Skip to main content
Log in

Time distribution of the recurrence risk for breast cancer patients undergoing mastectomy: Further support about the concept of tumor dormancy

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

Abstract

Purpose

To gather information on metastatic growth from the time-distribution of first treatment failure in breast cancer patients undergoing mastectomy alone.Methods: The risk of recurrence at a given time after surgery was studied utilizing the cause-specific hazard function. Recurrence was categorized as first treatment failure at any site, local-regional recurrence, distant metastases, and contralateral tumor. The risk distribution was assessed relative to tumor size, axillary lymph node involvement, and menopausal status.Results: A total of 1173 patients treated between 1964 and 1980 with mastectomy alone and no adjuvant therapy were studied. The hazard function for first failure presented an early peak at about 18 months after surgery, a second peak at about 60 months and then a tapered plateau-like tail extending up to 15 years. A similar risk pattern was detectable for both local recurrence and distant metastases, while the curve of contralateral breast tumors showed a near flat plateau. The risk of early local-regional and distant recurrences was much lower for tumors less than 2 cm in diameter than for larger tumors; the risk of late recurrence was similar for small and large primaries. Node-positive patients showed peaks four to five times higher than node-negative patients. Subdividing node-positive patients into 1–3 and > 3 node-positive subsets did not substantially change the general picture of tumor recurrence. The hazard functions for premenopausal and postmenopausal patients were virtually superimposable.Conclusions: The multipeak hazard curve suggests that the process resulting in overt clinical metastases may have discrete features. Primary tumor size could affect in different ways early and late metastases, while axillary node status should be related to the risk level, not to the risk pattern, and menopausal status does not seem to significantly affect the hazard distribution. Moreover, contralateral breast tumors, occurring at constant risk throughout the time, should be considered as second primary cancers. These findings could be reasonably explained by a tumor dormancy hypothesis, which assumes that micrometastases may be in different biological steady states, most of which do not imply tumor growth. Tumor or microenvironment changes could induce metastatic growth after given mean transition times from surgery and originate a discrete pattern of the hazard function.

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.

References

  1. Simes RJ, Zelen M: Exploratory data analysis and the use of the hazard function for interpreting survival data: an investigator's primer. J Clin Oncol 3: 1418–1431, 1985

    PubMed  Google Scholar 

  2. Norton L: Implications of kinetic heterogeneity in clinical oncology. Sem Oncol 12: 231–249, 1985

    Google Scholar 

  3. Demicheli R, Valagussa P, Foroni R, Bonadonna G: Mean relapse rate per year (MRR/Y) suggests different biological conditions of breast cancer micrometastases at the time of primary local-regional treatment. Proc Am Soc Clin Oncol 12: 119, 1993

    Google Scholar 

  4. Fidler I: The biology of renal cancer metastasis. Semin Urol 1: 3–11, 1992

    Google Scholar 

  5. Marubini E, Valsecchi MG: Analyzing survival data from clinical trials and observational studies. Wiley & Sons Ltd, Chichester (UK) 1995, pp 331–364

    Google Scholar 

  6. Prentice RL, Kalbfleisch JD, Peterson AV Jr: The analysis of failure times in the presence of competing risks. Biometrics 34: 541–554, 1978

    PubMed  Google Scholar 

  7. Ramlau-Hansen H: Smoothing counting process intensities by means of Kernel functions. Ann Statistics 11: 453–466, 1983

    Google Scholar 

  8. Efron B: Logistic regression, survival analysis, and Kaplan-Meier curve. J Am Stat Ass 83: 414–425, 1988

    Google Scholar 

  9. Veronesi U, Marubini E, DelVecchio M, Manzari A, Andreola S, Greco M, Luini A, Merson M, Saccozzi R, Rilke F, Salvadori B: Local recurrences and distant metastases after conservative breast cancer treatments: partly independent events. J Natl Cancer Inst 87: 19–27, 1995

    PubMed  Google Scholar 

  10. Kennedy MJ, Abeloff MD: Management of locally recurrent breast cancer. Cancer 71: 2395–2409, 1992

    Google Scholar 

  11. Valagussa P, Bonadonna G, Veronesi U: Patterns of relapse and survival following radical mastectomy. Cancer 41: 1170–1178, 1978

    PubMed  Google Scholar 

  12. Kamby C: The pattern of metastases in human breast cancer: methodological aspects and influence of prognostic factors. Cancer Treat Rev 17: 37–61, 1990

    Google Scholar 

  13. Gilchrist KW, Gray R, Fowble B, Tormey DC, Taylor IV SG: Tumor necrosis is a prognostic predictor for early recurrence and death in lymphnode-positive breast cancer: a 10-year follow-up study of 728 Eastern Cooperative Oncology Group patients. J Clin Oncol 11: 1929–1935, 1993

    PubMed  Google Scholar 

  14. Yoshimoto M, Sakamoto G, Ohashi Y: Time dependency of the influence of prognostic factors on relapse in breast cancer. Cancer 72: 2993–3001, 1993

