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July 26, 2020 /PRNewswire/ -- A team led by researchers at the University of California, San Francisco, Genetek and Stanford University has created a new model of breast cancer causes designed to capture the complex interrelationships between dozens of primary and secondary breast cancer causes and stimulate further research.
breast cancer is the most common cancer in women, with an estimated 268,600 new cases and 41,760 deaths in the United States in 2019.
although breast cancer can be successfully treated if detected early.
but researchers are still looking for the best way to prevent it.
researchers say the model balances the relationships and potential interactions between factors we now know that women can control, including alcohol consumption, hormone replacement therapy, overweight and obesity, and areas of public health policy that affect how people are affected by social factors.
it illustrates the dynamics and unpredictability of many different causes of breast cancer interactions and effects.
the model, published recently in the American Cancer Research Association's journal Cancer Research, Biomarkers and Prevention, includes biological variables such as age, breast density, genes, and physical risk factors such as exposure to cancer-causing chemicals, radiation, and secondhand smoke.
Photo Source: Overall, the model, known as Model II, illustrates 96 potential interactions between the biological, behavioral, social and physical realms of breast cancer.
the model was created by a multidisciplinary team with expertise in epidemiology, biostatistics, mathematics and computational modeling, breast cancer biology, toxicology, genetics, population health and breast cancer advocacy.
it updated Model I, an earlier model created by the same team and published in 2014, that described 83 such relationships.
researchers stress that Model II is primarily designed to inform researchers, public health policy makers and the public about the complex and interactive nature of breast cancer at the population level.
researchers hope that papers and online models will work together to facilitate discussion and decision-making.
they would also like to highlight areas where more research is needed to increase our understanding of breast cancer prevention and control.
researchers say that while this pattern is not helpful in diagnosing or treating individual patients, it can help doctors educate them about the causes of breast cancer by making them aware that "it's not just one thing that causes the disease."
() References: Robert A. Hiatt et al. A Complex Systems Model of Breast Cancer Etiology: The Paradigm II Conceptual Model. Cancer simry biomarkers and prevention. 2020. DOI: 10.1158/1055-9965.EPI-20-0016.