Skip to main content

Advertisement

SpringerLink
Log in

Patterns and predictors of breast cancer chemotherapy use in Kaiser Permanente Northern California, 2004–2007

  • Epidemiology
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

Chemotherapy regimens for early stage breast cancer have been tested by randomized clinical trials, and specified by evidence-based practice guidelines. However, little is known about the translation of trial results and guidelines to clinical practice. We extracted individual-level data on chemotherapy administration from the electronic medical records of Kaiser Permanente Northern California (KPNC), a pre-paid integrated healthcare system serving 29 % of the local population. We linked data to the California Cancer Registry, incorporating socio-demographic and tumor factors, and performed multivariable logistic regression analyses on the receipt of specific chemotherapy regimens. We identified 6,004 women diagnosed with Stage I–III breast cancer at KPNC during 2004–2007; 2,669 (44.5 %) received at least one chemotherapy infusion at KPNC within 12 months of diagnosis. Factors associated with receiving chemotherapy included <50 years of age [odds ratio (OR) 2.27, 95 % confidence interval (CI) 1.81–2.86], tumor >2 cm (OR 2.14, 95 % CI 1.75–2.61), involved lymph nodes (OR 11.3, 95 % CI 9.29–13.6), hormone receptor-negative (OR 6.94, 95 % CI 4.89–9.86), Her2/neu-positive (OR 2.71, 95 % CI 2.10–3.51), or high grade (OR 3.53, 95 % CI 2.77–4.49) tumors; comorbidities associated inversely with chemotherapy use [heart disease for anthracyclines (OR 0.24, 95 % CI 0.14–0.41), neuropathy for taxanes (OR 0.45, 95 % CI 0.22–0.89)]. Relative to high-socioeconomic status (SES) non-Hispanic Whites, we observed less anthracycline and taxane use by SES non-Hispanic Whites (OR 0.63, 95 % CI 0.49-0.82) and American Indians (OR 0.23, 95 % CI 0.06–0.93), and more anthracycline use by high-SES Asians/Pacific Islanders (OR 1.72, 95 % CI 1.02–2.90). In this equal-access healthcare system, chemotherapy use followed practice guidelines, but varied by race and socio-demographic factors. These findings may inform efforts to optimize quality in breast cancer care.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. De Angelis R, Tavilla A, Verdecchia A et al (2009) Breast cancer survivors in the United States: geographic variability and time trends, 2005–2015. Cancer 115:1954–1966

    Article  PubMed  Google Scholar 

  2. Early Breast Cancer Trialists’ Collaborative Group (1988) Effects of adjuvant tamoxifen and of cytotoxic therapy on mortality in early breast cancer. An overview of 61 randomized trials among 28,896 women. N Engl J Med 319:1681–1692

    Article  Google Scholar 

  3. Early Breast Cancer Trialists’ Collaborative Group (1992) Systemic treatment of early breast cancer by hormonal, cytotoxic, or immune therapy. 133 randomised trials involving 31,000 recurrences and 24,000 deaths among 75,000 women. Lancet 339:71–85

    Google Scholar 

  4. Early Breast Cancer Trialists’ Collaborative Group (1998) Polychemotherapy for early breast cancer: an overview of the randomised trials. Lancet 352:930–942

    Article  Google Scholar 

  5. Berry DA, Cirrincione C, Henderson IC et al (2006) Estrogen-receptor status and outcomes of modern chemotherapy for patients with node-positive breast cancer. JAMA 295:1658–1667

    Article  PubMed  CAS  Google Scholar 

  6. Clarke M (2006) Meta-analyses of adjuvant therapies for women with early breast cancer: the Early Breast Cancer Trialists’ Collaborative Group overview. Ann Oncol 17(Suppl 10):x59–x62

    Article  PubMed  Google Scholar 

  7. Blayney DW, McNiff K, Hanauer D, Miela G, Markstrom D, Neuss M (2009) Implementation of the Quality Oncology Practice Initiative at a university comprehensive cancer center. J Clin Oncol 27:3802–3807

    Article  PubMed  Google Scholar 

  8. Carlson RW, Allred DC, Anderson BO et al (2011) Invasive breast cancer. J Natl Compr Canc Netw 9:136–222

    PubMed  CAS  Google Scholar 

  9. Du W, Mood D, Gadgeel S, Simon MS (2009) An educational video to increase clinical trials enrollment among breast cancer patients. Breast Cancer Res Treat 117:339–347

