Evidence map›Paper›PMID 39448514›Full record

ArticleDigestive diseases and sciences2024

Identification of Endosonographic Features that Compromise EUS-FNB Diagnostic Accuracy in Pancreatic Masses.

Hsueh-Chien Chiang, Chien-Jui Huang, Yao-Shen Wang, Chun-Te Lee, Meng-Ying Lin, Wei-Lun Chang

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Article in Digestive diseases and sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3 citing papers in PubMed.

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6 authors.

Hsueh-Chien ChiangDepartment of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, No.138, Sheng Li Road, Tainan, 704, Taiwan.
Chien-Jui HuangDepartment of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, No.138, Sheng Li Road, Tainan, 704, Taiwan.
Yao-Shen WangDepartment of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, No.138, Sheng Li Road, Tainan, 704, Taiwan.
Chun-Te LeeDepartment of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, No.138, Sheng Li Road, Tainan, 704, Taiwan.
Meng-Ying LinDepartment of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, No.138, Sheng Li Road, Tainan, 704, Taiwan. n049952@mail.hosp.ncku.edu.tw.
Wei-Lun ChangDepartment of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, No.138, Sheng Li Road, Tainan, 704, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEndoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) is highly accurate for diagnosing pancreatic mass. However, making diagnosis is challenging in 5-20% of patients. This study investigated the challenging features associated with reduced diagnostic performance in EUS-FNB and potential rescue methods that can improve the diagnostic rate.

methodsThis single-center retrospective study included patients with solid pancreatic tumors who underwent EUS-FNB between January 1, 2019, and December 12, 2021. Patients without a computed tomography (CT) scan or definite diagnosis were excluded. Challenging features were features that reduced diagnostic accuracy in EUS-FNB, as determined through multivariate analysis. Rescue methods were methods that assisted operators in assessing lesions in patients with challenging features.

resultsOf 332 enrolled patients, an accurate diagnosis obtained using EUS-FNB was achieved in 286 (86.1%). Univariable analysis revealed that the diagnostic accuracy was lower in cases of pancreatic tumors with isoattenuation in CT images (77.3% vs. 89.8%, odds ratio [OR]: 0.39, p = 0.003), an ill-defined margin on EUS (61.2% vs. 92.5%, OR: 0.13, p < 0.001), or tumor size < 20 mm (65.5% vs. 88.1%, OR: 0.26, p = 0.002). However, only ill-defined margins on EUS (OR: 0.14, p < 0.001) and tumor size < 20 mm (OR: 0.25, p = 0.005) were independent predictors of inconclusive EUS-FNB in the multivariate analysis. The use of contrast (OR: 4.46, p = 0.026) and a highly experienced endosonographer (> 5cases/month; OR: 3.25, p = 0.034) improved diagnostic performance in difficult cases.

conclusionsPancreatic tumors with ill-defined tumor margins on EUS or size < 20 mm are challenging features in EUS-FNB. The use of contrast and a highly experienced endosonographer can improve diagnostic performance in difficult cases.

Indexed as

Endoscopic Ultrasound-Guided Fine Needle AspirationEndosonographyPancreatic NeoplasmsAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedRetrospective StudiesTomography, X-Ray ComputedChallenging featureDiagnostic accuracyEndoscopic ultrasoundFine-needle biopsyPancreatic tumor

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.