CrossrefGoogle ScholarWong, I O, K M Kuntz, B J Cowling, C L Lam, and G M Leung. 2007. “Cost Effectiveness of Mammography Screening for Chinese Women.” Cancer 110 (4): 885–95. doi:10.1002/cncr.22848. CrossrefGoogle ScholarYang, J J, S K Park, L Y Cho, W Han, and B Park, and others. 2010. “Cost-Effectiveness Analysis of 5 Years of Postoperative Adjuvant Tamoxifen Therapy for Korean Women with Breast Cancer: Retrospective Cohort Study of the Korean Breast Cancer Society Database.” Clinical Therapeutics 32 (6): 1122–38. doi:10.1016/j.clinthera.2010.05.013. CrossrefGoogle ScholarYip, C H, R A Smith, B O Anderson, A B Miller, and D B Thomas, and others. 2008. “Guideline Implementation for Breast Healthcare in Low- and Middle-Income Countries: Early Detection Resource Allocation.” Cancer 113 (Suppl. 8):2244–56. doi:10.1002/cncr.23842. CrossrefGoogle ScholarYoo, C, J H Ahn, K H Jung, S B Kim, and H H Kim, and others. 2012. “Impact of Immunohistochemistry-Based Molecular Subtype on Chemosensitivity and Survival in Patients with Breast Cancer Following Neoadjuvant Chemotherapy.” Journal of Breast Cancer 15 (2): 203–10. doi:10.4048/jbc.2012.15.2.203. CrossrefGoogle ScholarZelle, S G and R M Baltussen. 2013. “Economic Analyses of Breast Cancer Control in Low- and Middle-Income Countries: A Systematic Review.” Systematic Reviews 2: 20. doi:10.1186/2046-4053-2-20. CrossrefGoogle ScholarZelle, S G, K M Nyarko, W K Bosu, M Aikins, and L M Niens, and others. 2012. “Costs, Effects and Cost-Effectiveness of Breast Cancer Control in Ghana.” Tropical Medicine & International Health 17 (8): 1031–43. doi:10.1111/j.1365-3156.2012.03021.x. CrossrefGoogle Scholar Previous chapterNext chapter FiguresreferencesRecommendeddetailsCited byEpidemiology of Breast CancerOncologie, Vol.24, No.4GSTP1 Ile105Val polymorphism among North Indian lung cancer patients treated using monotherapy and poly-pharmacyHuman & Experimental Toxicology, Vol.40, No.12_suppl15 November 2021Breast cancer early detection: A phased approach to implementationCancer, Vol.126, No.S1029 April 2020 View Published: November 2015ISBN: 978-1-4648-0349-9e-ISBN: 978-1-4648-0369-7 Copyright & Permissions Related TopicsHealth Nutrition and Population KeywordsPREVENTION AND DIAGNOSISCANCER SCREENINGBURDEN OF DISEASEBREAST CANCERACCESS TO HEALTH SERVICESPREVENTIVE HEALTH CARE PROGRAMSSURGERYWOMEN’S HEALTHLOW-INCOME COUNTRIESMIDDLE-INCOME COUNTRIESMAMMOGRAPHYCHEMOTHERAPYHEALTH EDUCATION PDF DownloadLoading ...

In 2007, the International Agency for Research on Cancer classified shift work that involves circadian disruption as a probable human carcinogen. Suppression of the antineoplastic hormone, melatonin, is a presumed mechanism of action. We conducted a case-cohort study nested within a cohort of 267,400 female textile workers in Shanghai, China. Newly diagnosed lung cancer cases (n = 1451) identified during the study period (1989-2006) were compared with an age-stratified subcohort (n = 3040). Adjusting for age, smoking, parity, and endotoxin exposure, relative risks [hazard ratios (HRs)] were estimated by Cox regression modeling to assess associations with cumulative years and nights of rotating shift work. Results did not consistently reveal any increased risk of lung cancer among rotating shift work or statistically significant trends for both cumulative years (HR 0.82, 95% CI 0.66 to 1.02; P-trend = 0.294) and nights (HR 0.81, 95% CI 0.65 to 1.00; P-trend = 0.415). Further analyses imposing 10- and 20-year lag times for disease latency also revealed similar results. Contrary to the initial hypothesis, rotating nighttime shift work appears to be associated with a relatively reduced lung cancer risk although the magnitude of the effect was modest and not statistically significant.

