Prasad Pooja, Wallace Lauren, Navidi Maziar, Phillips Alexander W
Northern Oesophagogastric Unit, Royal Victoria Infirmary, Newcastle Upon Tyne, UK.
Northern Oesophagogastric Unit, Royal Victoria Infirmary, Newcastle Upon Tyne, UK.
Surgery. 2022 May;171(5):1247-1256. doi: 10.1016/j.surg.2021.10.050. Epub 2021 Nov 28.
Minimally invasive techniques are increasingly used in the treatment of esophageal cancer. The learning curve for minimally invasive esophagectomy is variable and can impact patient outcomes. The aim of this study was to review the current evidence on learning curves in minimally invasive esophagectomy and identify which parameters are used for benchmarking.
A search of the major reference databases (PubMed, Medline, Cochrane) was performed with no time limits up to February 2020. Results were screened in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies were included if an assessment of the learning curve was reported on, regardless of which (if any) statistical method was used.
Twenty-nine studies comprising 3,741 patients were included. Twenty-two studies reported on a combination of thoracoscopic, hybrid, and total minimally invasive esophagectomy, 6 studies reported robotic-assisted minimally invasive esophagectomy alone, and 1 study evaluated both robotic-assisted minimally invasive esophagectomy and thoracoscopic esophagectomies. Operating time was the most frequently used parameter to determine learning curve progression (23/39 studies), with number of resected lymph nodes, morbidity, and blood loss also frequently used. Learning curves were found to plateau at 7 to 60 cases for thoracoscopic esophagectomy, 12 to 175 cases for total and thoracoscopic/hybrid esophagectomy, and 9 to 85 cases for robotic-assisted minimally invasive esophagectomy.
Multiple parameters are employed to gauge minimally invasive esophagectomy learning curve progression. However, there are no validated or approved sets of outcomes. Further work is required to determine the optimum parameters that should be used to ensure best patient outcomes and required length of proctoring.
微创技术在食管癌治疗中的应用日益广泛。微创食管切除术的学习曲线存在差异，可能会影响患者的治疗效果。本研究旨在回顾目前关于微创食管切除术学习曲线的证据，并确定用于基准评估的参数。
检索主要参考数据库（PubMed、Medline、Cochrane），检索时间截至2020年2月，无时间限制。根据系统评价和Meta分析的首选报告项目指南对结果进行筛选。如果报告了对学习曲线的评估，则纳入研究，无论使用何种（如果有的话）统计方法。
纳入了29项研究，共3741例患者。22项研究报告了胸腔镜、杂交和完全微创食管切除术的联合应用，6项研究仅报告了机器人辅助微创食管切除术，1项研究评估了机器人辅助微创食管切除术和胸腔镜食管切除术。手术时间是确定学习曲线进展最常用的参数（23/39项研究），切除淋巴结数量、发病率和失血量也经常被使用。胸腔镜食管切除术的学习曲线在7至60例时趋于平稳，完全和胸腔镜/杂交食管切除术在12至175例时趋于平稳,机器人辅助微创食管切除术在9至85例时趋于平稳。
采用多个参数来衡量微创食管切除术学习曲线的进展。然而，目前尚无经过验证或批准的结果集。需要进一步开展工作，以确定用于确保最佳患者治疗效果和所需指导时长的最佳参数。
