Skip to main content

Advertisement

Log in

Differential impact of non-insulin-dependent diabetes mellitus and insulin-dependent diabetes mellitus on breast reconstruction outcomes

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

Abstract

While the comparative safety of breast reconstruction in diabetic patients has been previously studied, we examine the differential effects of insulin and non-insulin-dependence on surgical/medical outcomes. Patients undergoing implant/expander or autologous breast reconstruction were extracted from the National Surgical Quality Improvement Program 2005–2012 database. Preoperative and postoperative variables were analyzed using chi-square and Student’s t test as appropriate. Multivariate regression modeling was used to evaluate whether non-insulin-dependent diabetes mellitus (NIDDM) or insulin-dependent diabetes mellitus (IDDM) is independently associated with adverse 30-day events following breast reconstruction. Of 29,736 patients meeting inclusion criteria, 23,042 (77.5 %) underwent implant/expander reconstructions, of which 815 had NIDDM and 283 had IDDM. Of the 6,694 (22.5 %) patients who underwent autologous reconstructions, 286 had NIDDM and 94 had IDDM. Rates of overall and surgical complications significantly differed among non-diabetic, NIDDM and IDDM patients in both the implant/expander and autologous cohorts on univariate analysis. After multivariate analysis, NIDDM was significantly associated with surgical complications (OR 1.511); IDDM was significantly associated with medical (OR 1.815) and overall complications (OR 1.852); and any type of diabetes was significantly associated with surgical (OR 1.58) and overall (OR 1.361) complications after autologous reconstruction. Diabetes of any type was not associated with any type of complication after implant/expander reconstruction. In this large, multi-institutional study, diabetes mellitus was significantly associated with adverse outcomes after autologous, but not implant-based breast reconstruction. The multivariate analysis in this study adds granularity to the differential effects of NIDDM and IDDM on complication risk.

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

Similar content being viewed by others

References

  1. Habermann EB et al (2010) Are mastectomy rates really increasing in the United States. J Clin Oncol 28(21):3437–3441

    Article  PubMed  Google Scholar 

  2. Tracy MS et al (2013) Contralateral prophylactic mastectomy in women with breast cancer: trends, predictors, and areas for future research. Breast Cancer Res Treat 140(3):447–452

    Article  PubMed  Google Scholar 

  3. Tuttle TM et al (2010) The increasing use of prophylactic mastectomy in the prevention of breast cancer. Curr Oncol Rep 12(1):16–21

    Article  PubMed  Google Scholar 

  4. Tuttle TM et al (2007) Increasing use of contralateral prophylactic mastectomy for breast cancer patients: a trend toward more aggressive surgical treatment. J Clin Oncol 25(33):5203–5209

    Article  PubMed  Google Scholar 

  5. Fischer JP et al (2013) Complications and morbidity following breast reconstruction: a review of 16,063 cases from the 2005–2010 NSQIP datasets. J Plast Surg Hand Surg 48:104–114

  6. Albornoz CR et al (2013) A paradigm shift in U.S. Breast reconstruction: increasing implant rates. Plast Reconstr Surg 131(1):15–23

    Article  CAS  PubMed  Google Scholar 

  7. Cemal Y et al (2013) A paradigm shift in U.S. breast reconstruction: part 2. The influence of changing mastectomy patterns on reconstructive rate and method. Plast Reconstr Surg 131(3):320e–326e

    Article  CAS  PubMed  Google Scholar 

  8. Jones RL, Peterson CM (1981) Hematologic alterations in diabetes mellitus. Am J Med 70(2):339–352

    Article  CAS  PubMed  Google Scholar 

  9. Simpson LO (1985) Intrinsic stiffening of red blood cells as the fundamental cause of diabetic nephropathy and microangiopathy: a new hypothesis. Nephron 39(4):344–351

    Article  CAS  PubMed  Google Scholar 

  10. Fischer JP et al (2013) Impact of obesity on outcomes in breast reconstruction: analysis of 15,937 patients from the ACS-NSQIP datasets. J Am Coll Surg 217(4):656–664

    Article  PubMed  Google Scholar 

  11. Hanwright PJ et al (2013) The differential effect of BMI on prosthetic versus autogenous breast reconstruction: a multivariate analysis of 12,986 patients. Breast 22(5):938–945

    Article  PubMed  Google Scholar 

  12. Fischer JP et al (2013) Peri-operative risk factors associated with early tissue expander (TE) loss following immediate breast reconstruction (IBR): a review of 9,305 patients from the 2005–2010 ACS-NSQIP datasets. J Plast Reconstr Aesthet Surg 66(11):1504–1512

    Article  PubMed  Google Scholar 

  13. Moran SL, Serletti JM (2001) Outcome comparison between free and pedicled TRAM flap breast reconstruction in the obese patient. Plast Reconstr Surg 108(7):1954–1960 (discussion 1961–2)

    Article  CAS  PubMed  Google Scholar 

  14. Chang DW et al (2000) Effect of obesity on flap and donor-site complications in free transverse rectus abdominis myocutaneous flap breast reconstruction. Plast Reconstr Surg 105(5):1640–1648

    Article  CAS  PubMed  Google Scholar 

  15. Miller RB et al (2007) Microvascular breast reconstruction in the diabetic patient. Plast Reconstr Surg 119(1):38–45 (discussion 46–8)

    Article  CAS  PubMed  Google Scholar 

  16. Andree C et al (2013) A single center prospective study of bilateral breast reconstruction with free abdominal flaps: a critical analyses of 144 patients. Med Sci Monit 19:467–474