Although night-shift work has been associated with elevated risk of breast cancer in numerous epidemiologic studies, evidence is not consistent. We conducted a nested case–cohort study to investigate a possible association between shift work including a night shift and risk of breast cancer within a large cohort of women textile workers in Shanghai, China.

AbstractBackground: The etiology of male breast cancer is poorly understood, partly due to its relative rarity. Although tobacco and alcohol exposures are known carcinogens, their association with male breast cancer risk remains ill-defined.Methods: The Male Breast Cancer Pooling Project consortium provided 2,378 cases and 51,959 controls for analysis from 10 case–control and 10 cohort studies. Individual participant data were harmonized and pooled. Unconditional logistic regression was used to estimate study design–specific (case–control/cohort) ORs and 95% confidence intervals (CI), which were then combined using fixed-effects meta-analysis.Results: Cigarette smoking status, smoking pack-years, duration, intensity, and age at initiation were not associated with male breast cancer risk. Relations with cigar and pipe smoking, tobacco chewing, and snuff use were also null. Recent alcohol consumption and average grams of alcohol consumed per day were also not associated with risk; only one subanalysis of very high recent alcohol consumption (>60 g/day) was tentatively associated with male breast cancer (ORunexposed referent = 1.29; 95% CI, 0.97–1.71; OR>0–<7 g/day referent = 1.36; 95% CI, 1.04–1.77). Specific alcoholic beverage types were not associated with male breast cancer. Relations were not altered when stratified by age or body mass index.Conclusions: In this analysis of the Male Breast Cancer Pooling Project, we found little evidence that tobacco and alcohol exposures were associated with risk of male breast cancer.Impact: Tobacco and alcohol do not appear to be carcinogenic for male breast cancer. Future studies should aim to assess these exposures in relation to subtypes of male breast cancer. Cancer Epidemiol Biomarkers Prev; 24(3); 520–31. ©2014 AACR.

BACKGROUND:Associations between stomach and esophageal cancer and exposures to dusts, metals, chemicals, and endotoxin in the workplace are not very well understood, particularly in women. METHODS:We followed 267,400 female textile workers in Shanghai, China for cancer incidence from 1989 to 2006. Stomach (n = 1374) and esophageal (n = 190) cancer cases were identified and a comparison subcohort (n = 3187) was randomly selected. Cox proportional hazard modeling was used, adjusting for age and smoking. RESULTS:Increasing stomach cancer risk was observed with increasing duration of synthetic fiber dust exposure (p = 0.03), although the magnitude of effect was small (20 + years: HR = 1.2, 95% CI 1.1-1.4). Trends with endotoxin exposure were modestly inversed for esophageal cancer and increased for stomach cancer, but with little deviation from a null association. CONCLUSIONS:Our findings demonstrate that long durations of synthetic fiber dust exposure can increase stomach cancer risk in women, but provide limited support for associations with other textile industry exposures.

BACKGROUND The etiology of male breast cancer is poorly understood, partly because of its relative rarity. Although genetic factors are involved, less is known regarding the role of anthropometric and hormonally related risk factors. METHODS In the Male Breast Cancer Pooling Project, a consortium of 11 case-control and 10 cohort investigations involving 2405 case patients (n = 1190 from case-control and n = 1215 from cohort studies) and 52013 control subjects, individual participant data were harmonized and pooled. Unconditional logistic regression generated study design-specific (case-control/cohort) odds ratios (ORs) and 95% confidence intervals (CIs), with exposure estimates combined using fixed effects meta-analysis. All statistical tests were two-sided. RESULTS Risk was statistically significantly associated with weight (highest/lowest tertile: OR = 1.36; 95% CI = 1.18 to 1.57), height (OR = 1.18; 95% CI = 1.01 to 1.38), and body mass index (BMI; OR = 1.30; 95% CI = 1.12 to 1.51), with evidence that recent rather than distant BMI was the strongest predictor. Klinefelter syndrome (OR = 24.7; 95% CI = 8.94 to 68.4) and gynecomastia (OR = 9.78; 95% CI = 7.52 to 12.7) were also statistically significantly associated with risk, relations that were independent of BMI. Diabetes also emerged as an independent risk factor (OR = 1.19; 95% CI = 1.04 to 1.37). There were also suggestive relations with cryptorchidism (OR = 2.18; 95% CI = 0.96 to 4.94) and orchitis (OR = 1.43; 95% CI = 1.02 to 1.99). Although age at onset of puberty and histories of infertility were unrelated to risk, never having had children was statistically significantly related (OR = 1.29; 95% CI = 1.01 to 1.66). Among individuals diagnosed at older ages, a history of fractures was statistically significantly related (OR = 1.41; 95% CI = 1.07 to 1.86). CONCLUSIONS Consistent findings across case-control and cohort investigations, complemented by pooled analyses, indicated important roles for anthropometric and hormonal risk factors in the etiology of male breast cancer. Further investigation should focus on potential roles of endogenous hormones.

