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Evaluation of waiting times for breast cancer diagnosis and surgical treatment

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Abstract

Purpose

To analyse any delays in breast cancer diagnosis and surgical treatment, influence of clinical and biological factors and influence of delays on survival.

Methods/patients

A descriptive, observational, and retrospective study was conducted between 2006 and 2016 on stages I–III breast cancer patients. This is a retrospective review of health records to collect data on delays, patients’ clinical data, biological features of the tumour and information on treatment. Mortality data from the National Death Index.

Results

In 493 evaluable patients, the median of days from the first symptom to mammography, biopsy, and surgery was 41, 57, and 92, respectively. The median of days from screening mammography to biopsy and surgery was 10 and 51, respectively. From biopsy to surgery, the median was 34 days in every case. Over the last 5 years, an increase in biopsy–surgery delay has been observed (p = 0.0001). Tumour stages I and II vs. stage III (RR 1.74. 95% CI 1.08–2.80, p = 0.027), diagnosis in screening (RR 0.66. 95% CI 0.45–0.96, p = 0.030), and use of magnetic resonance imaging (RR 2.08. 95 CI 1.21–3.56, p = 0.008) condition a greater biopsy–surgery delay. No influence of delays on survival has been identified.

Conclusions

Delays in diagnosis and surgery in the case of women diagnosed on the basis of symptoms may be improved. There is a temporary tendency to a greater delay in surgery. Some clinical and biological factors must be taken into account to optimise delays. Survival results are not adversely affected by delays.

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References

  1. Waks AG, King TA, Winer EP. Timeliness in breast cancer treatment—the sooner, the better. JAMA Oncol. 2016;2(3):302–4. https://doi.org/10.1001/jamaoncol.2015.4506.

    Article  PubMed  Google Scholar 

  2. Goldie JH, Coldman AJ. A mathematic model for relating the drug sensitivity of tumors to their spontaneous mutation rate. Cancer Treat Rep. 1979;63(11):1727–33.

    PubMed  CAS  Google Scholar 

  3. Harding FA, McArthur JG, Gross JA, Raulet DH, Allison JP. CD28-mediated signalling co-stimulates murine T cells and prevents induction of anergy in T-cell clones. Nature. 1992;356(6370):607–9.

    Article  CAS  Google Scholar 

  4. Halsted WS. The results of radical operations for the cure of carcinoma of the breast. Ann Surg. 1907;46(1):1–19.

    Article  CAS  Google Scholar 

  5. Richards MA, Westcombe AM, Love SB, Littlejohns P, Ramírez AJ. Influence of delay on survival in patients with breast cancer: a systematic review. Lancet. 1999;353:1119–26.

    Article  CAS  Google Scholar 

  6. Wagner JL, Warneke CL, Mittendorf EA, Bedrosian I, Babiera GV, Kuerer HM, et al. Delays in primary surgical treatment are not associated with significant tumor size progression in breast cancer patients. Ann Surg. 2011;254:119–24.

    Article  Google Scholar 

  7. Brazda A, Estroff J, Euhus D, Leitch AM, Huth J, Andrews V, et al. Delays in time to treatment and survival impact in breast cancer. Ann Surg Oncol. 2010;17:291–6.

    Article  Google Scholar 

  8. Bilimoria KY, Ko CY, Tomlinson JS, Stewart AK, Talamonti MS, Hynes DL, et al. Wait times for cancer surgery in the United States: trends and predictors of delays. Ann Surg. 2011;253:779–85.

    Article  Google Scholar 

  9. DeSantis CE, Fedewa SA, Goding Sauer A, Kramer JL, Smith RA, Jemal A. Breast cancer statistics, 2015: convergence of incidence rates between black and white women. CA Cancer J Clin. 2016;66(1):31–42.

    Article  Google Scholar 

  10. Oken MM, Creech RH, Tormey DC, Horton J, Davis TE, McFadden ET, et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol. 1982;5(6):649–55.

    Article  CAS  Google Scholar 

  11. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis. 1987;40(5):373–83.

    Article  CAS  Google Scholar 

  12. Hudis CA, Barlow WE, Constantino JP, Gray RJ, Pritchard KI, Chapman JAW, et al. Proposal for standardized definitions for efficacy end points in adjuvant breast cancer trials: The STEEP system. J Clin Oncol. 2007;25(15):2127–32.

    Article  Google Scholar 

  13. Richardson LC, Royalty J, Howe W, Helsel W, Kammerer W, Benard VB. Timeliness of breast cancer diagnosis and initiation of treatment in the National Breast and Cervical Cancer Early Detection Program, 1996–2005. Am J Public Health. 2010;100:1769–76.