    PubMed  Google Scholar 

  15. Fisher B, Bauer M, Wickerhan DL, Redmond CK, Fisher ER: Relation of number of positive axillary nodes to the prognosis of patients with primary breast cancer. An NSABP update. Cancer 52: 1551–1557, 1983

    Google Scholar 

  16. Gehan EA: Estimating survival functions from the life table. A J Chron Dis 21: 629–644, 1969

    Google Scholar 

  17. Fisher E, Fisher B, Sass R, Wickerham L and Collaborating NSABP Investigators: Pathologic findings from the National Surgical Adjuvant Breast Project (protocol # 4). XI. Bilateral breast cancer. Cancer 54: 3002–3011, 1984

    Google Scholar 

  18. Dawson PJ, Maloney T, Gimotty P, Juneau P, Ownby H, Wolman SR: Bilateral breast cancer: one disease or two? Breast Cancer Res Treat 19: 233–244, 1991

    PubMed  Google Scholar 

  19. Chaudary MA, Millis RR, Hoskins EO, Halder M, Bulbrook RD, Cuzick J, Hayward JL: Bilateral primary breast cancer: a prospective study of disease incidence. Br J Surg 71: 711–714, 1984

    PubMed  Google Scholar 

  20. Healey EA, Cook EF, Orav EJ, Schnitt SJ, Connolly JL, Harris JR: Contralateral breast cancer: clinical characteristics and impact on prognosis. J Clin Oncol 11: 1545–1552, 1993

    PubMed  Google Scholar 

  21. Rosen PP, Groshen S, Kinne DW, Norton L: Factors influencing prognosis in node-negative breast carcinoma: analysis of 767 T1N0M0/T2N0M0 patients with long-term follow-up. J Clin Oncol 11: 2090–2100, 1993

    PubMed  Google Scholar 

  22. Spratt JS, Spratt TL: Rates of growth of pulmonary metastases and host survival. Ann Surg 159: 161–171, 1964

    PubMed  Google Scholar 

  23. Uhr JW, Tucker T, May RD, Siu H, Vitetta ES: Cancer dormancy: studies of the murine BCL1 lymphoma. Cancer Res 51: 5045s-5053s, 1991

    PubMed  Google Scholar 

  24. Wijsman JH, Cornelisse CJ, Keijzer R, van de Velde CJH, van Dierendonck JH: A prolactin dependent, metastasising rat mammary carcinoma as a model for endocrine-related tumor dormancy. Br J Cancer 64: 463–468, 1991

    PubMed  Google Scholar 

  25. Gartner MF, Fearns C, Wilson EL, Campbell JAH, Dowdle EB: Unusual growth characteristics of human melanoma xenografts in the nude mouse: a model for desmoplasia, dormancy and progression. Br J Cancer 65: 487–490, 1992

    PubMed  Google Scholar 

  26. Shafie SM, Grantham FH: Role of hormones in the growth and regression of human breast cancer cells (MCF-7) transplanted into athymic nude mice. J Natl Cancer Inst 67: 51–56, 1981

    PubMed  Google Scholar 

  27. Holmgren L, O'Reilly MS, Folkman J: Dormancy of micrometastases: balanced proliferation and apoptosis in the presence of angiogenesis suppression. Nature Med 1: 149–153, 1995

    PubMed  Google Scholar 

  28. Pantel K, Schlimok G, Braun S: Differential expression of proliferation-associated molecules in individual micrometastatic carcinoma cells. J Natl Cancer Inst 85: 1419–1424, 1993

    PubMed  Google Scholar 

  29. Demicheli R, Terenziani M, Valagussa P, Moliterni A, Zambetti M, Bonadonna G: Local recurrences following mastectomy: support for the concept of tumor dormancy. J Natl Cancer Inst 86: 45–48, 1994

    PubMed  Google Scholar 

  30. Killion JJ, Fidler IJ: The biology of tumor metastasis. Semin Oncol 16: 106–115, 1989

    PubMed  Google Scholar 

  31. Sobel ME: Metastasis suppressor genes. J Natl Cancer Inst 82: 267–276, 1990

    PubMed  Google Scholar 

  32. Nicolson GL: Molecular mechanisms of cancer metastasis: tumor and host properties and the role of oncogenes and suppressor genes. Curr Opin Oncol 3: 75–92, 1991

    PubMed  Google Scholar 

  33. Folkman J: What is the evidence that tumors are angiogenesis dependent? J Natl Cancer Inst 82: 4–6, 1990

    PubMed  Google Scholar 

  34. Fisher B, Gunduz N, Coile J, Rudock C, Saffer E: Presence of a growth-stimulating factor in serum following primary tumor removal in mice. Cancer Res 49: 1996–2001, 1989

    PubMed  Google Scholar 

  35. Valagussa P, Brambilla C, Zambetti M, Bonadonna G: Salvage treatments in relapsing resectable breast cancer. Recent Results in Cancer Research 115: 69–76, 1989

    PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Demicheli, R., Abbattista, A., Miceli, R. et al. Time distribution of the recurrence risk for breast cancer patients undergoing mastectomy: Further support about the concept of tumor dormancy. Breast Cancer Res Tr 41, 177–185 (1996). https://doi.org/10.1007/BF01807163

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01807163

Key words

Navigation