Skip to main content

Advertisement

Log in

Impact of chemotherapy relative dose intensity on cause-specific and overall survival for stage I–III breast cancer: ER+/PR+, HER2- vs. triple-negative

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

Abstract

Purpose

To investigate the impact of chemotherapy relative dose intensity (RDI) on cause-specific and overall survival for stage I–III breast cancer: estrogen receptor or progesterone receptor positive, human epidermal-growth factor receptor negative (ER+/PR+ and HER2-) vs. triple-negative (TNBC) and to identify the optimal RDI cut-off points in these two patient populations.

Methods

Data were collected by the Louisiana Tumor Registry for two CDC-funded projects. Women diagnosed with stage I–III ER+/PR+, HER2- breast cancer, or TNBC in 2011 with complete information on RDI were included. Five RDI cut-off points (95, 90, 85, 80, and 75%) were evaluated on cause-specific and overall survival, adjusting for multiple demographic variables, tumor characteristics, comorbidity, use of granulocyte-growth factor/cytokines, chemotherapy delay, chemotherapy regimens, and use of hormone therapy. Cox proportional hazards models and Kaplan–Meier survival curves were estimated and adjusted by stabilized inverse probability treatment weighting (IPTW) of propensity score.

Results

Of 494 ER+/PR+, HER2- patients and 180 TNBC patients, RDI < 85% accounted for 30.4 and 27.8%, respectively. Among ER+/PR+, HER2- patients, 85% was the only cut-off point at which the low RDI was significantly associated with worse overall survival (HR = 1.93; 95% CI 1.09–3.40). Among TNBC patients, 75% was the cut-off point at which the high RDI was associated with better cause-specific (HR = 2.64; 95% CI 1.09, 6.38) and overall survival (HR = 2.39; 95% CI 1.04–5.51).

Conclusions

Higher RDI of chemotherapy is associated with better survival for ER+/PR+, HER2- patients and TNBC patients. To optimize survival benefits, RDI should be maintained ≥ 85% in ER+/PR+, HER2- patients, and ≥ 75% in TNBC patients.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

RDI:

Relative dose intensity

RCT:

Randomized controlled trial

ESBC:

Early stage breast cancer

CMF:

Cyclophosphamide, methotrexate, and fluorouracil

ER:

Estrogen receptor

PR:

Progesterone receptor

HER2:

Human epidermal-growth factor receptor 2

TNBC:

Triple-negative breast cancer

pCR:

Pathologic complete response

LTR:

Louisiana Tumor Registry

CER:

Enhancing Cancer Registry Data for Comparative Effectiveness Research

PCOR:

Patient Centered Outcomes Research

CDC:

Centers for Disease Control and Prevention

AJCC:

American Joint Committee on Cancer

BSA:

body surface area

NCCN:

National Comprehensive Cancer Network

AC-T:

Doxorubicin/cyclophosphamide followed by paclitaxel or docetaxel

TC:

Docetaxel/cyclophosphamide

TAC:

Docetaxel/doxorubicin/cyclophosphamide

AC:

Doxorubicin/cyclophosphamide

SEER:

Surveillance, Epidemiology, and End Results program

CCI:

Charlson comorbidity index

G-CSF:

Granulocyte-growth factors/cytokines

IPTW:

Inverse probability of treatment weighting

HR:

Hazard ratio

CI:

Confidence interval

References

  1. 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(9472):1687–1717. https://doi.org/10.1016/s0140-6736(05)66544-0

    Article  Google Scholar 

  2. Fisher B, Dignam J, Wolmark N, DeCillis A, Emir B, Wickerham DL, Bryant J, Dimitrov NV, Abramson N, Atkins JN, Shibata H, Deschenes L, Margolese RG (1997) Tamoxifen and chemotherapy for lymph node-negative, estrogen receptor-positive breast cancer. J Natl Cancer Inst 89(22):1673–1682

    Article  CAS  PubMed  Google Scholar 

  3. Mansour EG, Gray R, Shatila AH, Tormey DC, Cooper MR, Osborne CK, Falkson G (1998) Survival advantage of adjuvant chemotherapy in high-risk node-negative breast cancer: ten-year analysis–an intergroup study. J Clin Oncol 16(11):3486–3492

    Article  CAS  PubMed  Google Scholar 

  4. Fisher B, Jeong JH, Dignam J, Anderson S, Mamounas E, Wickerham DL, Wolmark N (2001) Findings from recent National Surgical Adjuvant Breast and Bowel Project adjuvant studies in stage I breast cancer. J Natl Cancer Inst Monogr 30:62–66