Endotoxin (lipopolysaccharide) is a widespread contaminant in many environmental settings. Since the 1970s, there has been generally consistent evidence indicating reduced risks for lung cancer associated with occupational endotoxin exposure. We updated a case–cohort study nested within a cohort of 267 400 female textile workers in Shanghai, China. We compared exposure histories of 1456 incident lung cancers cases diagnosed during 1989–2006 with those of a reference subcohort of 3022 workers who were free of lung cancer at the end of follow-up. We applied Cox proportional hazards modelling to estimate exposure–response trends, adjusted for age and smoking, for cumulative exposures lagged by 0, 10, and 20 years, and separately for time windows of ⩽15 and >15 years since first exposure. We observed no associations between cumulative exposure and lung cancer, irrespective of lag interval. In contrast, analyses by exposure time windows revealed modestly elevated, but not statistically significant relative risks (∼1.27) at the highest three exposure quintiles for exposures that occurred >15 years since first exposure. The findings do not support a protective effect of endotoxin, but are suggestive of possible lung cancer promotion with increasing time since first exposure.

In: Journal of the National Cancer Institute, Vol. 106, No. 5, dju117, 14.05.2014 … Brinton, Louise A. ; Cook, Michael B. ; McCormack, Valerie ; Johnson, Kenneth C. ; Olsson, Håkan ; Casagrande, John T. ; Cooke, Rosie ; Falk, Roni T. ; Gapstur, Susan M. ; Gaudet, Mia M. ; Gaziano, J. Michael ; Gkiokas, Georgios ; Guénel, Pascal ; Henderson, Brian E. ; Hollenbeck, Albert ; Hsing, Ann W. ; Kolonel, Laurence N. ; Isaacs, Claudine ; Lubin, Jay H. ; Michels, Karin B. ; Negri, Eva ; Parisi, Dominick ; Petridou, Eleni Th ; Pike, Malcolm C. ; Riboli, Elio ; Sesso, Howard D. ; Snyder, Kirk ; Swerdlow, Anthony J. ; Trichopoulos, Dimitrios ; Ursin, Giske ; Van Den Brandt, Piet A. ; Van Den Eeden, Stephen K. ; Weiderpass, Elisabete ; Willett, Walter C. ; Ewertz, Marianne ; Thomas, David B. / Erratum : Anthropometric and hormonal risk factors for male breast cancer …

Low‐ and middle‐income countries (LMICs) are undergoing an increase in incidence of breast cancer, but have inadequate resources to implement mammographic screening. Clinical breast examination (CBE) has been suggested as an alternative to mammography in these settings. We compared the results of CBE screening by 47 midwives and 15 trained lay health workers to results of independently performed mammographic screening in an unscreened population of 1,179 women in Jakarta, Indonesia. Two hundred and eight‐nine (24.5%) of the screened women had a suspicious finding on CBE and/or mammography. Sixty‐nine (23.9%) of these women had both an abnormal CBE and mammogram; 98 (33.9%) had an abnormal CBE, but a normal mammogram; and 122 (42.2%) had a normal CBE and an abnormal mammogram. Fourteen breast cancers were diagnosed. Of these, 13 were identified by both mammogram and CBE. One breast cancer was identified from an abnormal mammogram, but had a normal CBE. One hundred and sixty‐seven (14.2%) of the CBEs required additional work‐up to diagnose 13 of the 14 cancers detected by mammography. In comparison, 191 (16.2%) of mammograms required additional work‐up to diagnose the 14 cancers. Unfortunately, only 42.8% of the women diagnosed with cancer returned for treatment. In an unscreened population in LMICs such as Indonesia, CBE is nearly as effective as mammography in detecting prevalent breast cancers. However identifying and overcoming barriers to appropriate treatment of women who are identified as having breast cancer are essential to the success of any screening program.