Abstract
Purpose
Breast cancer (BC) characteristics are known to influence patients survival. Social differences have been reported by previous studies for those characteristics but questions persist because of inconsistent conclusions. We aimed to investigate the impact of education on BC stage, grade, and hormone receptor (HR) status, while adjusting for potential confounders including a broad set of health behaviors, anthropometric measures, and reproductive factors.
Methods
In the French E3N cohort, 5236 women developed a primary invasive BC for which there was available information on stage, grade, and HR status. No multivariate analyses was performed for BC stage based on the lack of association in bivariate analyses. Odds ratios and confidence intervals were estimated using multinomial logistic regression models for BC grade or binomial logistic regression models for HR status of BC.
Results
Women with a lower education were diagnosed with higher grade BC compared to women with a higher education (1.32 [1.12; 1.57]). This association was slightly attenuated after adjustment for covariates independently and more strongly affected in the fully adjusted model (1.20 [0.99; 1.45]). A significant association was observed between lower education and HR- status of BC (1.20 [1.02; 1.42]) attenuated after adjustment for age at first childbirth (1.12 [0.95; 1.33]).
Conclusion
In this cohort, education was associated with BC grade and HR status but not stage at diagnosis. The link between education and BC grade was not entirely explained by the different adjustments. A specific mechanism could be at play and deserves further investigations.
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Data availability
The dataset generated and/or analyzed during the current study is not publicly available and permission to use the data is restricted to the team in charge of the cohort, which can be extended to collaborators with a specific research agreement.
References
Bertos NR, Park M (2011) Breast cancer—one term, many entities? J Clin Invest 121:3789–3796. https://doi.org/10.1172/JCI57100
Perou CM, Sørlie T, Eisen MB et al (2000) Molecular portraits of human breast tumours. Nature 406:747–752. https://doi.org/10.1038/35021093
Howlader N, Cronin KA, Kurian AW, Andridge R (2018) Differences in breast cancer survival by molecular subtypes in the United States. Cancer Epidemiol Biomarkers Prev 27:619–626. https://doi.org/10.1158/1055-9965.EPI-17-0627
Bastiaannet E, Craen AJM, Kuppen PJK et al (2010) Socioeconomic differences in survival among breast cancer patients in the Netherlands not explained by tumor size. Breast Cancer Res Treat 127:721–727. https://doi.org/10.1007/s10549-010-1250-z
Kaffashian F, Godward S, Davies T et al (2003) Socioeconomic effects on breast cancer survival: proportion attributable to stage and morphology. Br J Cancer 89:1693–1696. https://doi.org/10.1038/sj.bjc.6601339
Yu XQ (2009) Socioeconomic disparities in breast cancer survival: relation to stage at diagnosis, treatment and race. BMC Cancer 9:364. https://doi.org/10.1186/1471-2407-9-364
Feller A, Schmidlin K, Bordoni A et al (2017) Socioeconomic and demographic disparities in breast cancer stage at presentation and survival: a Swiss population-based study. Int J Cancer 141:1529–1539. https://doi.org/10.1002/ijc.30856
Gentil-Brevet J, Colonna M, Danzon A et al (2008) The influence of socio-economic and surveillance characteristics on breast cancer survival: a French population-based study. Br J Cancer 98:217–224. https://doi.org/10.1038/sj.bjc.6604163
Orsini M, Trétarre B, Daurès J-P, Bessaoud F (2016) Individual socioeconomic status and breast cancer diagnostic stages: a French case-control study. Eur J Public Health 26:445–450. https://doi.org/10.1093/eurpub/ckv233
Riba LA, Gruner RA, Alapati A, James TA (2019) Association between socioeconomic factors and outcomes in breast cancer. Breast J 25:488–492. https://doi.org/10.1111/tbj.13250
Berger F, Doussau A, Gautier C et al (2012) Impact of socioeconomic status on stage at diagnosis of breast cancer. Rev Epidemiol Sante Publique 60:19–29. https://doi.org/10.1016/j.respe.2011.08.066
Adams J, White M, Forman D (2004) Are there socioeconomic gradients in stage and grade of breast cancer at diagnosis? Cross sectional analysis of UK cancer registry data. BMJ 329:142. https://doi.org/10.1136/bmj.38114.679387.AE
