Role of EUS-FNA-Based Cytology in the Diagnosis of Mucinous Pancreatic Cystic Lesions: A Systematic Review and Meta-Analysis
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- Thosani, N., Thosani, S., Qiao, W. et al. Dig Dis Sci (2010) 55: 2756. doi:10.1007/s10620-010-1361-8
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Preoperative diagnosis of malignancy in pancreatic cystic lesions (PCLs) remains challenging. Most non-mucinous cystic lesions (NMCLs) are benign, but mucinous cystic lesions (MCLs) are more likely to be premalignant or malignant.
The aim of this study was to assess the sensitivity, specificity, and positive and negative likelihood ratios (LRs) of EUS-FNA-based cytology in differentiating MCLs from non-mucinous PCLs.
We conducted a comprehensive search of MEDLINE, SCOPUS, Cochrane, and “CINAHL Plus” databases to identify studies, in which the results of EUS-FNA-based cytology of PCLs were compared with those of surgical biopsy or surgical excision histopathology. A DerSimonian-Laird random effect model was used to estimate the pooled sensitivity, specificity, and LRs, and a summary receiver-operating characteristic (SROC) curve was constructed.
We included 376 patients from 11 distinct studies who underwent EUS-FNA-based cytology and also had histopathological diagnosis. The pooled sensitivity and specificity in diagnosing MCLs were 0.63 (95% CI, 0.56–0.70) and 0.88 (95% CI, 0.83–0.93), respectively. The positive and negative LRs in diagnosing MCLs were 4.46 (95% CI, 1.21–16.43) and 0.46 (95% CI, 0.25–0.86), respectively. The area under the curve (AUC) was 0.89.
EUS-FNA-based cytology has overall low sensitivity but good specificity in differentiating MCLs from NMCLs. Further research is required to improve the overall sensitivity of EUS-FNA-based cytology to diagnose MCLs while evaluating PCL.
KeywordsEUSFNACytologyMeta-analysisPancreatic cyst lesions
Pancreatic cyst lesions
Pancreatic cyst neoplasm
Non-mucinous cystic lesions
Mucinous cystic lesions
Serous cyst adenoma
Solid pseudopapillary tumor
Pancreatic endocrine tumor
Intraductal papillary mucinous neoplasms
Summary receiver operating characteristic
Diagnostic odds ratio
Area under curve