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Original Investigation
From the American Head and Neck Society
February 9, 2017

Assessment of Surgical Learning Curves in Transoral Robotic Surgery for Squamous Cell Carcinoma of the Oropharynx

Author Affiliations
  • 1Department of Otolaryngology–Head and Neck Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
  • 2Biostatistics Facility, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania
  • 3Veterans Affairs Pittsburgh Health System, Pittsburgh, Pennsylvania
JAMA Otolaryngol Head Neck Surg. Published online February 9, 2017. doi:10.1001/jamaoto.2016.4132
Key Points

Question  This study assesses learning curves for the oncologic transoral robotic surgery (TORS) surgeon and elucidates the number of cases needed to identify the learning phase.

Results  In this analysis learning curves for TORS for oropharyngeal cancer were surgeon-specific but tended to show inflection points between 20 and 30 cases.

Meaning  Evidence for learning should be tracked for surgeons using TORS as an oncologic treatment modality, which may be used as a guide to assist with surgeon credentialing.


Importance  Transoral robotic surgery (TORS) is increasingly employed as a treatment option for squamous cell carcinoma of the oropharynx (OPSCC). Measures of surgical learning curves are needed particularly as clinical trials using this technology continue to evolve.

Objective  To assess learning curves for the oncologic TORS surgeon and to identify the number of cases needed to identify the learning phase.

Design, Setting, and Participants  A retrospective review of all patients who underwent TORS for OPSCC at the University of Pittsburgh Medical Center between March 2010 and March 2016. Cases were excluded for involvement of a subsite outside of the oropharynx, for nonmalignant abnormality or nonsquamous histology, unknown primary, no tumor in the main specimen, free flap reconstruction, and for an inability to define margin status.

Exposures  Transoral robotic surgery for OPSCC.

Main Outcomes and Measures  Primary learning measures defined by the authors include the initial and final margin status and time to resection of main surgical specimen. A cumulative sum learning curve was developed for each surgeon for each of the study variables. The inflection point of each surgeon’s curve was considered to be the point signaling the completion of the learning phase.

Results  There were 382 transoral robotic procedures identified. Of 382 cases, 160 met our inclusion criteria: 68 for surgeon A, 37 for surgeon B, and 55 for surgeon C. Of the 160 included patients, 125 were men and 35 were women. The mean (SD) age of participants was 59.4 (9.5) years. Mean (SD) time to resection including robot set-up was 79 (36) minutes. The inflection points for the final margin status learning curves were 27 cases (surgeon A) and 25 cases (surgeon C). There was no inflection point for surgeon B for final margin status. Inflection points for mean time to resection were: 39 cases (surgeon A), 30 cases (surgeon B), and 27 cases (surgeon C).

Conclusions and Relevance  Using metrics of positive margin rate and time to resection of the main surgical specimen, the learning curve for TORS for OPSCC is surgeon-specific. Inflection points for most learning curves peak between 20 and 30 cases.