    Article  PubMed  Google Scholar 

  10. Kimmick GG, Peterson BL, Kornblith AB et al (2005) Improving accrual of older persons to cancer treatment trials: a randomized trial comparing an educational intervention with standard information: CALGB 360001. J Clin Oncol 23:2201–2207

    Article  PubMed  Google Scholar 

  11. Simon MS, Du W, Flaherty L et al (2004) Factors associated with breast cancer clinical trials participation and enrollment at a large academic medical center. J Clin Oncol 22:2046–2052

    Article  PubMed  Google Scholar 

  12. Winn RJ (1994) Obstacles to the accrual of patients to clinical trials in the community setting. Semin Oncol 21:112–117

    PubMed  CAS  Google Scholar 

  13. Citron ML, Berry DA, Cirrincione C et al (2003) Randomized trial of dose-dense versus conventionally scheduled and sequential versus concurrent combination chemotherapy as postoperative adjuvant treatment of node-positive primary breast cancer: first report of Intergroup Trial C9741/Cancer and Leukemia Group B Trial 9741. J Clin Oncol 21:1431–1439

    Article  PubMed  CAS  Google Scholar 

  14. Sparano JA, Wang M, Martino S et al (2008) Weekly paclitaxel in the adjuvant treatment of breast cancer. N Engl J Med 358:1663–1671

    Article  PubMed  CAS  Google Scholar 

  15. Bickell NA, McAlearney AS, Wellner J, Fei K, Franco R (2011) Understanding the challenges of adjuvant treatment measurement and reporting in breast cancer: cancer treatment measuring and reporting. Med Care (electronic publication) December 30

  16. Lodrigues W, Dumas J, Rao M, Lilley L, Rao R (2011) Compliance with the commission on cancer quality of breast cancer care measures: self-evaluation advised. Breast J 17:167–171

    Article  PubMed  Google Scholar 

  17. Wagner EH, Greene SM, Hart G et al (2005) Building a research consortium of large health systems: the Cancer Research Network. J Natl Cancer Inst Monogr 2005:3–11

    Article  Google Scholar 

  18. Hershman DL, Kushi LH, Shao T et al (2010) Early discontinuation and nonadherence to adjuvant hormonal therapy in a cohort of 8,769 early-stage breast cancer patients. J Clin Oncol 28:4120–4128

    Article  PubMed  Google Scholar 

  19. Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383

    Article  PubMed  CAS  Google Scholar 

  20. Deyo RA, Cherkin DC, Ciol MA (1992) Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 45:613–619

    Article  PubMed  CAS  Google Scholar 

  21. Quan H, Li B, Couris CM et al (2011) Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol 173:676–682

    Article  PubMed  Google Scholar 

  22. Shavers VL, Brown M, Klabunde CN et al (2004) Race/ethnicity and the intensity of medical monitoring under ‘watchful waiting’ for prostate cancer. Med Care 42:239–250

    Article  PubMed  Google Scholar 

  23. Cancer reporting in California: abstracting and coding procedures for hospitals, tenth edition. California cancer reporting system standards, volumes I-IV (2009-2011). California Department of Public Health, Cancer Surveillance and Research Branch, Sacramento, CA. http://www.ccrcal.org/Cancer_Reporting/Registrar_Resources/Reporting_Cancer_Cal.shtml. Accessed May 30, 2012

  24. California Cancer Registry. http://www.ccrcal.org. Accessed May 30, 2012

  25. American Joint Committee on Cancer Staging. http://www.cancerstaging.org. Accessed May 30, 2012

  26. North American Association of Central Cancer Registries. Great Circle Distance Calculator. http://www.naaccr.org/Research/DataAnalysisTools.aspx. Accessed May 30, 2012

  27. Yost K, Perkins C, Cohen R, Morris C, Wright W (2001) Socioeconomic status and breast cancer incidence in California for different race/ethnic groups. Cancer Causes Control 12:703–711

    Article  PubMed  CAS  Google Scholar 

  28. Henderson IC, Berry DA, Demetri GD et al (2003) Improved outcomes from adding sequential Paclitaxel but not from escalating Doxorubicin dose in an adjuvant chemotherapy regimen for patients with node-positive primary breast cancer. J Clin Oncol 21:976–983

    Article  PubMed  CAS  Google Scholar 

  29. Bonadonna G, Moliterni A, Zambetti M et al (2005) 30 years’ follow up of randomised studies of adjuvant CMF in operable breast cancer: cohort study. BMJ 330:217

