The learning curve in TaTME—considerations to guide safe implementation
Editorial

The learning curve in TaTME—considerations to guide safe implementation

Deborah S. Keller1, Roel Hompes2

1Division of Colorectal Surgery, Department of Surgery, Columbia University Medical Center, New York, NY, USA; 2Department of Surgery, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands

Correspondence to: Roel Hompes, MD. Department of Surgery, Amsterdam University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands. Email: roelhompes@gmail.com.

Provenance: This is an invited article commissioned by the Editor-in-Chief Minhua Zheng (Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Minimal Invasive Surgery Center, Shanghai, China).

Comment on: Lee L, Kelly J, Nassif GJ, et al. Defining the learning curve for transanal total mesorectal excision for rectal adenocarcinoma. Surg Endosc. 2018Defining the learning curve for transanal total mesorectal excision for rectal adenocarcinoma. Surg Endosc 2018. [Epub ahead of print].


Received: 28 December 2018; Accepted: 04 January 2019; Published: 17 January 2019.

doi: 10.21037/ales.2019.01.03


For a colorectal surgeon, the immediate goal in rectal cancer surgery is to extract a perfect total mesorectal excision (TME) specimen with clear oncologic margins. Since the introduction of the TME concept by Heald in 1982, data from both historic and modern randomized controlled trials (RCT) comparing surgical approaches for rectal cancer have demonstrated that this can be challenging (1-5). The subjective perception of a technically challenging and often unsatisfactory pelvic dissection, paired with the ongoing controversy regarding the optimal surgical approach, fuel the need for further innovation.

Transanal total mesorectal excision (TaTME) was introduced as an innovative procedure that may overcome the technical challenges of operating in the deep pelvis, where anatomic constraints and tumour specific characteristics have a major impact (6). While excellent short-term oncologic results have been reported, relatively high rates of complications and new procedure specific morbidity arose, most likely due to limited experience with the anatomic landmarks, critical procedural concepts, and pattern recognition with the “bottom up” view (7-15). The incidence and development of procedure specific complications reflects the unregulated nature of surgical innovation; analogous situations were seen with the introduction of laparoscopic cholecystectomy and minimal invasive colon cancer resections. A dilemma arises however, between prolonged waiting for sufficient safety and efficacy data or early adoption of new treatments that could potentially improve outcomes. A careful balance needs to be struck between the two as we keep in mind that “the new” is not always better, and too rapid widespread adoption of novel techniques may prove more harmful than beneficial for patients.

Adherence to the well-established IDEAL framework is recommended, which describes the five stages for evaluating and reporting surgical innovations: Idea, Development, Exploration, Assessment and Long-term (16). The concept of the learning curve is often overlooked but remains important in surgical innovation, and a key element in the “Exploration” phase within IDEAL. Lee et al. describe the institutional learning curve for TaTME in a single high-volume tertiary referral center with extensive experience in transanal minimally invasive surgery (TAMIS) and minimally invasive rectal cancer surgery (17). Their findings suggest 45–51 cases are needed to reach technical proficiency, with improvements in the pathologic outcomes resulting after 36 cases. The authors attempted to validate their reported patient numbers using an adjusted composite outcome measure of postoperative morbidity and operative times.

What constitutes an acceptable outcome measure as a proxy for clinical effectiveness with TaTME remains a contentious issue. Similar to the ALACART and ACOSOG Z6051 randomized controlled trials, a composite endpoint for high-quality TME was used by the authors to determine proficiency (3,4). In both trials, even though the laparoscopic arm did not meet the criteria for non-inferiority compared to the open arm, rates of 2-year disease-free survival (DFS) and recurrence were not significantly different (18,19). Similarly, the significantly decreased rate of a positive circumferential resection margin following transanal low rectal dissection compared to a full laparoscopic approach reported by Denost et al. did not translate into a decreased incidence of local recurrence (20).

Other issues exist in the authors’ chosen method to measure learning. Operating time is not an ideal outcome measure. Prior work has shown that operative times are a weak proxy for learning, and do not relate to proficiency (21-23). It may be assumed that with experience, operating times will drop. This assumption relies on all patients, tumors, and operative conditions being equal. In reality, surgeons will generally perform more complex cases with increased experience and comfort with a procedure; the more complex procedures have inherently longer operating times. Assessing for a second peak on the learning curve may add value if using operative times. There should also be consideration of the individual surgeon and center’s case volumes, and experience with TAMIS. The work by Lee et al. represented a high-volume TaTME and TAMIS center, where their results may not be generalizable. Furthermore, cases from more than 1 surgeon at the center were bundled; a more accurate way to define the learning curve may be to evaluate consecutive cases from each individual surgeon to create individual CUSUM curves which can then be compared for validity and generalizability. Alternative suggestions for outcome measures that could serve as a proxy for clinical effectiveness in TaTME procedures are postoperative morbidities, particularly septic complications related to the anastomosis which can serve as an indirect indicator for quality, functional outcomes, and quality of life. In future studies, such outcomes can and should be used for the characterization of the learning curve following appropriate case mix.

Developing expertise in any procedure requires a steady case volume to optimize technical skills and improve clinical judgement. These attributes will improve performance along the learning curve. Therefore, centralization in high-volume centers with high-volume surgeons is an area for debate, particularly for complex procedures like TaTME, where the number to achieve proficiency is high and associated with morbidity along the learning curve. Aside from appropriate institutional case volume, parallel interventions are required to boost performance, shorten the learning curve, and reduce subsequent risk to patients. To ensure safe introduction amidst the enthusiasm, a structured training pathway that includes mentorship for the initial cases with participation in multicenter registries is recommended, and controlled trials are underway.


Acknowledgements

None.


Footnote

Conflicts of Interest: The authors have no conflicts of interest to declare.


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doi: 10.21037/ales.2019.01.03
Cite this article as: Keller DS, Hompes R. The learning curve in TaTME—considerations to guide safe implementation. Ann Laparosc Endosc Surg 2019;4:7.