    Article  Google Scholar 

  5. Bonadonna G, Valagussa P, Moliterni A, Zambetti M, Brambilla C (1995) Adjuvant cyclophosphamide, methotrexate, and fluorouracil in node-positive breast cancer: the results of 20 years of follow-up. NEngl J Med 332(14):901–906. https://doi.org/10.1056/nejm199504063321401

    Article  CAS  Google Scholar 

  6. Budman DR, Berry DA, Cirrincione CT, Henderson IC, Wood WC, Weiss RB, Ferree CR, Muss HB, Green MR, Norton L, Frei E 3rd (1998) Dose and dose intensity as determinants of outcome in the adjuvant treatment of breast cancer. The Cancer and Leukemia Group B. J Natl Cancer Inst 90(16):1205–1211

    Article  CAS  PubMed  Google Scholar 

  7. Chirivella I, Bermejo B, Insa A, Perez-Fidalgo A, Magro A, Rosello S, Garcia-Garre E, Martin P, Bosch A, Lluch A (2009) Optimal delivery of anthracycline-based chemotherapy in the adjuvant setting improves outcome of breast cancer patients. Breast Cancer Res Treat 114(3):479–484. https://doi.org/10.1007/s10549-008-0018-1

    Article  CAS  PubMed  Google Scholar 

  8. Lyman GH (2009) Impact of chemotherapy dose intensity on cancer patient outcomes. J Natl Compr Cancer Netw 7(1):99–108

    Article  Google Scholar 

  9. Havrilesky LJ, Reiner M, Morrow PK, Watson H, Crawford J (2015) A review of relative dose intensity and survival in patients with metastatic solid tumors. Critical Rev Oncol/Hematol 93(3):203–210. https://doi.org/10.1016/j.critrevonc.2014.10.006

    Article  Google Scholar 

  10. Harris L, Fritsche H, Mennel R, Norton L, Ravdin P, Taube S, Somerfield MR, Hayes DF, Bast RC Jr (2007) American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. Journal Clin Oncol 25(33):5287–5312. https://doi.org/10.1200/jco.2007.14.2364

    Article  CAS  Google Scholar 

  11. National Comprehensive Cancer Network. NCCN Guidelines for Treatment of Cancer by Site. http://www.nccn.org/professionals/physician_gls/f_guidelines.asp#site. Accessed Aug. 2017

  12. McShane LM, Hayes DF (2012) Publication of tumor marker research results: the necessity for complete and transparent reporting. J Clin Oncol 30(34):4223–4232. https://doi.org/10.1200/jco.2012.42.6858

    Article  PubMed  PubMed Central  Google Scholar 

  13. Lang JE, Wecsler JS, Press MF, Tripathy D (2015) Molecular markers for breast cancer diagnosis, prognosis and targeted therapy. J Surg Oncol 111(1):81–90. https://doi.org/10.1002/jso.23732

    Article  PubMed  Google Scholar 

  14. Onitilo AA, Engel JM, Greenlee RT, Mukesh BN (2009) Breast cancer subtypes based on ER/PR and Her2 expression: comparison of clinicopathologic features and survival. Clin Med Res 7(1–2):4–13. https://doi.org/10.3121/cmr.2009.825

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Lee HJ, Song IH, Seo AN, Lim B, Kim JY, Lee JJ, Park IA, Shin J, Yu JH, Ahn JH, Gong G (2015) Correlations between molecular subtypes and pathologic response patterns of breast cancers after neoadjuvant chemotherapy. Ann Surg Oncol 22(2):392–400. https://doi.org/10.1245/s10434-014-4054-2

    Article  PubMed  Google Scholar 

  16. Kuerer HM, Newman LA, Smith TL, Ames FC, Hunt KK, Dhingra K, Theriault RL, Singh G, Binkley SM, Sneige N, Buchholz TA, Ross MI, McNeese MD, Buzdar AU, Hortobagyi GN, Singletary SE (1999) Clinical course of breast cancer patients with complete pathologic primary tumor and axillary lymph node response to doxorubicin-based neoadjuvant chemotherapy. J Clin Oncol 17(2):460–469

