Literature DB >> 25655120

Update on nodal staging in non-small cell lung cancer with integrated positron emission tomography/computed tomography: a meta-analysis.

Kyoungjune Pak1, Sohyun Park, Gi Jeong Cheon, Keon Wook Kang, In-Joo Kim, Dong Soo Lee, E Edmund Kim, June-Key Chung.   

Abstract

OBJECTIVES: Nowadays, the number of primary studies on fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) has been increasing rapidly. Thus, we updated meta-analysis to evaluate the test performance of FDG PET/CT for nodal staging in non-small cell lung cancer (NSCLC) including the most recent studies.
METHODS: We performed a systematic search of MEDLINE and EMBASE for English publications using keywords "positron emission tomography", "lung cancer", and "lymph node". All searches were limited to human studies. Inclusion criteria were studies of the initial nodal staging of NSCLC with PET/CT. The reasons for exclusion are as follows: (1) studies with PET, (2) previous therapy before PET/CT, (3) nodal staging not confirmed by histology, and (4) reviews, abstracts, and editorial materials. 786 articles were identified through database searching.
RESULTS: 28 studies including 3,255 patients and 11,887 lymph nodes (LN) were eligible for this study. The pooled sensitivity was 0.62 (95% CI 0.54-0.70), widely ranging from 0.13 to 0.98. The specificity ranged between 0.72 and 0.98 with an overall estimated specificity of 0.92 (0.88-0.95) for node-based data. The pooled sensitivity, specificity, positive and negative likelihood ratio were 0.67 (0.54-0.79), 0.87 (0.82-0.91), 5.20 (3.59-7.54), and 0.37 (0.25-0.55) for patient-based data. Studies from tuberculosis (Tb) endemic countries showed lower sensitivity (0.56 vs 0.68, p = 0.03) for node-based data and lower specificity (0.83 vs 0.89, p < 0.01) for patient-based ones.
CONCLUSIONS: PET/CT has a high specificity, but low sensitivity for detecting LN metastasis in patients with NSCLC. Tb might be one of the main reasons for lower sensitivity of PET/CT in several countries. The primary clinicians of lung cancer should be aware of the possibility of hidden metastatic LNs in bilateral FDG uptake of mediastinal and hilar LNs, especially in the Tb endemic countries.

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Year:  2015        PMID: 25655120     DOI: 10.1007/s12149-015-0958-6

Source DB:  PubMed          Journal:  Ann Nucl Med        ISSN: 0914-7187            Impact factor:   2.668


  15 in total

Review 1.  Evaluation of lymph node metastasis in lung cancer: who is the chief justice?

Authors:  Yang Xia; Bin Zhang; Hao Zhang; Wen Li; Ko-Pen Wang; Huahao Shen
Journal:  J Thorac Dis       Date:  2015-12       Impact factor: 2.895

2.  Prediction of pathological nodal involvement by CT-based Radiomic features of the primary tumor in patients with clinically node-negative peripheral lung adenocarcinomas.

Authors:  Ying Liu; Jongphil Kim; Yoganand Balagurunathan; Samuel Hawkins; Olya Stringfield; Matthew B Schabath; Qian Li; Fangyuan Qu; Shichang Liu; Alberto L Garcia; Zhaoxiang Ye; Robert J Gillies
Journal:  Med Phys       Date:  2018-04-29       Impact factor: 4.071

3.  Evaluation of lobar lymph node metastasis in non-small cell lung carcinoma using modified total lesion glycolysis.

Authors:  Hitoshi Dejima; Hiroaki Kuroda; Yuko Oya; Noriaki Sakakura; Yoshitaka Inaba; Tsuneo Tamaki; Yasushi Yatabe; Yukinori Sakao
Journal:  J Thorac Dis       Date:  2018-12       Impact factor: 2.895

4.  Development and validation of a deep learning signature for predicting lymph node metastasis in lung adenocarcinoma: comparison with radiomics signature and clinical-semantic model.

Authors:  Xiaoling Ma; Liming Xia; Jun Chen; Weijia Wan; Wen Zhou
Journal:  Eur Radiol       Date:  2022-09-28       Impact factor: 7.034

5.  FDG PET-CT SUVmax and IASLC/ATS/ERS histologic classification: a new profile of lung adenocarcinoma with prognostic value.

Authors:  Marina Suárez-Piñera; José Belda-Sanchis; Alvaro Taus; Albert Sánchez-Font; Antoni Mestre-Fusco; Marcel Jiménez; Lara Pijuan
Journal:  Am J Nucl Med Mol Imaging       Date:  2018-04-25

6.  Improving accuracy of hilar and lobar nodal staging in non-small cell lung cancer.

Authors:  Juha Kauppi; Jari Räsänen
Journal:  J Thorac Dis       Date:  2019-05       Impact factor: 2.895

7.  FDG-PET parameters predicting mediastinal malignancy in lung cancer.

Authors:  M Serra Fortuny; M Gallego; Ll Berna; C Montón; L Vigil; M J Masdeu; A Fernández-Villar; M I Botana; R Cordovilla; R García-Luján; E Cases; E Monsó
Journal:  BMC Pulm Med       Date:  2016-12-08       Impact factor: 3.317

8.  Comparison of 18F-FDG PET/CT and DWI for detection of mediastinal nodal metastasis in non-small cell lung cancer: A meta-analysis.

Authors:  Guohua Shen; You Lan; Kan Zhang; Pengwei Ren; Zhiyun Jia
Journal:  PLoS One       Date:  2017-03-02       Impact factor: 3.240

9.  DeepCUBIT: Predicting Lymphovascular Invasion or Pathological Lymph Node Involvement of Clinical T1 Stage Non-Small Cell Lung Cancer on Chest CT Scan Using Deep Cubical Nodule Transfer Learning Algorithm.

Authors:  Kyongmin Sarah Beck; Bomi Gil; Sae Jung Na; Ji Hyung Hong; Sang Hoon Chun; Ho Jung An; Jae Jun Kim; Soon Auck Hong; Bora Lee; Won Sang Shim; Sungsoo Park; Yoon Ho Ko
Journal:  Front Oncol       Date:  2021-07-05       Impact factor: 6.244

10.  A decision tree model for predicting mediastinal lymph node metastasis in non-small cell lung cancer with F-18 FDG PET/CT.

Authors:  Kyoungjune Pak; Keunyoung Kim; Mi-Hyun Kim; Jung Seop Eom; Min Ki Lee; Jeong Su Cho; Yun Seong Kim; Bum Soo Kim; Seong Jang Kim; In Joo Kim
Journal:  PLoS One       Date:  2018-02-27       Impact factor: 3.240

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