    Article  PubMed Central  PubMed  Google Scholar 

  17. Birkmeyer JD et al (2008) Blueprint for a new American College of Surgeons: National Surgical Quality Improvement Program. J Am Coll Surg 207(5):777–782

    Article  PubMed  Google Scholar 

  18. Ingraham AM et al (2010) Quality improvement in surgery: the American College of Surgeons National Surgical Quality Improvement Program approach. Adv Surg 44:251–267

    Article  PubMed  Google Scholar 

  19. Henderson WG, Daley J (2009) Design and statistical methodology of the National Surgical Quality Improvement Program: why is it what it is? Am J Surg 198(5 Suppl):S19–S27

    Article  PubMed  Google Scholar 

  20. Merkow RP, Bilimoria KY, Hall BL (2011) Interpretation of the C-statistic in the context of ACS-NSQIP models. Ann Surg Oncol 18(Suppl 3):S295 (author reply S296)

    Article  PubMed  Google Scholar 

  21. Paul P, Pennell ML, Lemeshow S (2013) Standardizing the power of the Hosmer–Lemeshow goodness of fit test in large data sets. Stat Med 32(1):67–80

    Article  PubMed  Google Scholar 

  22. Schauer PR et al (2014) Bariatric surgery versus intensive medical therapy for diabetes: 3-year outcomes. N Engl J Med 370:2002–2013

  23. Conrotto F et al (2014) Impact of diabetes mellitus on early and midterm outcomes after transcatheter aortic valve implantation (from a multicenter registry). Am J Cardiol 113(3):529–534

    Article  PubMed  Google Scholar 

  24. Yeh CC et al (2013) Adverse outcomes after noncardiac surgery in patients with diabetes: a nationwide population-based retrospective cohort study. Diabetes Care 36(10):3216–3221

    Article  PubMed  Google Scholar 

  25. Hensel JM et al (2001) An outcomes analysis and satisfaction survey of 199 consecutive abdominoplasties. Ann Plast Surg 46(4):357–363

    Article  CAS  PubMed  Google Scholar 

  26. Hanemann MS Jr, Grotting JC (2010) Evaluation of preoperative risk factors and complication rates in cosmetic breast surgery. Ann Plast Surg 64(5):537–540

    CAS  PubMed  Google Scholar 

  27. Xue DQ et al (2012) Risk factors for surgical site infections after breast surgery: a systematic review and meta-analysis. Eur J Surg Oncol 38(5):375–381

    Article  CAS  PubMed  Google Scholar 

  28. McCarthy CM et al (2008) Predicting complications following expander/implant breast reconstruction: an outcomes analysis based on preoperative clinical risk. Plast Reconstr Surg 121(6):1886–1892

    Article  CAS  PubMed  Google Scholar 

  29. Davis GB et al (2013) Identifying risk factors for surgical site infections in mastectomy patients using the National Surgical Quality Improvement Program database. Am J Surg 205(2):194–199

    Article  PubMed  Google Scholar 

  30. Momeni A et al (2009) Complications in abdominoplasty: a risk factor analysis. J Plast Reconstr Aesthet Surg 62(10):1250–1254

    Article  PubMed  Google Scholar 

  31. Neaman KC, Hansen JE (2007) Analysis of complications from abdominoplasty: a review of 206 cases at a university hospital. Ann Plast Surg 58(3):292–298

    Article  CAS  PubMed  Google Scholar 

  32. Pinsolle V et al (2006) Complications analysis of 266 immediate breast reconstructions. J Plast Reconstr Aesthet Surg 59(10):1017–1024

    Article  PubMed  Google Scholar 

  33. Marchant MH Jr et al (2009) The impact of glycemic control and diabetes mellitus on perioperative outcomes after total joint arthroplasty. J Bone Joint Surg Am 91(7):1621–1629

    Article  PubMed  Google Scholar 

  34. Belmont PJ Jr et al (2014) Thirty-day postoperative complications and mortality following total knee arthroplasty: incidence and risk factors among a national sample of 15,321 patients. J Bone Joint Surg Am 96(1):20–26

    Article  PubMed  Google Scholar 

  35. Bolognesi MP et al (2008) The impact of diabetes on perioperative patient outcomes after total hip and total knee arthroplasty in the United States. J Arthroplast 23(6 Suppl 1):92–98

    Article  Google Scholar 

  36. Epelboym I et al (2014) Limitations of ACS-NSQIP in reporting complications for patients undergoing pancreatectomy: underscoring the need for a pancreas-specific module. World J Surg 38:1461–1467

  37. Sippel RS, Chen H (2011) Limitations of the ACS NSQIP in thyroid surgery. Ann Surg Oncol 18(13):3529–3530

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This particular research received no internal or external grant funding.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standard

De-identified patient information is freely available to all institutional members who comply with the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) Data Use Agreement. The Data Use Agreement implements the protections afforded by the Health Insurance Portability and Accountability Act of 1996 and the ACS-NSQIP Hospital Participation Agreement, and conforms to the Declaration of Helsinki.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to John Y. S. Kim.

Additional information

The NSQIP and the hospitals participating in the NSQIP are the source of the data used herein; they have not been verified and are not responsible for the statistical validity of the data analysis, or the conclusions derived by the authors of this study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qin, C., Vaca, E., Lovecchio, F. et al. Differential impact of non-insulin-dependent diabetes mellitus and insulin-dependent diabetes mellitus on breast reconstruction outcomes. Breast Cancer Res Treat 146, 429–438 (2014). https://doi.org/10.1007/s10549-014-3024-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10549-014-3024-5

Keywords

Navigation