    Article  CAS  PubMed  Google Scholar 

  17. Cortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, Bonnefoi H, Cameron D, Gianni L, Valagussa P, Swain SM, Prowell T, Loibl S, Wickerham DL, Bogaerts J, Baselga J, Perou C, Blumenthal G, Blohmer J, Mamounas EP, Bergh J, Semiglazov V, Justice R, Eidtmann H, Paik S, Piccart M, Sridhara R, Fasching PA, Slaets L, Tang S, Gerber B, Geyer CE, Pazdur R, Ditsch N, Rastogi P, Eiermann W, Minckwitz G (2014) Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet 384(9938):164–172. https://doi.org/10.1016/s0140-6736(13)62422-8

    Article  PubMed  Google Scholar 

  18. North American Association of Central Cancer Registries: Data standards and data dictionary. http://datadictionary.naaccr.org/. Accessed Aug. 2017

  19. Surveillance, epidemiology, and end results program: derived HER2 Recode (2010+). https://seer.cancer.gov/seerstat/databases/ssf/her2-derived.html. Accessed Aug. 2017

  20. Chen VW, Eheman CR, Johnson CJ, Hernandez MN, Rousseau D, Styles TS, West DW, Hsieh M, Hakenewerth AM, Celaya MO, Rycroft RK, Wike JM, Pearson M, Brockhouse J, Mulvihill LG, Zhang KB (2014) Enhancing cancer registry data for comparative effectiveness research (CER) project: overview and methodology. J Regist Manag 41(3):103–112

    Google Scholar 

  21. Hryniuk W, Levine MN (1986) Analysis of dose intensity for adjuvant chemotherapy trials in stage II breast cancer. J Clin Oncol 4(8):1162–1170

    Article  CAS  PubMed  Google Scholar 

  22. Longo DL, Duffey PL, DeVita VT Jr, Wesley MN, Hubbard SM, Young RC (1991) The calculation of actual or received dose intensity: a comparison of published methods. J Clin Oncol 9(11):2042–2051

    Article  CAS  PubMed  Google Scholar 

  23. Shayne M, Crawford J, Dale DC, Culakova E, Lyman GH (2006) Predictors of reduced dose intensity in patients with early-stage breast cancer receiving adjuvant chemotherapy. Breast Cancer Res Treat 100(3):255–262. https://doi.org/10.1007/s10549-006-9254-4

    Article  PubMed  Google Scholar 

  24. Lyman GH, Dale DC, Crawford J (2003) Incidence and predictors of low dose-intensity in adjuvant breast cancer chemotherapy: a nationwide study of community practices. J Clin Oncol 21(24):4524–4531. https://doi.org/10.1200/jco.2003.05.002

    Article  PubMed  Google Scholar 

  25. Weycker D, Barron R, Edelsberg J, Kartashov A, Lyman GH (2012) Incidence of reduced chemotherapy relative dose intensity among women with early stage breast cancer in US clinical practice. Breast Cancer Res Treat 133(1):301–310. https://doi.org/10.1007/s10549-011-1949-5

    Article  CAS  PubMed  Google Scholar 

  26. Lyman GH, Dale DC, Tomita D, Whittaker S, Crawford J (2013) A retrospective evaluation of chemotherapy dose intensity and supportive care for early-stage breast cancer in a curative setting. Breast Cancer Res Treat 139(3):863–872. https://doi.org/10.1007/s10549-013-2582-2

    Article  CAS  PubMed  Google Scholar 

  27. SEER Cause-specific Death Classification. http://seer.cancer.gov/causespecific/index.html. Accessed Aug. 2017

  28. Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, Saunders LD, Beck CA, Feasby TE, Ghali WA (2005) Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 43(11):1130–1139

    Article  PubMed  Google Scholar 

  29. Austin PC, Stuart EA (2015) Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Stat Med 34(28):3661–3679. https://doi.org/10.1002/sim.6607

    Article  PubMed  PubMed Central  Google Scholar 

  30. Austin PC, Grootendorst P, Anderson GM (2007) A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study. Stat Med 26(4):734–753. https://doi.org/10.1002/sim.2580

    Article  PubMed  Google Scholar 

  31. Xu S, Ross C, Raebel MA, Shetterly S, Blanchette C, Smith D (2010) Use of stabilized inverse propensity scores as weights to directly estimate relative risk and its confidence intervals. Value Health 13(2):273–277. https://doi.org/10.1111/j.1524-4733.2009.00671.x