    Article  Google Scholar 

  14. Molinie F, Leux C, Delafosse P, Ayrault-Piault S, Arveux P, Woronoff AS, et al. Waiting time disparities in breast cancer diagnosis and treatment: a population-based study in France. Breast. 2013;22:810–6.

    Article  CAS  Google Scholar 

  15. Norsaadah B, Rampal KG, Rahmah MA, Naing NN, Biswal BM. Diagnosis delay of breast cancer and its associated factors in Malaysian women. BMC Cancer. 2011;11:141.

    Article  Google Scholar 

  16. Unger-Saldaña K, Miranda A, Zarco-Espinosa G, Mainero-Ratchelous F, Bargalló-Rocha E, Lázaro-León JM. Health system delay and its effect on clinical stage of breast cancer: multicenter study. Cancer. 2015;121:2198–206.

    Article  Google Scholar 

  17. Barros AF, Uemura G, Macedo JL. Interval for access to treatment for breast cancer in the Federal District, Brazil. Rev Bras Ginecol Obstet. 2013;35:458–63.

    Article  Google Scholar 

  18. Arnaout A, Catley C, Booth CM, McInnes M, Graham I, Kumar V, et al. Use of preoperative magnetic resonance imaging for breast cancer: a Canadian population-based study. JAMA Oncol. 2015;1(9):1238–50. https://doi.org/10.1001/jamaoncol.2015.3018.

    Article  PubMed  Google Scholar 

  19. Turnbull L, Brown S, Harvey I, Olivier C, Drew P, Napp V, et al. Comparative effectiveness of MRI in breast cancer (COMICE) trial: a randomised controlled trial. Lancet. 2010;375(9714):563–71. https://doi.org/10.1016/S0140-6736(09)62070-5.

    Article  PubMed  Google Scholar 

  20. Sainsbury R, Johnston C, Haward B. Effect on survival of delays in referral of patients with breast-cancer symptoms: a retrospective analysis. Lancet. 1999;353:1132–5.

    Article  CAS  Google Scholar 

  21. Arndt V, Sturmer T, Stegmaier C, Ziegler H, Becker A, Brenner H. Provider delay among patients with breast cancer in Germany: a population-based study. J Clin Oncol. 2003;21:1440–6.

    Article  Google Scholar 

  22. Chiarelli AM, Muradali D, Blackmore KM, Smith CR, Mirea L, Majpruz V, et al. Evaluating wait times from screening to breast cancer diagnosis among women undergoing organised assessment vs usual care. Br J Cancer. 2017;116:1254–63. https://doi.org/10.1038/bjc.2017.87.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Olivotto IA, Gomi A, Bancej C, Brisson J, Tonita J, Kan L, et al. Influence of delay to diagnosis on prognostic indicators of screen-detected breast carcinoma. Cancer. 2002;94:2143–50. https://doi.org/10.1002/cncr.10453.

    Article  PubMed  Google Scholar 

  24. Lee SH, Kim YS, Han W, Ryu HS, Chang JM, Cho N, et al. Tumor growth rate of invasive breast cancers during wait times for surgery assessed by ultrasonography. Medicine (Baltimore). 2016;95(37):e4874. https://doi.org/10.1097/MD.0000000000004874.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Bleicher RJ, Ruth K, Sigurdson ER, Beck JR, Ross E, Wong Y-N, et al. Time to surgery and breast cancer survival in the United States. JAMA Oncol. 2016;2(3):330–9.

    Article  Google Scholar 

  26. Thorne SE, Harris SR, Hislop TG, Vestrup JA. The experience of waiting for diagnosis after an abnormal mammogram. Breast J. 1999;5:42–51.

    Article  Google Scholar 

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Funding

This research did not receive any specific Grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Correspondence to J. M. Baena-Cañada.

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Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

The required favourable report of the institution’s Research Ethics Committee was requested and obtained.

Informed consent

Since it is a retrospective study based on the data contained in the medical histories and there has been no intervention or risks to patients, their informed consent was not necessary.

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Baena-Cañada, J.M., Rodríguez-Pérez, L., Gámez-Casado, S. et al. Evaluation of waiting times for breast cancer diagnosis and surgical treatment. Clin Transl Oncol 20, 1345–1352 (2018). https://doi.org/10.1007/s12094-018-1867-7

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  • DOI: https://doi.org/10.1007/s12094-018-1867-7

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