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Year 2020 / Volume 112 / Number 9
Original

Sentinel lymph node mapping for metastasis detection in colorectal cancer: a systematic review and meta-analysis

722-730

DOI: 10.17235/reed.2020.6767/2019

Likui Qiao,

Abstract

Introduction: controversy exists on the diagnostic performance of sentinel lymph node (SLN) mapping in colorectal cancer. This study aimed to provide a more precise estimation of its clinical significance. Materials and methods: a systematic search of electronic databases was conducted to retrieve all relevant studies up to August 31st, 2019. Detection rate, sensitivity, and upstaging rate were pooled together, and a subgroup analysis was performed to identify factors that affect diagnostic performance. The prognostic value of upstaging was also explored. Results: sixty-eight studies were eligible and included. The pooled SLN detection rate was 0.93 (95 % CI, 0.91-0.94), with a significant higher rate in colon cancer or in studies including more than 100 patients. The overall sensitivity of the SLN procedure in colorectal cancer was 0.72 (95 % CI, 0.67-0.77). The tracers used were found to influence sensitivity. A mean weighted upstaging of 0.22 (95 % CI, 0.18-0.25) was identified. True upstaging, defined as micro-metastases, was 14 %. Upstaged patients were associated with worse overall survival (OS) when compared with node-negative patients (HR = 2.60, 95 % CI, 0.16-4.63). In addition, upstaged patients had a lower 5-year disease-free survival (DFS) rate than node-negative patients. Conclusion: based on the results of the present meta-analysis, the SLN mapping procedure should focus on early stage patients to refine staging, since upstaging appeared to be a prognostic factor for DFS and OS. The SLN procedure can be recommended for colorectal cancer patients in addition to conventional resection.

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Qiao L. Sentinel lymph node mapping for metastasis detection in colorectal cancer: a systematic review and meta-analysis. 6767/2019

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Publication history

Received: 25/11/2019

Accepted: 11/03/2020

Online First: 07/09/2020

Published: 10/09/2020

Article revision time: 92 days

Article Online First time: 287 days

Article editing time: 290 days

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