Literature DB >> 31715310

Intraoperative frozen section for identifying the invasion status of lung adenocarcinoma: A systematic review and meta-analysis.

Feng Li1, Lin Yang2, Yue Zhao1, Ligong Yuan1, Shuaibo Wang1, Yousheng Mao3.   

Abstract

BACKGROUND: For early-stage lung adenocarcinoma, determining the extent of surgical resection and lymphadenectomy according to the invasion status of the tumour may be more reliable. Intraoperative frozen section (FS) is a potentially effective method to identify the invasion status while its accuracy is still unknown. This meta-analysis aimed to evaluate the accuracy of FS for the invasion status of lung adenocarcinoma.
METHODS: We conducted a systematic search of PubMed, Embase, Scopus and Cochrane Library databases (from inception to October 26, 2018) to identify studies investigating the accuracy of FS for the invasion status of lung adenocarcinoma. The accuracy of FS was evaluated by calculating the pooled concordance rates (CCR) between FS and final pathology and the pooled sensitivity, specificity, and other parameters of FS for discriminating pre-/minimally invasive adenocarcinoma from invasive adenocarcinoma (IAC). The negative predictive value (NPV) of FS for diagnosing IAC was also calculated to evaluate the chance of underestimation.
RESULTS: Six eligible studies were included. The pooled CCR for differentiating pre-invasive adenocarcinoma, minimally invasive adenocarcinoma and IAC was 88% (95% CI, 84%-93%). When pre-invasive adenocarcinoma and minimally invasive adenocarcinoma were classified as a group, the pooled CCR, sensitivity, specificity of FS for differentiating pre-/minimally invasive adenocarcinoma from IAC were 95% (95% CI, 94%-97%), 95% (95% CI, 92%-97%), 95% (95% CI, 80%-99%), respectively. The pooled NPV of FS for diagnosing IAC was 95% (95% CI, 92%-97%).
CONCLUSIONS: Intraoperative FS is reliable for identifying the invasion status of lung adenocarcinoma, with high diagnostic accuracy for differentiating pre-/minimally invasive adenocarcinoma from IAC.
Copyright © 2019 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Frozen section; Invasion status; Lung adenocarcinoma

Mesh:

Year:  2019        PMID: 31715310     DOI: 10.1016/j.ijsu.2019.10.047

Source DB:  PubMed          Journal:  Int J Surg        ISSN: 1743-9159            Impact factor:   6.071


  3 in total

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Authors:  Alaa Ahmed Elshanbary; Alaa Abdelsameia Awad; Alaa Abdelsalam; Islam H Ibrahim; Walid Abdel-Aziz; Youssef Bahaaeldin Darwish; Alaa Saad Isa; Boutheyna Drid; Marwa Gamal Mustafa; Radwa Hamdy Allam; Amira A Abo Ali; Anas Zakarya Nourelden; Khaled Mohamed Ragab; Hussah I M AlGwaiz; Aeshah A Awaji; Mousa O Germoush; Ashraf Albrakati; Marina Piscopo; Nehmat Ghaboura; Mohamed Sayed Zaazouee
Journal:  Environ Sci Pollut Res Int       Date:  2022-05-11       Impact factor: 5.190

3.  Stain-free identification of tissue pathology using a generative adversarial network to infer nanomechanical signatures.

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Journal:  Nanoscale Adv       Date:  2021-09-02
  3 in total

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