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Breast Cancer Research and Treatment

, Volume 130, Issue 3, pp 953–964 | Cite as

The effect of delays in treatment for breast cancer metastasis on survival

  • Su Yon JungEmail author
  • Susan M. Sereika
  • Faina Linkov
  • Adam Brufsky
  • Joel L. Weissfeld
  • Margaret Rosenzweig
Epidemiology

Abstract

It is generally accepted that delay in receiving treatment for breast cancer results in adverse outcomes. The purpose of this study was to evaluate the impact of delay in treatment after the diagnosis of metastatic disease on survival measured from metastatic breast cancer diagnosis and from first treatment while controlling for immortal time effect among patients with metastatic breast cancer. A total of 553 patients with breast cancer metastasis diagnosis from one large urban practice have been followed between January 1, 1999 and June 30, 2008. Prognostic factors and outcomes of these patients were analyzed using log-rank test and Cox regression model. Backward stepwise selection of covariates was conducted to assess the association of treatment delay with survival. The median survival was 40 months (range 1–114 months), with 265 (47.9%) women alive and 288 (52.1%) having died at the end of the follow-up period. Treatment delays of more than 12 weeks had impact on poor survival from first treatment than the delays of 4–12 weeks with borderline significance level (HR 1.76, 95% CI 0.99–3.13, P = 0.056) in multivariate analysis, adjusted by BMI, history of hypertension, ER/PR status, HER2 status, number of metastatic sites, and liver metastasis. Moreover, the interval of 12–24 weeks, compared to the interval of 4–12 weeks was associated with greater risk of death from first treatment (HR 2.39, 95% CI 1.19–4.77, P = 0.014). The treatment delay interval of >12 weeks was not related with survival since metastatic breast cancer diagnosis, compared to the 4–12 weeks of treatment delays. This study demonstrated that delays of over 12 weeks in receiving treatment for metastatic breast cancer were related to adverse survival outcomes measured from initiation of first treatment. The findings of this study support targeted efforts to ensure prompt treatment initiation in patients diagnosed with metastatic breast cancer.

