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  2. Matching Content Categories
  3. CMS
  4. Monthly Traffic Estimate
  5. How Does Link.springer.com Make Money
  6. Keywords
  7. Topics
  8. Questions
  9. Schema
  10. External Links
  11. Analytics And Tracking
  12. Libraries
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We are analyzing https://link.springer.com/article/10.1007/s10552-006-0092-9.

Title:
Estimating age-specific breast cancer risks: a descriptive tool to identify age interactions | Cancer Causes & Control
Description:
Objective Clarifying age-specific female breast cancer risks and interactions may provide important etiologic clues. Method Using a population-based case–control study in Poland (2000–2003) of 2,386 incident breast cancer cases and 2,502 control subjects aged 25–74 years, we estimated age-specific breast cancer incidence rates according to risk factors. Results Breast cancer risks were elevated among women with positive family history (FH), younger age at menarche, older age at first full-term birth, nulliparity, exogenous hormonal usage, and reduced physical activity (PA). Notwithstanding overall risks, we observed statistically significant quantitative (non-crossover) and qualitative (crossover) age interactions for all risk factors except for FH and PA. For example, nulliparity compared to parity reduced breast cancer risk among women ages 25–39 years then rates crossed or reversed, after which nulliparity increased relative risks among women ages 40–74 years. Conclusion Though quantitative age interactions could be expected, qualitative interactions were somewhat counterintuitive. If confirmed in other populations, qualitative interactions for a continuous covariate such as age will be difficult to reconcile in a sequential (multistep or monolithic) ‘stochastic’ breast cancer model. Alternatively, the reversal of relative risks among younger and older women suggests subgroup heterogeneity with different etiologic mechanisms for early-onset and late-onset breast cancer types.
Website Age:
28 years and 1 months (reg. 1997-05-29).

Matching Content Categories {📚}

  • Health & Fitness
  • Education
  • Insurance

Content Management System {📝}

What CMS is link.springer.com built with?

Custom-built

No common CMS systems were detected on Link.springer.com, and no known web development framework was identified.

Traffic Estimate {📈}

What is the average monthly size of link.springer.com audience?

🌠 Phenomenal Traffic: 5M - 10M visitors per month


Based on our best estimate, this website will receive around 5,000,019 visitors per month in the current month.
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How Does Link.springer.com Make Money? {💸}

We can't figure out the monetization strategy.

Not all websites focus on profit; some are designed to educate, connect people, or share useful tools. People create websites for numerous reasons. And this could be one such example. Link.springer.com has a secret sauce for making money, but we can't detect it yet.

Keywords {🔍}

cancer, breast, google, scholar, pubmed, article, cas, risk, age, women, factors, risks, anderson, interactions, data, research, control, brinton, study, hormonal, access, natl, inst, institute, privacy, cookies, content, agespecific, lissowska, epidemiol, collaborative, med, epidemiology, author, publish, search, william, matsuno, jolanta, gail, chatterjee, years, rates, results, activity, qualitative, relative, related, res, health,

Topics {✒️}

population-based case–control study beata peplonska case–control studies month download article/chapter relative risks dhhs/nih/nci/dceg neonila szeszenia-dąbrowska marie sklodowska-curie institute jolanta lissowska author correspondence node-negative breast cancer alicja bardin-mikolajczak nurses’ health study age-specific mortality swedish population full article pdf relative risk female breast cancer check access instant access cancer statistics branch developing breast cancer national cancer institute privacy choices/manage cookies breast cancer heterogeneity based full term pregnancy identify age interactions breast cancer risk full-term birth misclassification bias related �breast tissue age hormone receptor expression related subjects risks quantitative age interactions polygenic risk score intramural research program �hormonal’ risk factors article cancer reduced physical activity european economic area witold zatonski postulated underlying biology body mass index projecting individualized probabilities november 2004 submission hormone replacement therapy risk factor status article anderson

Questions {❓}

  • Anderson WF, Althuis MD, Brinton LA, Devesa SS (2004) Is male breast cancer similar or different than female breast cancer?
  • Anderson WF, Matsuno RK (2006) Breast cancer heterogeneity: a mixture of at least two main types?
  • Colditz GA, Rosner BA (2006) What can be learnt from models of incidence rates?
  • Do they differ according to age at diagnosis?

