Skip to main content
SpringerLink
Log in

Robotic intersphincteric resection for low rectal cancer: a cumulative sum analysis for the learning curve

  • Original Article
  • Published:
Surgery Today Aims and scope Submit manuscript

Abstract

Purpose

This study aimed to assess the learning curve of robot-assisted intersphincteric resection for low rectal cancer.

Methods

We retrospectively analyzed the clinical data of 89 patients who underwent robot-assisted intersphincteric resection. All surgeries were performed by the same group of surgeons at our institution between June 2016 and April 2021. The learning curve was evaluated using a cumulative sum analysis and the best-fit curve. The different stages of the learning curve were compared based on patient characteristics and short-term clinical outcomes to evaluate their impact on clinical efficacy.

Results

The minimum number of cases required to overcome the learning curve was 47. The learning curve was divided into the learning improvement and proficiency stages. Significant differences were observed in the operation time and the number of lymph nodes between the two stages (P < 0.05), whereas no significant differences were found in intraoperative blood loss, first postoperative exhaust time, postoperative complications, 3-year progression-free survival, overall survival, and local recurrence-free survival (P > 0.05).

Conclusion

Robotic-assisted intersphincteric resection for low rectal cancer exhibits a learning curve that can be divided into two stages: namely, learning improvement and proficiency. Achieving proficiency requires a minimum of 47 surgical cases.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

The data used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Weber PA, Merola S, Wasielewski A, Ballantyne GH. Telerobotic-assisted laparoscopic right and sigmoid colectomies for benign disease. Dis Colon Rectum. 2002;45:1689–96.

    Article  PubMed  Google Scholar 

  2. Shah MF, Nasir IUI, Parvaiz A. Robotic surgery for colorectal cancer. Visc Med. 2019;35:247–50.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Yamauchi S, Shiomi A, Matsuda C, Takemasa I, Hanai T, Uemura M, et al. Robotic-assisted colectomy for right-sided colon cancer: short-term surgical outcomes of a multi-institutional prospective cohort study in Japan. Ann Gastroenterol Surg. 2023;7:932–9.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Schiessel R, Karner-Hanusch J, Herbst F, Teleky B, Wunderlich M. Intersphincteric resection for low rectal tumours. Br J Surg. 1994;81:1376–8.

    Article  CAS  PubMed  Google Scholar 

  5. Piozzi GN, Park H, Kim J-S, Choi H-B, Lee T-H, Baek S-J, et al. Anatomic landmarks for transabdominal robotic-assisted intersphincteric dissection for ultralow anterior resection. Dis Colon Rectum. 2021;64:e87–8.

    Article  PubMed  Google Scholar 

  6. Chi P, Huang S-H, Lin H-M, Lu X-R, Huang Y, Jiang W-Z, et al. Laparoscopic transabdominal approach partial intersphincteric resection for low rectal cancer: surgical feasibility and intermediate-term outcome. Ann Surg Oncol. 2015;22:944–51.

    Article  PubMed  Google Scholar 

  7. Huang S, Huang Y, Chi P, Lin H, Lu X, Xu Z, et al. Completely abdominal approach laparoscopic partial intersphincteric resection after neoadjuvant chemoradiation for initial cT3 Juxta-anal rectal cancer. J Laparoendosc Adv Surg Tech A. 2019;29:809–16.

    Article  PubMed  Google Scholar 

  8. Huang S, Chen M, Deng Y, Wang X, Lu X, Jiang W, et al. Mesorectal fat area and mesorectal area affect the surgical difficulty of robotic-assisted mesorectal excision and intersphincteric resection, respectively, in different ways. Colorectal Dis. 2020;22:1130–8.

    Article  CAS  PubMed  Google Scholar 

  9. Park SY, Lee SM, Park JS, Kim HJ, Choi G-S. Robot surgery shows similar long-term oncologic outcomes as laparoscopic surgery for mid/lower rectal cancer but is beneficial to ypT3/4 after preoperative chemoradiation. Dis Colon Rectum. 2021;64:812–21.

