Diagnostic yield of endoscopic ultrasound-guided fine-needle aspiration-based cytology for distinguishing malignant and benign pancreatic cystic lesions: A systematic review and meta-analysis
Abstract
Background Preoperative diagnosis of malignancy in patients with pancreatic cystic lesions (PCLs) remains challenging. The aim of this study was to assess the sensitivity, specificity, and positive and negative likelihood ratios (LRs) of endoscopic ultrasound-guided fine needle aspiration (EUS-FNA)-based cytology in differentiating malignant PCLs from benign PCLs. Methods A comprehensive search was performed in multiple databases in November 2023. Studies differentiating benign and malignant PCLs via EUS-FNA-based cytology, in which the results were compared with those of surgical excision histopathology, were included in this meta-analysis. Data from the selected studies were pooled to summarize the sensitivity, specificity, positive and negative LRs, diagnostic odds ratios and summary receiver operating characteristic (SROC) curves. Results We included 755 patients from 15 distinct studies who underwent EUS-FNA-based cytology and had a histopathological diagnosis. The pooled sensitivity and specificity in diagnosing malignant PCLs were 0.62 (95% CI, 0.42–0.78) and 0.96 (95% CI, 0.91–0.98), respectively. The positive and negative LRs for diagnosing malignant PCLs were 16.3 (95% CI, 7.2–37.0) and 0.40 (95% CI, 0.25–0.64), respectively. The area under the curve (AUC) was 0.94 (95% CI, 0.91–0.95). Conclusions EUS-FNA-based cytology has overall high specificity, medium sensitivity and good diagnostic accuracy in differentiating malignant from benign PCLs. Further research is needed to improve the overall sensitivity of EUS-FNA-based cytology for the diagnosis of malignant PCLs.
Article Details
Authors (8)
Cong Ding
State Key Laboratory of Metabolism and Regulation in Complex Organisms, College of Chemistry and Molecular Sciences, Taikang Center for Life and Medical Sciences
Jian-feng Yang
Xia Wang
Yi-feng Zhou
Ye Gu
Qiang Liu
Hong-zhang Shen
Xiao-feng Zhang