    Article  PubMed  Google Scholar 

  30. Bonadonna G, Rossi A, Valagussa P, Banfi A, Veronesi U (1977) The CMF program for operable breast cancer with positive axillary nodes. Updated analysis on the disease-free interval, site of relapse and drug tolerance. Cancer 39:2904–2915

    Article  PubMed  CAS  Google Scholar 

  31. Piccart-Gebhart MJ, Procter M, Leyland-Jones B et al (2005) Trastuzumab after adjuvant chemotherapy in HER2-positive breast cancer. N Engl J Med 353:1659–1672

    Article  PubMed  CAS  Google Scholar 

  32. Romond EH, Perez EA, Bryant J et al (2005) Trastuzumab plus adjuvant chemotherapy for operable HER2-positive breast cancer. N Engl J Med 353:1673–1684

    Article  PubMed  CAS  Google Scholar 

  33. Telli ML, Chang ET, Kurian AW et al (2011) Asian ethnicity and breast cancer subtypes: a study from the California Cancer Registry. Breast Cancer Res Treat 127:471–478

    Article  PubMed  Google Scholar 

  34. Ma H, Wang Y, Sullivan-Halley J et al (2009) Breast cancer receptor status: do results from a centralized pathology laboratory agree with SEER registry reports? Cancer Epidemiol Biomarkers Prev 18:2214–2220

    Article  PubMed  CAS  Google Scholar 

  35. Caan B, Sternfeld B, Gunderson E, Coates A, Quesenberry C, Slattery ML (2005) Life After Cancer Epidemiology (LACE) Study: a cohort of early stage breast cancer survivors (United States). Cancer Causes Control 16:545–556

    Article  PubMed  Google Scholar 

  36. Kwan ML, Ambrosone CB, Lee MM et al (2008) The Pathways Study: a prospective study of breast cancer survivorship within Kaiser Permanente Northern California. Cancer Causes Control 19:1065–1076

    Article  PubMed  Google Scholar 

  37. Gnant M, Harbeck N, Thomssen C (2011) St. Gallen 2011: summary of the Consensus Discussion. Breast Care (Basel) 6:136–141

    Article  Google Scholar 

  38. Early Breast Cancer Trialists’ Collaborative Group (2005) Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 365:1687–1717

    Article  Google Scholar 

  39. Carlson RW, Anderson BO, Burstein HJ et al (2007) Invasive breast cancer. J Natl Compr Canc Netw 5:246–312

    PubMed  CAS  Google Scholar 

  40. Olivotto IA, Bajdik CD, Ravdin PM et al (2005) Population-based validation of the prognostic model ADJUVANT! For early breast cancer. J Clin Oncol 23:2716–2725

    Article  PubMed  Google Scholar 

  41. Ravdin PM, Siminoff LA, Davis GJ et al (2001) Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 19:980–991

    PubMed  CAS  Google Scholar 

  42. Krieger N (1992) Overcoming the absence of socioeconomic data in medical records: validation and application of a census-based methodology. Am J Public Health 82:703–710

    Article  PubMed  CAS  Google Scholar 

  43. Gordon NP (2012). Similarity of the Adult Kaiser Permanente Membership in Northern California to the Insured and General Population in Northern California: Statistics from the 2009 California Health Interview Survey. Internal Division of Research Report, Oakland, CA, Kaiser Permanente Division of Research. http://www.dor.kaiser.org/external/chis_non_kp_2009. Accessed May 30, 2012

  44. Carey LA, Perou CM, Livasy CA et al (2006) Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 295:2492–2502

    Article  PubMed  CAS  Google Scholar 

  45. Curtis E, Quale C, Haggstrom D, Smith-Bindman R (2008) Racial and ethnic differences in breast cancer survival: how much is explained by screening, tumor severity, biology, treatment, comorbidities, and demographics? Cancer 112:171–180

    Article  PubMed  Google Scholar 

  46. Li CI (2005) Racial and ethnic disparities in breast cancer stage, treatment, and survival in the United States. Ethn Dis 15(2 Suppl 2):S5–S9

    PubMed  Google Scholar 

  47. West DW, Satariano WA, Ragland DR, Hiatt RA (1996) Comorbidity and breast cancer survival: a comparison between black and white women. Ann Epidemiol 6:413–419

    Article  PubMed  CAS  Google Scholar 

  48. Giordano SH, Lin YL, Kuo YF, Hortobagyi GN, Goodwin JS (2012) Decline in the use of anthracyclines for breast cancer. J Clin Oncol 30:2232–2239

