4.2 Article

EUS-Guided FNA for Diagnosis of Pancreatic Cystic Lesions: a Meta-Analysis

Journal

CELLULAR PHYSIOLOGY AND BIOCHEMISTRY
Volume 36, Issue 3, Pages 1197-1209

Publisher

Cell Physiol Biochem Press GmbH & Co
DOI: 10.1159/000430290

Keywords

EUS-FNA; Diagnosis; Pancreatic cystic lesions; Malignantcy

Funding

  1. Natural Science Foundation of Hubei Province [2012FFB04303]

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Background: Preoperative diagnosis of pancreatic cystic lesions (PCLs) must be reliable as the current standard treatment, major or total pancreatectomy, dramatically affects quality of life. Additionally, early diagnosis of malignancy is essential to an improved prognosis. The diagnostic accuracy of fluid analysis using endoscopic ultrasonography-guided fine-needle aspiration (EUS-FNA) has been demonstrated in pancreatic solid lesions. The utility of this technique in the diagnosis of PCLs is still unknown. Methods: A comprehensive search was performed in multiple databases. Studies differentiating benign and malignant PCLs via EUS-FNA were included in this meata-analysis. The quality of diagnostic accuracy studies (QUADAS) was adopted to evaluate the selected studies. Pooled sensitivity, specificity, likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristic (sROC) curve analyses were conducted. Two main classification types of malignancy were characterized and analyzed. We also generated a subgroup analysis of available clinical factors. Publication bias was evaluated by Begg's and Egger's tests. Results: Sixteen studies containing 1024 subjects have been published. The pooled sensitivity for malignant cytology according to classification 1 was 0.51 (95% CI, 0.45-0.58), and pooled specificity was 0.94 (95% CI, 0.92-0.96). When the detected PCLs were identified as classification 2, suspicious malignancy or potential malignancy, sensitivity and specificity were similar, 0.52 (95% CI, 0.46-0.57) and 0.97 (95% CI, 0.95-0.98) respectively. Conclusion: This meta-analysis demonstrates that EUS-FNA is a reliable clinical tool for the diagnosis of PCLs. However, a more accurate algorithm is needed to reduce various biases and to improve the sensitivity of EUS-FNA in the detection of malignant PCLs. Copyright (C) 2015 S. Karger AG, Basel

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