Schema {🗺️}

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         description:Clarifying age-specific female breast cancer risks and interactions may provide important etiologic clues. Using a population-based case–control study in Poland (2000–2003) of 2,386 incident breast cancer cases and 2,502 control subjects aged 25–74 years, we estimated age-specific breast cancer incidence rates according to risk factors. Breast cancer risks were elevated among women with positive family history (FH), younger age at menarche, older age at first full-term birth, nulliparity, exogenous hormonal usage, and reduced physical activity (PA). Notwithstanding overall risks, we observed statistically significant quantitative (non-crossover) and qualitative (crossover) age interactions for all risk factors except for FH and PA. For example, nulliparity compared to parity reduced breast cancer risk among women ages 25–39 years then rates crossed or reversed, after which nulliparity increased relative risks among women ages 40–74 years. Though quantitative age interactions could be expected, qualitative interactions were somewhat counterintuitive. If confirmed in other populations, qualitative interactions for a continuous covariate such as age will be difficult to reconcile in a sequential (multistep or monolithic) ‘stochastic’ breast cancer model. Alternatively, the reversal of relative risks among younger and older women suggests subgroup heterogeneity with different etiologic mechanisms for early-onset and late-onset breast cancer types.
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      headline:Estimating age-specific breast cancer risks: a descriptive tool to identify age interactions
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      dateModified:2007-01-09T00:00:00Z
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         Absolute risks
         Relative risks
         Odds ratio
         Rate ratios
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         Biomedicine
         general
         Oncology
         Public Health
         Epidemiology
         Hematology
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                     type:PostalAddress
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                     name:Department of Cancer Epidemiology and Prevention, Cancer Center and Marie Sklodowska-Curie Institute of Oncology, Warsaw, Poland
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            name:DHHS/NIH/NCI/DCEG
            address:
               name:Biostatistics Branch, DHHS/NIH/NCI/DCEG, Bethesda, USA
               type:PostalAddress
            type:Organization
      email:[email protected]
      name:Rayna K. Matsuno
      affiliation:
            name:National Cancer Institute, National Institute of Health
            address:
               name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
               type:PostalAddress
            type:Organization
      name:Mark E. Sherman
      affiliation:
            name:National Cancer Institute, National Institute of Health
            address:
               name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
               type:PostalAddress
            type:Organization
      name:Jolanta Lissowska
      affiliation:
            name:National Cancer Institute, National Institute of Health
            address:
               name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
               type:PostalAddress
            type:Organization
            name:Cancer Center and Marie Sklodowska-Curie Institute of Oncology
            address:
               name:Department of Cancer Epidemiology and Prevention, Cancer Center and Marie Sklodowska-Curie Institute of Oncology, Warsaw, Poland
               type:PostalAddress
            type:Organization
      name:Mitchell H. Gail
      affiliation:
            name:National Cancer Institute, National Institute of Health
            address:
               name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
               type:PostalAddress
            type:Organization
      name:Louise A. Brinton
      affiliation:
            name:National Cancer Institute, National Institute of Health
            address:
               name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
               type:PostalAddress
            type:Organization
      name:Xiaohong (Rose) Yang
      affiliation:
            name:National Cancer Institute, National Institute of Health
            address:
               name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
               type:PostalAddress
            type:Organization
      name:Beata Peplonska
      affiliation:
            name:Nofer Institute of Occupational Medicine
            address:
               name:Nofer Institute of Occupational Medicine, Łódź, Poland
               type:PostalAddress
            type:Organization
      name:Bingshu E. Chen
      affiliation:
            name:National Cancer Institute, National Institute of Health
            address:
               name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
               type:PostalAddress
            type:Organization
      name:Philip S. Rosenberg
      affiliation:
            name:National Cancer Institute, National Institute of Health
            address:
               name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
               type:PostalAddress
            type:Organization
      name:Nilanjan Chatterjee
      affiliation:
            name:National Cancer Institute, National Institute of Health
            address:
               name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
               type:PostalAddress
            type:Organization
      name:Neonila Szeszenia-Dąbrowska
      affiliation:
            name:Nofer Institute of Occupational Medicine
            address:
               name:Nofer Institute of Occupational Medicine, Łódź, Poland
               type:PostalAddress
            type:Organization
      name:Alicja Bardin-Mikolajczak
      affiliation:
            name:Cancer Center and Marie Sklodowska-Curie Institute of Oncology
            address:
               name:Department of Cancer Epidemiology and Prevention, Cancer Center and Marie Sklodowska-Curie Institute of Oncology, Warsaw, Poland
               type:PostalAddress
            type:Organization
      name:Witold Zatonski
      affiliation:
            name:Cancer Center and Marie Sklodowska-Curie Institute of Oncology
            address:
               name:Department of Cancer Epidemiology and Prevention, Cancer Center and Marie Sklodowska-Curie Institute of Oncology, Warsaw, Poland
               type:PostalAddress
            type:Organization
      name:Susan S. Devesa
      affiliation:
            name:National Cancer Institute, National Institute of Health
            address:
               name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
               type:PostalAddress
            type:Organization
      name:Montserrat García-Closas
      affiliation:
            name:National Cancer Institute, National Institute of Health
            address:
               name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
               type:PostalAddress
            type:Organization
PostalAddress:
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
      name:Biostatistics Branch, DHHS/NIH/NCI/DCEG, Bethesda, USA
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
      name:Department of Cancer Epidemiology and Prevention, Cancer Center and Marie Sklodowska-Curie Institute of Oncology, Warsaw, Poland
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
      name:Nofer Institute of Occupational Medicine, Łódź, Poland
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
      name:Nofer Institute of Occupational Medicine, Łódź, Poland
      name:Department of Cancer Epidemiology and Prevention, Cancer Center and Marie Sklodowska-Curie Institute of Oncology, Warsaw, Poland
      name:Department of Cancer Epidemiology and Prevention, Cancer Center and Marie Sklodowska-Curie Institute of Oncology, Warsaw, Poland
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
      name:Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, USA
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