Annals of Surgical Oncology

, Volume 23, Issue 11, pp 3744–3748 | Cite as

Factors Impacting Use of Robotic Surgery for Treatment of Endometrial Cancer in the United States

  • Erin A. Blake
  • Jeanelle Sheeder
  • Kian Behbakht
  • Saketh R. Guntupalli
  • Michael S. Guy
Gynecologic Oncology



This study was designed to examine the impact of patient socioeconomic, clinical, and hospital characteristics on the utilization of robotics in the surgical staging of endometrial cancer.


Patients surgically treated for endometrial cancer at facilities that offered robotic and open approaches were identified from the National Inpatient Sample Database from 2008 to 2012. The groups were compared for socioeconomic, clinical, and hospital differences. Medical comorbidity scores were calculated using the Charlson comorbidity index. T tests and χ 2 were used to compare groups. Multivariable analyses were used to determine factors that were independently associated with a robotic approach.


A total of 18,284 patients were included (robotic, n = 7169; laparotomy, n = 11,115). Significant differences were noted in all patient clinical and socioeconomic characteristics and all hospital characteristics. Multivariable analyses identified factors that independently predicted patients undergoing robotic surgery. These patients were older [adjusted odds ratio (aOR) 1.008; 95 % confidence interval (CI) 1.004–1.011], white (aOR 1.38; 95 % CI 1.27–1.50), and privately insured (aOR 1.16; 95 % CI 1.07–1.26). Clinically, these women were more likely to be obese (aOR 1.20; 95 % CI 1.11–1.30) and to be undergoing an elective case (aOR 1.25; 95 % CI 1.11–1.40). Hospitals were more likely to be under private control (aOR 1.55, 95 % CI 1.39–1.71) but less likely to be located in the south (aOR 0.87; 0.81–0.93), quantified as large or medium (aOR 0.57; 95 %CI 0.50–0.67), or teaching hospitals (aOR 0.68; 95 % CI 0.63–0.74).


Socioeconomic status and hospital characteristics are factors that independently predict robotic utilization in the United States. These racial, socioeconomic, and geographic disparities warrant further study regarding the utilization of this important technology.


Endometrial Cancer Robotic Surgery Charlson Comorbidity Index National Comprehensive Cancer Network Surgical Staging 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Conflict of interest

The authors report no conflict of interest.


