Learning curve and factors influencing successful robot-assisted bilateral sentinel lymph node mapping in early-stage cervical cancer: an observational cohort study.

IF 2.9 3区 医学 Q3 ENGINEERING, BIOMEDICAL Expert Review of Medical Devices Pub Date : 2023-07-01 DOI:10.1080/17434440.2023.2212157
Ilse G T Baeten, Jacob P Hoogendam, Arthur J A T Braat, Bart de Keizer, Cornelis G Gerestein, Ronald P Zweemer
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Abstract

Objectives: To evaluate whether a learning curve affects the bilateral sentinel lymph node (SLN) detection in early-stage cervical cancer.

Methods: All patients with FIGO (2018) stage IA1-IB2 or IIA1 cervical cancer who had undergone robot-assisted SLN mapping performed with a combination of preoperative technetium-99m nanocolloids (including preoperative imaging) and intraoperative blue dye were retrospectively included. Risk-adjusted cumulative sum (RA-CUSUM) analysis was used to determine if a learning curve based on bilateral SLN detection existed in this cohort.

Results: A total of 227 cervical cancer patients were included. In 98.2% of patients (223/227) at least one SLN was detected. The bilateral SLN detection rate was 87.2% (198/227). Except for age (OR 1.06 per year, 95%CI 1.02-1.09), no significant risk factors for non-bilateral SLN detection were found (e.g., prior conization, BMI or FIGO stage). The RA-CUSUM analysis showed no clear learning phase during the first procedures and cumulative bilateral detection rate remained at least 80% during the entire inclusion period.

Conclusions: In this single-institution experience, we observed no learning curve affecting robot-assisted SLN mapping using a radiotracer and blue dye in early-stage cervical cancer patients, with stable bilateral detection rates of at least 80% when adhering to a standardized methodology.

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早期宫颈癌机器人辅助双侧前哨淋巴结定位成功的学习曲线和影响因素:一项观察性队列研究。
目的:探讨学习曲线对早期宫颈癌双侧前哨淋巴结(SLN)检测的影响。方法:回顾性分析所有FIGO (2018) IA1-IB2期或IIA1期宫颈癌患者,这些患者接受了机器人辅助SLN定位,术前使用技术-99m纳米胶体(包括术前成像)和术中蓝色染料联合进行SLN定位。采用风险调整累积和(RA-CUSUM)分析来确定该队列中是否存在基于双侧SLN检测的学习曲线。结果:共纳入227例宫颈癌患者。98.2%的患者(223/227)至少检出一种SLN。双侧SLN检出率为87.2%(198/227)。除年龄(OR 1.06 /年,95%CI 1.02-1.09)外,未发现非双侧SLN检测的显著危险因素(例如,既往锥化,BMI或FIGO分期)。RA-CUSUM分析显示,在第一次手术中没有明确的学习阶段,在整个纳入期间,累积双侧检出率保持在80%以上。结论:在这个单一机构的经验中,我们观察到没有学习曲线影响早期宫颈癌患者使用放射性示踪剂和蓝色染料的机器人辅助SLN定位,当坚持标准化方法时,稳定的双侧检出率至少为80%。
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来源期刊
Expert Review of Medical Devices
Expert Review of Medical Devices 医学-工程:生物医学
CiteScore
5.90
自引率
3.20%
发文量
69
审稿时长
6-12 weeks
期刊介绍: The journal serves the device research community by providing a comprehensive body of high-quality information from leading experts, all subject to rigorous peer review. The Expert Review format is specially structured to optimize the value of the information to reader. Comprehensive coverage by each author in a key area of research or clinical practice is augmented by the following sections: Expert commentary - a personal view on the most effective or promising strategies Five-year view - a clear perspective of future prospects within a realistic timescale Key issues - an executive summary cutting to the author''s most critical points In addition to the Review program, each issue also features Medical Device Profiles - objective assessments of specific devices in development or clinical use to help inform clinical practice. There are also Perspectives - overviews highlighting areas of current debate and controversy, together with reports from the conference scene and invited Editorials.
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