Keywords

Advanced breast cancer Treatment delay Immortal time bias 

References

  1. 1.
    Surveillance Epidemiology and End Results Program (SEER) (2008). SEER Stat Database: SEER Stat Fact SheetsGoogle Scholar
  2. 2.
    Wingo PA, Tong T, Bolden S (1995) Cancer statistics, 1995. CA Cancer J Clin 45(1):8–30PubMedCrossRefGoogle Scholar
  3. 3.
    McGinn K, Moore J (2001) Metastatic breast cancer: understanding current management options. Oncol Nurs Forum 28(3):507–512 quiz 513–514PubMedGoogle Scholar
  4. 4.
    Greenberg PA et al (1996) Long-term follow-up of patients with complete remission following combination chemotherapy for metastatic breast cancer. J Clin Oncol 14(8):2197–2205PubMedGoogle Scholar
  5. 5.
    Handerson IC, Harris JR, Kinne DW (1989) Cancer of the breast. In: De Vita VT, Hellman S, Rosenberg SA (eds) Cancer principles practice of oncology, 3rd edn. Lippincott, Philadelphia, pp 1197–1268Google Scholar
  6. 6.
    Insa A et al (1999) Prognostic factors predicting survival from first recurrence in patients with metastatic breast cancer: analysis of 439 patients. Breast Cancer Res Treat 56(1):67–78PubMedCrossRefGoogle Scholar
  7. 7.
    Chang J et al (2003) Survival of patients with metastatic breast carcinoma: importance of prognostic markers of the primary tumor. Cancer 97(3):545–553PubMedCrossRefGoogle Scholar
  8. 8.
    Beslija S et al (2009) Third consensus on medical treatment of metastatic breast cancer. Ann Oncol 20(11):1771–1785PubMedCrossRefGoogle Scholar
  9. 9.
    Rezaianzadeh A et al (2009) Survival analysis of 1148 women diagnosed with breast cancer in Southern Iran. BMC Cancer 9:168PubMedCrossRefGoogle Scholar
  10. 10.
    Vincent MD et al (1986) An analysis of possible prognostic features of long term and short term survivors of metastatic breast cancer. Eur J Cancer Clin Oncol 22(9):1059–1065PubMedCrossRefGoogle Scholar
  11. 11.
    Bradley CJ, Given CW, Roberts C (2002) Race socioeconomic status, and breast cancer treatment and survival. J Natl Cancer Inst 94(7):490–496PubMedCrossRefGoogle Scholar
  12. 12.
    Whiteman MK et al (2005) Body mass and mortality after breast cancer diagnosis. Cancer Epidemiol Biomarkers Prev 14(8):2009–2014PubMedCrossRefGoogle Scholar
  13. 13.
    Braithwaite D et al (2009) Hypertension is an independent predictor of survival disparity between African-American and white breast cancer patients. Int J Cancer 124(5):1213–1219PubMedCrossRefGoogle Scholar
  14. 14.
    Ahern TP et al (2009) Impact of acquired comorbidities on all-cause mortality rates among older breast cancer survivors. Med Care 47(1):73–79PubMedCrossRefGoogle Scholar
  15. 15.
    Gregorio DI, Cummings KM, Michalek A (1983) Delay stage of disease, and survival among White and Black women with breast cancer. Am J Public Health 73(5):590–593PubMedCrossRefGoogle Scholar
  16. 16.
    Kievit J (2002) The effect of treatment delay on the prognosis of breast cancer patients. Ned Tijdschr Geneeskd 146(22):1031–1034PubMedGoogle Scholar
  17. 17.
    Gorin SS et al. (2006) Effect of race/ethnicity and treatment delay on breast cancer survival. J Clin Oncol; ASCO Annual Meeting Proceedings Part I, 24(18S):6063Google Scholar
  18. 18.
    Gorin SS, Hebert JR, Cheng B (2007) Killing time: treatment delay and breast cancer survival. J Clin Oncol; ASCO Annual Meeting Proceedings Part I, 25(18S):6589Google Scholar
  19. 19.
    Richards MA et al (1999) The influence on survival of delay in the presentation and treatment of symptomatic breast cancer. Br J Cancer 79(5–6):858–864PubMedCrossRefGoogle Scholar
  20. 20.
    Afzelius P (1994) Patient’s and doctor’s delay in primary breast cancer. Prognostic implications. Acta Oncol 33(4):345–351PubMedCrossRefGoogle Scholar
  21. 21.
    Hermann RE et al (1985) Results of conservative operations for breast cancer. Arch Surg 120(6):746–751PubMedGoogle Scholar
  22. 22.
    Sheridan B et al (1971) The effects of delay in treatment of survival rates in carcinoma of the breast. Med J Aust 1(5):262–267PubMedGoogle Scholar
  23. 23.
    Smith ER et al (2008) Breast cancer survival among economically disadvantaged women: the influences of delayed diagnosis and treatment on mortality. Cancer Epidemiol Biomarkers Prev 17(10):2882–2890PubMedCrossRefGoogle Scholar
  24. 24.
    Elmore JG et al (2005) Racial inequities in the timing of breast cancer detection, diagnosis, and initiation of treatment. Med Care 43(2):141–148PubMedCrossRefGoogle Scholar
  25. 25.
    Hershman D et al (2005) Racial disparities in treatment and survival among women with early-stage breast cancer. J Clin Oncol 23(27):6639–6646PubMedCrossRefGoogle Scholar
