Assessing the Impact of Socio-economic Variables on Breast Cancer Treatment Outcome Disparity

  • Published : 2013.12.31


Background: We studied Surveillance, Epidemiology and End Results (SEER) breast cancer data of Georgia USA to analyze the impact of socio-economic factors on the disparity of breast cancer treatment outcome. Materials and Methods: This study explored socio-economic, staging and treatment factors that were available in the SEER database for breast cancer from Georgia registry diagnosed in 2004-2009. An area under the receiver operating characteristic curve (ROC) was computed for each predictor to measure its discriminatory power. The best biological predictors were selected to be analyzed with socio-economic factors. Survival analysis, Kolmogorov-Smirnov 2-sample tests and Cox proportional hazard modeling were used for univariate and multivariate analyses of time to breast cancer specific survival data. Results: There were 34,671 patients included in this study, 99.3% being females with breast cancer. This study identified race and education attainment of county of residence as predictors of poor outcome. On multivariate analysis, these socio-economic factors remained independently prognostic. Overall, race and education status of the place of residence predicted up to 10% decrease in cause specific survival at 5 years. Conclusions: Socio-economic factors are important determinants of breast cancer outcome and ensuring access to breast cancer treatment may eliminate disparities.


  1. Agarwal J, Agarwal S, Pappas L, Neumayer L (2012). A population-based study of breast cancer-specific survival following mastectomy and immediate or early-delayed breast reconstruction. Breast J, 18, 226-32.
  2. Beal SH, Martinez S R, Canter RJ, et al (2010). Survival in 12,653 breast cancer patients with extensive axillary lymph node metastasis in the anthracycline era. Med Oncol, 27, 1420-1424.
  3. Cheung R (2012). Poor treatment outcome of neuroblastoma and other peripheral nerve cell tumors may be related to under usage of radiotherapy and socio-economic disparity: A US SEER data analysis. Asian Pac J Cancer Prev, 13, 4587-91.
  4. Cheung R, Altschuler MD, D'Amico AV, et al (2001a). ROCoptimization may improve risk stratification of prostate cancer patients. Urology, 57, 286-90.
  5. Cheung R, Altschuler MD, D'Amico AV, et al (2001b). Using the receiver operator characteristic curve to select pretreatment and pathologic predictors for early and late post-prostatectomy PSA failure. Urology, 58, 400-5.
  6. Clarke M, Coates AS, Darby SC, et al (2008). Adjuvant chemotherapy in oestrogen-receptor-poor breast cancer: patient-level meta-analysis of randomised trials. Lancet, 371, 29-40.
  7. Davies C, Godwin J, Gray R, et al (2011). Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials. Lancet, 378, 771-84.
  8. Downing S, Ahuja N, Oyetunji TA, et al (2010). Disparity in limb-salvage surgery among sarcoma patients. Am J Surg, 199, 549-53.
  9. Dragun A E, Huang B, Gupta S, Crew J B, and Tucker T C (2012). One decade later: trends and disparities in the application of post-mastectomy radiotherapy since the release of the american society of clinical oncology clinical practice guidelines. Int J Radiat Oncol Biol Phys, 83, e591-6.
  10. Feltner FJ, Ely GE, Whitler ET, Gross D, Dignan M (2012). Effectiveness of community health workers in providing outreach and education for colorectal cancer screening in Appalachian Kentucky. Soc Work Health Care, 51, 430-40.
  11. Gross C P, Smith B D, Wolf E, Andersen M (2008). Racial disparities in cancer therapy: did the gap narrow between 1992 and 2002? Cancer, 112, 900-8.
  12. Hanley JA, McNeil BJ (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143, 29-36.
  13. Harlan L, Brawley O, Pommerenke F, Wali P, Kramer B (1995). Geographic, age, and racial variation in the treatment of local/regional carcinoma of the prostate. J Clin Oncol, 13, 93-100.
  14. Jagsi R, Abrahamse P, Hawley ST, et al (2012). Underascertainment of radiotherapy receipt in Surveillance, Epidemiology, and End Results registry data. Cancer, 118, 333-41.
  15. Lund MJ, Brawley OP, Ward KC, et al (2008). Parity and disparity in first course treatment of invasive breast cancer. Breast Cancer Res Treat, 109, 545-57.
  16. Martinez SR, Beal SH, Chen SL, et al (2010). Disparities in the use of radiation therapy in patients with local-regionally advanced breast cancer. Int J Radiat Oncol Biol Phys, 78, 787-92.
  17. Martinez S R, Tseng W H, Canter R J, et al (2012). Do radiation use disparities influence survival in patients with advanced breast cancer? Cancer, 118, 196-204.
  18. Roder D, Webster F, Zorbas H, Sinclair S (2012). Breast screening and breast cancer survival in Aboriginal and Torres Strait Islander women of Australia. Asian Pac J Cancer Prev, 13, 147-55.
  19. Roder D, Zorbas H, Kollias J, et al (2013). Risk factors for poorer breast cancer outcomes in residents of remote areas of Australia. Asian Pac J Cancer Prev, 14, 547-52.
  20. Rudat V, Brune-Erbe I, Noureldin A, et al (2012). Epidemiology of breast cancer patients at a tertiary care center in the Eastern Province of Saudi Arabia. Gulf J Oncology, 1, 45-9.
  21. Sail K, Franzini L, Lairson D, Du X (2012). Differences in treatment and survival among African-American and Caucasian women with early stage operable breast cancer. Ethn Health, 17, 309-23.
  22. Schlichting JA, Soliman AS, Schairer C, et al (2012). Association of inflammatory and noninflammatory breast cancer with socioeconomic characteristics in the Surveillance, Epidemiology, and End Results database, 2000-2007. Cancer Epidemiol Biomarkers Prev, 21, 155-65.
  23. Schootman M, Jeffe DB, Lian M, Gillanders WE, Aft R (2009). The role of poverty rate and racial distribution in the geographic clustering of breast cancer survival among older women: a geographic and multilevel analysis. Am J Epidemiol, 169, 554-61.
  24. Shavers VL, Harlan LC, and Stevens JL (2003). Racial/ethnic variation in clinical presentation, treatment, and survival among breast cancer patients under age 35. Cancer, 97, 134-47.
  25. Siegel R, Desantis C, Virgo K, et al (2012). Cancer treatment and survivorship statistics, 2012. CA Cancer J Clin, 62, 220-41.
  26. Voordeckers M, Vinh-Hung V, Lamote J, Bretz A, Storme G (2009). Survival benefit with radiation therapy in nodepositive breast carcinoma patients. Strahlenther Onkol, 185, 656-62.
  27. Wampler NS, Lash TL, Silliman RA, Heeren TC (2005). Breast cancer survival of American Indian/Alaska Native women, 1973-1996. Soz Praventivmed, 50, 230-7.
  28. Yan W, Christos P, Nori D, Chao KS, Ravi A (2012). Is there a cause-specific survival benefit of postmastectomy radiation therapy in women younger than age 50 with T3N0 invasive breast cancer? A SEER database analysis: outcomes by Receptor Status/Race/Age: Analysis Using the NCI Surveillance, Epidemiology, and End Results (SEER) Database. Am J Clin Oncol,
  29. Yao N, Lengerich E J, and Hillemeier M M (2012). Breast cancer mortality in Appalachia: reversing patterns of disparity over

Cited by

  1. Cancer Prediction Based on Radical Basis Function Neural Network with Particle Swarm Optimization vol.15, pp.18, 2014,
  2. Years of Potential Life Lost Due to Breast and Cervical Cancer: a Challenge for Brazilian Public Policy vol.15, pp.23, 2015,