Assessment of surgical learning curves in transoral robotic surgery for squamous cell carcinoma of the oropharynx

William Greer Albergotti, William E. Gooding, Mark W. Kubik, Mathew Geltzeiler, Seungwon Kim, Umamaheswar Duvvuri, Robert L. Ferris

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

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, 160met 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 Usingmetrics 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.

Original languageEnglish (US)
Pages (from-to)542-548
Number of pages7
JournalJAMA Otolaryngology - Head and Neck Surgery
Volume143
Issue number6
DOIs
StatePublished - Jun 1 2017
Externally publishedYes

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Oropharynx
Learning Curve
Robotics
Squamous Cell Carcinoma
Learning
Surgeons
Unknown Primary Neoplasms
Free Tissue Flaps
Histology
Outcome Assessment (Health Care)
Clinical Trials
Technology

ASJC Scopus subject areas

  • Surgery
  • Otorhinolaryngology

Cite this

Assessment of surgical learning curves in transoral robotic surgery for squamous cell carcinoma of the oropharynx. / Albergotti, William Greer; Gooding, William E.; Kubik, Mark W.; Geltzeiler, Mathew; Kim, Seungwon; Duvvuri, Umamaheswar; Ferris, Robert L.

In: JAMA Otolaryngology - Head and Neck Surgery, Vol. 143, No. 6, 01.06.2017, p. 542-548.

Research output: Contribution to journalArticle

Albergotti, William Greer ; Gooding, William E. ; Kubik, Mark W. ; Geltzeiler, Mathew ; Kim, Seungwon ; Duvvuri, Umamaheswar ; Ferris, Robert L. / Assessment of surgical learning curves in transoral robotic surgery for squamous cell carcinoma of the oropharynx. In: JAMA Otolaryngology - Head and Neck Surgery. 2017 ; Vol. 143, No. 6. pp. 542-548.
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abstract = "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, 160met 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 Usingmetrics 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.",
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AU - Kim, Seungwon

AU - Duvvuri, Umamaheswar

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N2 - 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, 160met 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 Usingmetrics 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.

AB - 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, 160met 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 Usingmetrics 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.

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