    Article  PubMed  CAS  Google Scholar 

  49. Griggs JJ, Culakova E, Sorbero ME et al (2007) Social and racial differences in selection of breast cancer adjuvant chemotherapy regimens. J Clin Oncol 25:2522–2527

    Article  PubMed  Google Scholar 

  50. Griggs JJ, Culakova E, Sorbero ME et al (2007) Effect of patient socioeconomic status and body mass index on the quality of breast cancer adjuvant chemotherapy. J Clin Oncol 25:277–284

    Article  PubMed  Google Scholar 

  51. Lipscomb J, Gillespie TW, Goodman M et al (2012) Black–white differences in receipt and completion of adjuvant chemotherapy among breast cancer patients in a rural region of the US. Breast Cancer Res Treat 133:285–296

    Article  PubMed  CAS  Google Scholar 

  52. Sparano JA, Wang M, Zhao F et al (2012) Race and hormone receptor-positive breast cancer outcomes in a randomized chemotherapy trial. J Natl Cancer Inst 104:406–414

    Article  PubMed  CAS  Google Scholar 

  53. Wu XC, Lund MJ, Kimmick GG et al (2012) Influence of race, insurance, socioeconomic status, and hospital type on receipt of guideline-concordant adjuvant systemic therapy for locoregional breast cancers. J Clin Oncol 30:142–150

    Article  PubMed  Google Scholar 

  54. Delate T, Bowles EJ, Pardee R et al (2012) Validity of eight integrated healthcare delivery organizations’ administrative clinical data to capture breast cancer chemotherapy exposure. Cancer Epidemiol Biomarkers Prev 21:673–680

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

This research was supported by the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under contract HHSN261201000140C and a SEER Rapid Response Surveillance Study under contract N01-PC-35136 awarded to the Cancer Prevention Institute of California, and under a subcontract to Kaiser Permanente Northern California Division of Research. This research was also supported by grants from the National Cancer Institute (R01 CA105274 to L.H.K. and R01 CA098838 to L.A.H.) and from the American Cancer Society (RSGT-08-009-01-CPHPS to D.L.H.). The collection of cancer incidence data used in this study was supported by the California Department of Health Services as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885; the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program under contract HHSN261201000140C awarded to the Cancer Prevention Institute of California, contract HHSN261201000035C awarded to the University of Southern California, and contract HHSN261201000034C awarded to the Public Health Institute; and the Centers for Disease Control and Prevention’s National Program of Cancer Registries, under agreement #1U58 DP000807-01 awarded to the Public Health Institute. The ideas and opinions expressed herein are those of the authors, and endorsement by the State of California, the California Department of Health Services, the National Cancer Institute, or the Centers for Disease Control and Prevention or their contractors and subcontractors is not intended nor should be inferred. We thank Dr. Lou Fehrenbacher for his helpful comments on the manuscript.

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical Standards

All reported work in this study complies with the current laws of the United States.

Author information

Authors and Affiliations

  1. Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Allison W. Kurian

  2. Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA, USA

    Allison W. Kurian, Theresa H. M. Keegan & Scarlett L. Gomez

  3. Cancer Prevention Institute of California, 2201 Walnut Avenue, Suite 300, Fremont, CA, 94538, USA

    Daphne Y. Lichtensztajn, Theresa H. M. Keegan, Rita W. Leung, Sarah J. Shema & Scarlett L. Gomez

  4. Columbia University Medical Center, New York, NY, USA

    Dawn L. Hershman

  5. Division of Research, Kaiser Permanente, Oakland, CA, USA

    Lawrence H. Kushi, Laurel A. Habel & Bette J. Caan

  6. Kaiser Permanente, Vallejo, CA, USA

    Tatjana Kolevska

Authors
  1. Allison W. Kurian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daphne Y. Lichtensztajn
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Theresa H. M. Keegan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rita W. Leung
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sarah J. Shema
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Dawn L. Hershman
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Lawrence H. Kushi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Laurel A. Habel
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Tatjana Kolevska
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Bette J. Caan
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Scarlett L. Gomez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Scarlett L. Gomez.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kurian, A.W., Lichtensztajn, D.Y., Keegan, T.H.M. et al. Patterns and predictors of breast cancer chemotherapy use in Kaiser Permanente Northern California, 2004–2007. Breast Cancer Res Treat 137, 247–260 (2013). https://doi.org/10.1007/s10549-012-2329-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10549-012-2329-5

Keywords

Search

Navigation