  1. 1.
    Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin. 2015;65(1):5–29.CrossRefPubMedGoogle Scholar
  2. 2.
    DeSantis CE, Lin CC, Mariotto AB, Siegel RL, Stein KD, Kramer JL, et al. Cancer treatment and survivorship statistics, 2014. CA Cancer J Clin. 2014;64(4):252–71.CrossRefPubMedGoogle Scholar
  3. 3.
    Bradley CJ, Given CW, Roberts C. Race, socioeconomic status, and breast cancer treatment and survival. J Natl Cancer Inst. 2002;94(7):490–6.CrossRefPubMedGoogle Scholar
  4. 4.
    Morris AM, Rhoads KF, Stain SC, Birkmeyer JD. Understanding racial disparities in cancer treatment and outcomes. J Am Coll Surg. 2010;211(1):105–13.CrossRefPubMedGoogle Scholar
  5. 5.
    Shavers VL, Brown ML. Racial and ethnic disparities in the receipt of cancer treatment. J Natl Cancer Inst. 2002;94(5):334–57.CrossRefPubMedGoogle Scholar
  6. 6.
    Bach PB, Schrag D, Brawley OW, Galaznik A, Yakren S, Begg CB. Survival of blacks and whites after a cancer diagnosis. JAMA. 2002;287(16):2106–13.CrossRefPubMedGoogle Scholar
  7. 7.
    Parsons HM, Habermann EB, Stain SC, Vickers SM, Al-Refaie WB. What happens to racial and ethnic minorities after cancer surgery at American College of Surgeons National Surgical Quality Improvement Program hospitals? J Am Coll Surg. 2012;214(4):539–47; discussion 479. CrossRefPubMedGoogle Scholar
  8. 8.
    Liu FW, Randall LM, Tewari KS, Bristow RE. Racial disparities and patterns of ovarian cancer surgical care in California. Gynecol Oncol. 2014;132(1):221–6.CrossRefPubMedGoogle Scholar
  9. 9.
    Aranda MA, McGory M, Sekeris E, Maggard M, Ko C, Zingmond DS. Do racial/ethnic disparities exist in the utilization of high-volume surgeons for women with ovarian cancer? Gynecol Oncol. 2008;111(2):166–72.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Robinson CN, Balentine CJ, Sansgiry S, Berger DH. Disparities in the use of minimally invasive surgery for colorectal disease. J Gastrointest Surg. 2012;16(5):897–903; discussion -4.CrossRefPubMedGoogle Scholar
  11. 11.
    Loehrer AP, Song Z, Auchincloss HG, Hutter MM. Massachusetts health care reform and reduced racial disparities in minimally invasive surgery. JAMA Surg. 2013;148(12):1116–22.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Varela JE, Nguyen NT. Disparities in access to basic laparoscopic surgery at U.S. academic medical centers. Surg Endosc. 2011;25(4):1209–14.CrossRefPubMedGoogle Scholar
  13. 13.
    Greenberg CC, Weeks JC, Stain SC. Disparities in oncologic surgery. World J Surg. 2008;32(4):522–8.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Koh W-Jea. NCCN Clinical Practice Guidelines in Oncology (NCCN guidelines):Uterine Neoplasms. National Cancer Center Network; Version 2.2015.Google Scholar
  15. 15.
    Walker JL, Piedmonte MR, Spirtos NM, Eisenkop SM, Schlaerth JB, Mannel RS, et al. Laparoscopy compared with laparotomy for comprehensive surgical staging of uterine cancer: Gynecologic Oncology Group Study LAP2. J Clin Oncol. 2009;27(32):5331–6.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Walker JL, Piedmonte MR, Spirtos NM, Eisenkop SM, Schlaerth JB, Mannel RS, et al. Recurrence and survival after random assignment to laparoscopy versus laparotomy for comprehensive surgical staging of uterine cancer: Gynecologic Oncology Group LAP2 Study. J Clin Oncol. 2012;30(7):695–700.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Sinno AK, Fader AN. Robotic-assisted surgery in gynecologic oncology. Fertil Steril. 2014;102(4):922–32.CrossRefPubMedGoogle Scholar
  18. 18.
    Gehrig PA, Cantrell LA, Shafer A, Abaid LN, Mendivil A, Boggess JF. What is the optimal minimally invasive surgical procedure for endometrial cancer staging in the obese and morbidly obese woman? Gynecol Oncol. 2008;111(1):41–5.CrossRefPubMedGoogle Scholar
  19. 19.
    Doo DW, Guntupalli SR, Corr BR, Sheeder J, Davidson SA, Behbakht K, et al. Comparative surgical outcomes for endometrial cancer patients 65 years old or older staged with robotics or laparotomy. Ann Surg Oncol. 2015;22(11):3687–3694.CrossRefPubMedGoogle Scholar
  20. 20.
    Yu X, Lum D, Kiet TK, Fuh KC, Orr J, Jr., Brooks RA, et al. Utilization of and charges for robotic versus laparoscopic versus open surgery for endometrial cancer. J Surg Oncol. 2013;107(6):653–8.CrossRefPubMedGoogle Scholar
  21. 21.
    HCUP Databases. Healthcare Cost and Utilization Project (HCUP). 2006–2009. Agency for Healthcare Research and Quality, Rockville, MD.
  22. 22.
    HCUP Nationwide Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). 2011. Agency for Healthcare Research and Quality, Rockville, MD.
  23. 23.
  24. 24.
    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.CrossRefPubMedGoogle Scholar
  25. 25.
    Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45(6):613–9.CrossRefPubMedGoogle Scholar
  26. 26.
    Long B, Liu FW, Bristow RE. Disparities in uterine cancer epidemiology, treatment, and survival among African Americans in the United States. Gynecol Oncol. 2013;130(3):652–9.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Fedewa SA, Lerro C, Chase D, Ward EM. Insurance status and racial differences in uterine cancer survival: a study of patients in the National Cancer Database. Gynecol Oncol. 2011;122:63–8.CrossRefPubMedGoogle Scholar
  28. 28.
    Liang MI, Rosen MA, Rath KS, Hade EM, Clements AE, Backes FJ, et al. Predicting inpatient stay lasting two midnights or more after robotic surgery for endometrial cancer. J Minim Invasive Gynecol. 2015;22(4):583–589.CrossRefPubMedGoogle Scholar
  29. 29.
    Collins Y, Holcomb K, Chapman-Davis E, Khabele D, Farley JH. Gynecologic cancer disparities: a report from the Health Disparities Taskforce of the Society of Gynecologic Oncology. Gynecol Oncol. 2014;133(2):353–61.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Chan JK, Gardner AB, Taylor K, Blansit K, Thompson CA, Brooks R, et al. The centralization of robotic surgery in high-volume centers for endometrial cancer patients: a study of 6560 cases in the U.S. Gynecol Oncol. 2015;138(1):128–32.CrossRefPubMedGoogle Scholar
  31. 31.
    Bell MC, Torgerson J, Seshadri-Kreaden U, Suttle AW, Hunt S. Comparison of outcomes and cost for endometrial cancer staging via traditional laparotomy, standard laparoscopy and robotic techniques. Gynecol Oncol. 2008;111:407–11.CrossRefPubMedGoogle Scholar

Copyright information

© Society of Surgical Oncology 2016

Authors and Affiliations

  • Erin A. Blake
    • 1
  • Jeanelle Sheeder
    • 1
  • Kian Behbakht
    • 2
  • Saketh R. Guntupalli
    • 2
  • Michael S. Guy
    • 3
  1. 1.Department of Obstetrics and GynecologyUniversity of ColoradoAuroraUSA
  2. 2.Division of Gynecologic Oncology, Department of Obstetrics and GynecologyUniversity of ColoradoDenverUSA
  3. 3.Division of Gynecologic Oncology and Advanced Pelvic Surgery, Department of Obstetrics and GynecologyUniversity of CincinnatiCincinnatiUSA

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