  26. 26.
    Vernon SW et al (1985) Ethnicity, survival, and delay in seeking treatment for symptoms of breast cancer. Cancer 55(7):1563–1571PubMedCrossRefGoogle Scholar
  27. 27.
    Neale AV, Tilley BC, Vernon SW (1986) Marital status delay in seeking treatment and survival from breast cancer. Soc Sci Med 23(3):305–312PubMedCrossRefGoogle Scholar
  28. 28.
    Charlson ME (1985) Delay in the treatment of carcinoma of the breast. Surg Gynecol Obstet 160(5):393–399PubMedGoogle Scholar
  29. 29.
    Gardner B (1978) The relationship of delay in treatment to prognosis in human cancer. Prog Clin Cancer 7:123–133PubMedGoogle Scholar
  30. 30.
    Machiavelli M et al (1989) Relation between delay and survival in 596 patients with breast cancer. Oncology 46(2):78–82PubMedCrossRefGoogle Scholar
  31. 31.
    Dennis CR, Gardner B, Lim B (1975) Analysis of survival and recurrence vs. patient and doctor delay in treatment of breast cancer. Cancer 35(3):714–720PubMedCrossRefGoogle Scholar
  32. 32.
    Luini A et al (2007) Metaplastic carcinoma of the breast, an unusual disease with worse prognosis: the experience of the European Institute of Oncology and review of the literature. Breast Cancer Res Treat 101(3):349–353PubMedCrossRefGoogle Scholar
  33. 33.
    Suissa S (2007) Immortal time bias in observational studies of drug effects. Pharmacoepidemiol Drug Saf 16(3):241–249PubMedCrossRefGoogle Scholar
  34. 34.
    Suissa S (2008) Immortal time bias in pharmaco-epidemiology. Am J Epidemiol 167(4):492–499PubMedCrossRefGoogle Scholar
  35. 35.
    Ray WA (2005) Observational studies of drugs and mortality. N Engl J Med 353(22):2319–2321PubMedCrossRefGoogle Scholar
  36. 36.
    Census 2000 summary file 3 (SF 3) (2000) US Census BureauGoogle Scholar
  37. 37.
    Richards MA et al (1999) Influence of delay on survival in patients with breast cancer: a systematic review. Lancet 353(9159):1119–1126PubMedCrossRefGoogle Scholar
  38. 38.
    American Heart Association. What is high blood pressure? 2009. Available from http://www.heart.org/HEARTORG/Conditions/HighBloodPressure/AboutHighBloodPressure/Understanding-Blood-Pressure-Readings_UCM_301764_Article.jsp. Accessed 1 Aug 2009
  39. 39.
    Charlson ME et al (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40(5):373–383PubMedCrossRefGoogle Scholar
  40. 40.
    Deyo RA, Cherkin DC, Ciol MA (1992) Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 45(6):613–619PubMedCrossRefGoogle Scholar
  41. 41.
    Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J Royal Stat Soc Ser B (Methodol) 39(1):1–38Google Scholar
  42. 42.
    Pater JL, Loeb M, Siu TO (1979) A multivariate analysis of the contribution of “auxometry” to prognosis in breast cancer. J Chronic Dis 32(5):375–384PubMedCrossRefGoogle Scholar
  43. 43.
    Andre F et al (2004) Breast cancer with synchronous metastases: trends in survival during a 14-year period. J Clin Oncol 22(16):3302–3308PubMedCrossRefGoogle Scholar
  44. 44.
    Grasic-Kuhar C, Bracko M, Zakotnik B (2008) Risk factors for late relapse and death in patients with early breast cancer. Neoplasma 55(5):416–420PubMedGoogle Scholar
  45. 45.
    Falkson G et al (1991) Factors predicting for response, time to treatment failure, and survival in women with metastatic breast cancer treated with DAVTH: a prospective Eastern Cooperative Oncology Group study. J Clin Oncol 9(12):2153–2161PubMedGoogle Scholar
  46. 46.
    Caplan LS, May DS, Richardson LC (2000) Time to diagnosis and treatment of breast cancer: results from the National Breast and Cervical Cancer Early Detection Program, 1991–1995. Am J Public Health 90(1):130–134PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2011

Authors and Affiliations

  • Su Yon Jung
    • 1
    Email author
  • Susan M. Sereika
    • 3
    • 5
    • 6
  • Faina Linkov
    • 2
    • 3
  • Adam Brufsky
    • 2
    • 4
  • Joel L. Weissfeld
    • 2
    • 3
    • 4
  • Margaret Rosenzweig
    • 2
    • 6
  1. 1.Department of Epidemiology, Graduate School of Public Health, Epidemiology Data Coordinating CenterUniversity of PittsburghPittsburghUSA
  2. 2.Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghUSA
  3. 3.Department of Epidemiology, Graduate School of Public HealthUniversity of PittsburghPittsburghUSA
  4. 4.University of Pittsburgh Cancer InstitutePittsburghUSA
  5. 5.Department of Biostatistics, Graduate School of Public HealthUniversity of PittsburghPittsburghUSA
  6. 6.University of Pittsburgh School of NursingPittsburghUSA

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