    Article  PubMed  Google Scholar 

  10. Jiang W-Z, Xu J-M, Xing J-D, Qiu H-Z, Wang Z-Q, Kang L, et al. Short-term outcomes of laparoscopy-assisted vs open surgery for patients with low rectal cancer: the LASRE randomized clinical trial. JAMA Oncol. 2022;8:1607–15.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Park JS, Lee SM, Choi G-S, Park SY, Kim HJ, Song SH, et al. Comparison of laparoscopic versus robot-assisted surgery for rectal cancers: the COLRAR randomized controlled trial. Ann Surg. 2023;278:31–8.

    Article  PubMed  Google Scholar 

  12. Jayne D, Pigazzi A, Marshall H, Croft J, Corrigan N, Copeland J, et al. Effect of robotic-assisted vs conventional laparoscopic surgery on risk of conversion to open laparotomy among patients undergoing resection for rectal cancer: the ROLARR randomized clinical trial. JAMA. 2017;318:1569–80.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Feng Q, Yuan W, Li T, Tang B, Jia B, Zhou Y, et al. Robotic versus laparoscopic surgery for middle and low rectal cancer (REAL): short-term outcomes of a multicentre randomised controlled trial. Lancet Gastroenterol Hepatol. 2022;7:991–1004.

    Article  PubMed  Google Scholar 

  14. Wang X, Zheng Z, Yu Q, Ghareeb WM, Lu X, Huang Y, et al. Impact of surgical approach on surgical resection quality in mid- and low rectal cancer. A Bayesian network meta-analysis. Front Oncol. 2021;11: 699200.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Park JS, Kim NK, Kim SH, Lee KY, Lee KY, Shin JY, et al. Multicentre study of robotic intersphincteric resection for low rectal cancer. Br J Surg. 2015;102:1567–73.

    Article  CAS  PubMed  Google Scholar 

  16. Piozzi GN, Khobragade K, Aliyev V, Asoglu O, Bianchi PP, Butiurca V-O, et al. International standardization and optimization group for intersphincteric resection (ISOG-ISR): modified Delphi consensus on anatomy, definition, indication, surgical technique, specimen description and functional outcome. Colorectal Dis. 2023. https://doi.org/10.1111/codi.16704.

    Article  PubMed  Google Scholar 

  17. Kayano H, Okuda J, Tanaka K, Kondo K, Tanigawa N. Evaluation of the learning curve in laparoscopic low anterior resection for rectal cancer. Surg Endosc. 2011;25:2972–9.

    Article  PubMed  Google Scholar 

  18. Zhang L, Hu C, Qin Q, Li R, Zhao J, Zhang Z, et al. Learning process analysis of robotic lateral pelvic lymph node dissection for local advanced rectal cancer: the CUSUM curve of 78 consecutive patients. Surg Today. 2023. https://doi.org/10.1007/s00595-023-02725-6.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Kuo L-J, Lin Y-K, Chang C-C, Tai C-J, Chiou J-F, Chang Y-J. Clinical outcomes of robot-assisted intersphincteric resection for low rectal cancer: comparison with conventional laparoscopy and multifactorial analysis of the learning curve for robotic surgery. Int J Colorectal Dis. 2014;29:555–62.

    Article  PubMed  Google Scholar 

  20. Aghayeva A, Baca B. Robotic sphincter saving rectal cancer surgery: a learning curve analysis. Int J Med Robot. 2020;16: e2112.

    Article  PubMed  Google Scholar 

  21. Odermatt M, Ahmed J, Panteleimonitis S, Khan J, Parvaiz A. Prior experience in laparoscopic rectal surgery can minimise the learning curve for robotic rectal resections: a cumulative sum analysis. Surg Endosc. 2017;31:4067–76.

