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However, it is unclear how these factors affect combinatorial biomarkers for aiding treatment decision-making in breast cancer.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>Patients were 8179 women with histologically confirmed invasive breast cancer, diagnosed and treated in a large cancer hospital in Beijing, China. Individual clinicopathological (tumor size, grade, lymph nodes) and immunohistochemical (IHC: ER, PR, HER2, KI67) markers were used to define clinically relevant combinatorial prognostic biomarkers, including the Nottingham Prognostic Index (NPI: combining size, grade, nodes) and IHC4 score (combining ER, PR, HER2, KI67). Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between breast cancer risk factors and quartiles (Q1\u2013Q4) of NPI and IHC4 were assessed in multivariable polytomous logistic regression models.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Overall, increasing parity (OR<jats:sub>trend<\/jats:sub>(95% CI)\u2009=\u20091.20(1.05\u20131.37);<jats:italic>P<\/jats:italic><jats:sub>trend<\/jats:sub>\u2009=\u20090.007), overweight (OR(95% CI)<jats:sub>vs normal<\/jats:sub>\u2009=\u20091.60(1.29\u20131.98)), and obesity (OR(95% CI) <jats:sub>vs normal<\/jats:sub>\u2009=\u20092.12(1.43\u20133.14)) were associated with higher likelihood of developing tumors with high (Q4) versus low (Q1) NPI score. Conversely, increasing age (OR<jats:sub>trend<\/jats:sub>(95% CI)\u2009=\u20090.75(0.66\u20130.84);<jats:italic>P<\/jats:italic><jats:sub>trend<\/jats:sub>\u2009&lt;\u20090.001) and positive family history of breast cancer (FHBC) (OR(95% CI)\u2009=\u20090.66(0.45\u20130.95)) were inversely associated with NPI. Only body mass index (BMI) was associated with IHC4, with overweight (OR(95% CI) <jats:sub>vs normal<\/jats:sub>\u2009=\u20090.82(0.66\u20131.02)) and obese (OR(95% CI) <jats:sub>vs normal<\/jats:sub>\u2009=\u20090.52(0.36\u20130.76)) women less likely to develop high IHC4 tumors. Notably, elevated BMI was associated with higher NPI irrespective of hormone receptor-expression status.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>Our findings indicate that factors affecting breast cancer incidence, particularly age, parity, FHBC, and BMI, may impact clinically relevant prognostic biomarkers with implications for surveillance, prognostication, and counseling.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s10549-021-06294-5","type":"journal-article","created":{"date-parts":[[2021,6,29]],"date-time":"2021-06-29T14:27:09Z","timestamp":1624976829000},"page":"483-495","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Impact of breast cancer risk factors on clinically relevant prognostic biomarkers for primary breast cancer"],"prefix":"10.1007","volume":"189","author":[{"given":"Mustapha","family":"Abubakar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changyuan","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hela","family":"Koka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph","family":"Deng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nan","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Montserrat","family":"Garcia-Closas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ning","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4451-8664","authenticated-orcid":false,"given":"Xiaohong R.","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,6,29]]},"reference":[{"issue":"8","key":"6294_CR1","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1093\/annonc\/mdr304","volume":"22","author":"A Goldhirsch","year":"2011","unstructured":"Goldhirsch A, Wood WC, Coates AS, Gelber RD, Th\u00fcrlimann B, Senn H-J et al (2011) Strategies for subtypes\u2014dealing with the diversity of breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. 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