    Article  PubMed  Google Scholar 

  32. Austin PC, Stuart EA (2015) The performance of inverse probability of treatment weighting and full matching on the propensity score in the presence of model misspecification when estimating the effect of treatment on survival outcomes. Stat Methods Med Res. https://doi.org/10.1177/0962280215584401

    Google Scholar 

  33. Lee BK, Lessler J, Stuart EA (2011) Weight trimming and propensity score weighting. PLoS ONE 6(3):e18174. https://doi.org/10.1371/journal.pone.0018174

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Therneau TM, Grambsch PM (2000) Testing proportional hazards. In: Dietz K et al (eds) Modeling survival Data: Extending the cox model. Statistics for biology and Health. Springer, New York

    Chapter  Google Scholar 

  35. Loibl S, Skacel T, Nekljudova V, Luck HJ, Schwenkglenks M, Brodowicz T, Zielinski C, von Minckwitz G (2011) Evaluating the impact of Relative Total Dose Intensity (RTDI) on patients’ short and long-term outcome in taxane- and anthracycline-based chemotherapy of metastatic breast cancer- a pooled analysis. BMC Cancer 11:131. https://doi.org/10.1186/1471-2407-11-131

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Yuan JQ, Wang SM, Tang LL, Mao J, Wu YH, Hai J, Luo SY, Ou HY, Guo L, Liao LQ, Huang J, Li Y, Xiao Z, Zhang KJ, Luo N, Chen FY (2015) Relative dose intensity and therapy efficacy in different breast cancer molecular subtypes: a retrospective study of early stage breast cancer patients treated with neoadjuvant chemotherapy. Breast Cancer Res Treat 151(2):405–413. https://doi.org/10.1007/s10549-015-3418-z

    Article  CAS  PubMed  Google Scholar 

  37. Moon HG, Im SA, Han W, Oh DY, Han SW, Keam B, Park IA, Chang JM, Moon WK, Cho N, Noh DY (2012) Estrogen receptor status confers a distinct pattern of response to neoadjuvant chemotherapy: implications for optimal durations of therapy: distinct patterns of response according to ER expression. Breast Cancer Res Treat 134(3):1133–1140. https://doi.org/10.1007/s10549-012-2145-y

    Article  CAS  PubMed  Google Scholar 

  38. Colleoni M, Li S, Gelber RD, Price KN, Coates AS, Castiglione-Gertsch M, Goldhirsch A (2005) Relation between chemotherapy dose, oestrogen receptor expression, and body-mass index. Lancet 366(9491):1108–1110. https://doi.org/10.1016/s0140-6736(05)67110-3

    Article  CAS  PubMed  Google Scholar 

  39. Paik S, Tang G, Shak S, Kim C, Baker J, Kim W, Cronin M, Baehner FL, Watson D, Bryant J, Costantino JP, Geyer CE Jr, Wickerham DL, Wolmark N (2006) Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol 24(23):3726–3734. https://doi.org/10.1200/jco.2005.04.7985

    Article  CAS  PubMed  Google Scholar 

  40. Lyman GH (2006) Chemotherapy dose intensity and quality cancer care. Oncology 20(14 Suppl 9):16–25

    Google Scholar 

  41. Denduluri N, Patt DA, Wang Y, Bhor M, Li X, Favret AM, Morrow PK, Barron RL, Asmar L, Saravanan S, Li Y, Garcia J, Lyman GH (2015) Dose delays, dose reductions, and relative dose intensity in patients with cancer who received adjuvant or neoadjuvant chemotherapy in community oncology practices. J Natl Compr Cancer Netw 13(11):1383–1393

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We acknowledge the Centers for Disease Control and Prevention (CDC) for funding Enhancing Cancer Registry Data for Comparative Effectiveness Research (CER) Project (Grant Number: 1eEDSK0106) and Patient Centered Outcomes Research (PCOR) project (Grant Number: 5NU58DP003915), and the Louisiana Tumor Registry for data and administrative support. We acknowledge Dr. Gary H. Lyman and Dr. Marek S. Poniewierski for clarifying variables used in the calculation of chemotherapy relative dose intensity.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tekeda Ferguson.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

For this type of study, formal consent is not required.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 18 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, L., Yu, Q., Wu, XC. et al. Impact of chemotherapy relative dose intensity on cause-specific and overall survival for stage I–III breast cancer: ER+/PR+, HER2- vs. triple-negative. Breast Cancer Res Treat 169, 175–187 (2018). https://doi.org/10.1007/s10549-017-4646-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10549-017-4646-1

Keywords

Navigation