    Article  PubMed  Google Scholar 

  22. Tang B, Li T, Gao G, Shi J, Li T. Learning curve of robotic-assisted total mesorectal excision for rectal cancer. Front Oncol. 2022;12: 931426.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Sugishita T, Tsukamoto S, Imaizumi J, Takamizawa Y, Inoue M, Moritani K, et al. Evaluation of the learning curve for robot-assisted rectal surgery using the cumulative sum method. Surg Endosc. 2022;36:5947–55.

    Article  PubMed  Google Scholar 

  24. Kuo L-J, Hung C-S, Wang W, Tam K-W, Lee H-C, Liang H-H, et al. Intersphincteric resection for very low rectal cancer: clinical outcomes of open versus laparoscopic approach and multidimensional analysis of the learning curve for laparoscopic surgery. J Surg Res. 2013;183:524–30.

    Article  PubMed  Google Scholar 

  25. Yamaguchi T, Kinugasa Y, Shiomi A, Sato S, Yamakawa Y, Kagawa H, et al. Learning curve for robotic-assisted surgery for rectal cancer: use of the cumulative sum method. Surg Endosc. 2015;29:1679–85.

    Article  PubMed  Google Scholar 

  26. Kim JC, Kim CW, Lee JL, Yoon YS, Park IJ, Kim JR, et al. Complete intersphincteric longitudinal muscle excision May Be key to reducing local recurrence during intersphincteric resection. Eur J Surg Oncol. 2021;47:1629–36.

    Article  PubMed  Google Scholar 

  27. Kneist W, Stein H, Rheinwald M. Da Vinci single-port robot-assisted transanal mesorectal excision: a promising preclinical experience. Surg Endosc. 2020;34:3232–5.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank the Department of Colorectal Surgery staff at Fujian Medical University Union Hospital (FMUUH, Fuzhou, China).

Funding

Joint Funds for the Innovation of Science and Technology, Fujian Province (2017Y9038, 2023Y9218, 2020Y9071); Fujian Provincial Health Technology Project (2020GGB022, 2020CXA025), Natural Science Foundation of Fujian Province (2022J01753, 2020J011030), Medical Science Research Foundation of Beijing Medical and Health Foundation(B20062DS), and Bethune Charitable Foundation (X-J-2018-004).

Author information

Author notes

  1. Yihuang Gao, Hongfeng Pan, Jiahong Ye and Haoyang Ruan contributed equally to this work and should be considered co-first authors.

Authors and Affiliations

  1. Department of Colorectal Surgery, Fujian Medical University Union Hospital, No. 29 Xinquan Road, Fuzhou, 350001, Fujian, China

    Yihuang Gao, Hongfeng Pan, Jiahong Ye, Haoyang Ruan, Weizhong Jiang, Pan Chi, Ying Huang & Shenghui Huang

  2. Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Yihuang Gao, Hongfeng Pan, Jiahong Ye, Haoyang Ruan, Weizhong Jiang, Pan Chi, Ying Huang & Shenghui Huang

Authors
  1. Yihuang Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hongfeng Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jiahong Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Haoyang Ruan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Weizhong Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Pan Chi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ying Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Shenghui Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

YG, HP, HR, YH, JY, WJ, and PC conceived of the idea and designed the project. YG, JY, and HR collected data. YG and HP analyzed and interpreted the data. YG and SH drafted the manuscript. All authors have read and approved the final manuscript.

Corresponding authors

Correspondence to Pan Chi, Ying Huang or Shenghui Huang.

Ethics declarations

Conflict of interest

The authors declare no conflicts of interest.

Ethics approval and consent to participate

This study was approved by the Institutional Review Board of Fujian Medical University Union Hospital. All procedures performed in this study (involving human participants) were under the ethical standards of the institutional and/or national research committee and the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Consent for publication

We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We also confirm that the order of the authors listed in the manuscript has been approved by all the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gao, Y., Pan, H., Ye, J. et al. Robotic intersphincteric resection for low rectal cancer: a cumulative sum analysis for the learning curve. Surg Today (2024). https://doi.org/10.1007/s00595-024-02841-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00595-024-02841-x

Keywords

Search

Navigation