4.6 Article

Evaluation of Ki-67 index in EUS-FNA specimens for the assessment of malignancy risk in pancreatic neuroendocrine tumors

Journal

ENDOSCOPY
Volume 46, Issue 1, Pages 32-38

Publisher

GEORG THIEME VERLAG KG
DOI: 10.1055/s-0033-1344958

Keywords

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Funding

  1. Ministry of Health, Labour, and Welfare of Japan
  2. National Cancer Center Research and Development Fund

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Background and study aim: Malignancy in pancreatic neuroendocrine tumors (PNETs) is graded by assessing the resected specimens according to the World Health Organization (WHO) 2010 criteria. The feasibility of such grading using endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) specimens remains unclear. The aim of this study was to ascertain the optimal method of measuring the Ki-67 index in EUS-FNA specimens, using resected specimens as the criterion standard. Patients and methods: A total of 58 consecutive patients diagnosed with PNETs between March 1998 and May 2011 were included. The study measured intratumoral Ki-67 index heterogeneity, concordance rates of PNET grading by EUS-FNA with grade of the resected tumor, optimal method of measuring the Ki-67 index in EUS-FNA specimens, and survival analysis based on EUS-FNA specimen grading. Results: Intratumoral dispersion of Ki-67 index in resected specimens was 0.033 for Grade 1 and 0.782 for Grade 2 tumors (P<0.001). Concordance rates for WHO classification between EUS-FNA and resected specimens were 74.0% using the mean Ki-67 index in EUS-FNA specimens and 77.8% using the highest Ki-67 index. The concordance rate rose to 90% when EUS-FNA samples with less than 2000 tumor cells were excluded (26% of EUS-FNA cases). The Kaplan-Meier survival curves were significantly stratified by the EUS-FNA grading of PNETs with 5-year survival rates of 100%, 58.3%, and 0%, for Grade 1, Grade 2, and neuroendocrine carcinoma (NEC) tumors, respectively. Conclusions: Grading of PNETs by the highest Ki-67 index in EUS-FNA specimens with adequate cellularity has a high concordance with grading of resected specimens, and can predict long term patient survival with high accuracy.

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