Taylor A, Cheng KK (2003) Social deprivation and breast cancer. J Public Health Med 25:228–233. https://doi.org/10.1093/pubmed/fdg072
DeSantis C, Jemal A, Ward E (2010) Disparities in breast cancer prognostic factors by race, insurance status, and education. Cancer Causes Control 21:1445–1450. https://doi.org/10.1007/s10552-010-9572-z
McKenzie F, Jeffreys M, ’t Mannetje A, Pearce N, (2008) Prognostic factors in women with breast cancer: inequalities by ethnicity and socioeconomic position in New Zealand. Cancer Causes Control 19:403–411. https://doi.org/10.1007/s10552-007-9099-0
Ag C, A S, Dw L, et al (1994) Relation between socioeconomic deprivation and pathological prognostic factors in women with breast cancer. BMJ (Clinical Research Ed). https://doi.org/10.1136/bmj.309.6961.1054
Gupta A, Jones K, Deveaux A et al (2021) Association of life-course educational attainment and breast cancer grade in the MEND study. Ann Glob Health 87:59. https://doi.org/10.5334/aogh.3142
Thomson CS, Hole DJ, Twelves CJ et al (2001) Prognostic factors in women with breast cancer: distribution by socioeconomic status and effect on differences in survival. J Epidemiol Community Health 55:308–315. https://doi.org/10.1136/jech.55.5.308
Bauer KR, Brown M, Cress RD et al (2007) Descriptive analysis of estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative invasive breast cancer, the so-called triple-negative phenotype: a population-based study from the California cancer registry. Cancer 109:1721–1728. https://doi.org/10.1002/cncr.22618
Andaya AA, Enewold L, Horner M-J et al (2012) Socioeconomic disparities and breast cancer hormone receptor status. Cancer Causes Control 23:951–958. https://doi.org/10.1007/s10552-012-9966-1
Barber LE, Zirpoli GR, Cozier YC et al (2021) Neighborhood disadvantage and individual-level life stressors in relation to breast cancer incidence in US Black women. Breast Cancer Res 23:108. https://doi.org/10.1186/s13058-021-01483-y
Auguste A, Cortet M, Dabakuyo-Yonli TS et al (2017) Breast cancer subtype of French women is not influenced by socioeconomic status: A population-based-study. PLoS ONE 12:e0170069. https://doi.org/10.1371/journal.pone.0170069
Akinyemiju TF, Pisu M, Waterbor JW, Altekruse SF (2015) Socioeconomic status and incidence of breast cancer by hormone receptor subtype. Springerplus. https://doi.org/10.1186/s40064-015-1282-2
Lamy S, Molinié F, Daubisse-Marliac L et al (2019) Using ecological socioeconomic position (SEP) measures to deal with sample bias introduced by incomplete individual-level measures: inequalities in breast cancer stage at diagnosis as an example. BMC Public Health 19:857. https://doi.org/10.1186/s12889-019-7220-4
Khalatbari-Soltani S, Maccora J, Blyth FM et al (2022) Measuring education in the context of health inequalities. Int J Epidemiol 51:701–708. https://doi.org/10.1093/ije/dyac058
Berger E, Maitre N, Romana Mancini F et al (2020) The impact of lifecourse socio-economic position and individual social mobility on breast cancer risk. BMC Cancer 20:1138. https://doi.org/10.1186/s12885-020-07648-w
Clavel-Chapelon F (2015) Cohort profile: the French E3N cohort study. Int J Epidemiol 44:801–809. https://doi.org/10.1093/ije/dyu184
Riboli E, Hunt KJ, Slimani N et al (2002) European prospective investigation into cancer and nutrition (EPIC): study populations and data collection. Public Health Nutr 5:1113–1124. https://doi.org/10.1079/PHN2002394
Sobin LH, Gospodarowicz MK, Wittekind C (1974) TNM classification of malignant tumours, 7th edn. Wiley-Blackwell
van Buuren S, Groothuis-Oudshoorn CGM (2011) mice: Multivariate imputation by chained equations in R. J Stat Softw 45:1–67
van Ginkel JR, Linting M, Rippe RCA, van der Voort A (2020) Rebutting existing misconceptions about multiple imputation as a method for handling missing data. J Pers Assess 102:297–308. https://doi.org/10.1080/00223891.2018.1530680
Rubin DB (1976) Inference and missing data. Biometrika 63:581–592. https://doi.org/10.1093/biomet/63.3.581
Lyratzopoulos G, Abel GA, Brown CH et al (2013) Socio-demographic inequalities in stage of cancer diagnosis: evidence from patients with female breast, lung, colon, rectal, prostate, renal, bladder, melanoma, ovarian and endometrial cancer. Ann Oncol 24:843–850. https://doi.org/10.1093/annonc/mds526
