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Ann Surg Oncol ; 21(3): 829-40, 2014 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-24217787

RESUMO

BACKGROUND: Laparoscopic surgery is increasingly used in the treatment of colorectal cancer and more recently robotic assistance has been advocated. However, the learning curve to achieve surgical proficiency in laparoscopic surgery is ill-defined and subject to many influences. The aim of this review was to comprehensively appraise the literature on the learning curve for laparoscopic and robotic colorectal cancer surgery, and to quantify attainment of surgical proficiency and its implications in surgical clinical trial design. METHODS: A systematic review using a defined search strategy was performed. Included studies had to state an explicit numerical value of the learning curve evaluated by a single parameter or multiple parameters. RESULTS: Thirty-four studies were included, 28 laparoscopic and 6 robot assisted. Of the laparoscopic studies, nine defined the learning curve on the basis of a single parameter. Nine studies used more than one parameter to define learning, and 11 used a cumulative sum (CUSUM) analysis. One study used both a multiparameter and CUSUM analysis. The definition of proficiency was subjective, and the number of operations to achieve it ranged from 5 to 310 cases for laparoscopic and 15-30 cases for robotic surgery. CONCLUSIONS: The learning curve in laparoscopic colorectal surgery is multifaceted and often ill-defined, with poor descriptions of mentorship/supervision. Further, the quantification to attain proficiency is variable. The use of a single parameter to quantify this is simplistic. Multidimensional assessment is recommended; as part of this, the CUSUM model, which assesses trends in multiple surgical outcomes, is useful and appropriate when assessing the learning curve in a clinical setting.


Assuntos
Competência Clínica , Ensaios Clínicos como Assunto , Neoplasias Colorretais/cirurgia , Cirurgia Colorretal/educação , Laparoscopia/educação , Projetos de Pesquisa , Robótica/educação , Humanos , Prognóstico
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