Flamant C, Gauthier E, Clavel-Chapelon F (2006) Determinants of non-compliance to recommendations on breast cancer screening among women participating in the French E3N cohort study. Eur J Cancer Prev 15:27–33. https://doi.org/10.1097/01.cej.0000180666.11958.60
Kelly-Irving M, Delpierre C (2018) The embodiment dynamic over the life course: a case for examining cancer aetiology. In: Meloni M, Cromby J, Fitzgerald D, Lloyd S (eds) The Palgrave handbook of biology and society. Palgrave Macmillan, London, pp 519–540
Chandola T, Clarke P, Morris JN, Blane D (2006) Pathways between education and health: a causal modelling approach. J R Stat Soc A 169:337–359. https://doi.org/10.1111/j.1467-985X.2006.00411.x
Barboza Solís C, Kelly-Irving M, Fantin R et al (2015) Adverse childhood experiences and physiological wear-and-tear in midlife: findings from the 1958 British birth cohort. Proc Natl Acad Sci USA 112:E738-746. https://doi.org/10.1073/pnas.1417325112
Ding X, Barban N, Mills MC (2019) Educational attainment and allostatic load in later life: evidence using genetic markers. Prev Med 129:105866. https://doi.org/10.1016/j.ypmed.2019.105866
Xing CY, Doose M, Qin B et al (2020) Prediagnostic allostatic load as a predictor of poorly differentiated and larger sized breast cancers among Black women in the women’s circle of health follow-up study. Cancer Epidemiol Biomarkers Prev 29:216–224. https://doi.org/10.1158/1055-9965.EPI-19-0712
Dos Santos Silva I, Beral V (1997) Socioeconomic differences in reproductive behaviour. IARC Sci Publ 138:285–308
Gaudet MM, Gierach GL, Carter BD et al (2018) Pooled analysis of nine cohorts reveals breast cancer risk factors by tumor molecular subtype. Cancer Res 78:6011–6021. https://doi.org/10.1158/0008-5472.CAN-18-0502
Barnard ME, Boeke CE, Tamimi RM (2015) Established breast cancer risk factors and risk of intrinsic tumor subtypes. Biochim Biophys Acta 1856:73–85. https://doi.org/10.1016/j.bbcan.2015.06.002
Yang XR, Chang-Claude J, Goode EL et al (2011) Associations of breast cancer risk factors with tumor subtypes: a pooled analysis from the breast cancer association consortium studies. JNCI J Natl Cancer Inst 103:250. https://doi.org/10.1093/jnci/djq526
Prakash O, Hossain F, Danos D et al (2020) Racial disparities in triple negative breast cancer: a review of the role of biologic and non-biologic factors. Front Public Health 8:576964. https://doi.org/10.3389/fpubh.2020.576964
Rauscher GH, Campbell RT, Wiley EL et al (2016) Mediation of racial and ethnic disparities in estrogen/progesterone receptor-negative breast cancer by socioeconomic position and reproductive factors. Am J Epidemiol 183:884–893. https://doi.org/10.1093/aje/kwv226
Acknowledgments
This work was supported by La Ligue nationale contre le cancer [Equipe Labellisée LIGUE 2017/CD]). The E3N cohort is being carried out with the financial support of the “Mutuelle Générale de l’Education Nationale” (MGEN); European Community; French League against Cancer (LNCC); Gustave Roussy Institute (IGR); French Institute of Health and Medical Research (INSERM).
Funding
This work was supported by the French National Institute of Cancer [SHSESP 2017-130 to CD]. The funder had no role in the study design, analysis and interpretation of data and in writing the manuscript.
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CD, RC, GS designed research; AG, AF, LD, MCB, GS collected and controlled the data; AG contributed to data acquisition and preparation. EB performed the statistical analysis and wrote the first draft of manuscript. CD, RC, EB, and GS discussed the results. All authors critically revised the manuscript. All authors read and approved the final manuscript.
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The E3N study was approved by the French Commission for Data Protection and Privacy (NCT03285230, CNIL/Commission national informatique et libertés-no. 327346 V 13). All methods were carried out in accordance with relevant guidelines and regulations.
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Berger, E., Gelot, A., Fournier, A. et al. Educational level and characteristics of invasive breast cancer: findings from a French prospective cohort. Cancer Causes Control (2024). https://doi.org/10.1007/s10552-024-01873-5
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DOI: https://doi.org/10.1007/s10552-024-01873-5