Predictors of false-negative results from percutaneous transthoracic fine-needle aspiration biopsy: An observational study from a retrospective cohort

Young Joo Suh, Jae Hoon Lee, Jin Hur, Sae Rom Hong, Dong Jin Im, Yun Jung Kim, Yoo Jin Hong, Hye Jeong Lee, Young Jin Kim, Byoung Wook Choi

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6 Citations (Scopus)

Abstract

Purpose: We investigated factors predictive of false-negative pulmonary lesions with nonspecific benign cytology results on percutaneous transthoracic fine-needle aspiration biopsy (FNAB). Materials and Methods: We included 222 pulmonary lesions that had a nonspecific benign result from percutaneous transthoracic FNAB between March 2005 and December 2012, and were confirmed by subsequent pathologic results or adequate clinical follow up over at least 2 years. Clinical, imaging, and biopsy procedure-related findings were compared between lesions with a final diagnosis of malignancy (false-negative) and lesions with a benign diagnosis (true-negative). Multivariate logistic regression analysis was performed to identify significant predictors of false-negatives. Results: Of 222 lesions, 115 lesions were proved to be false-negatives, and 107 were true-negatives. Compared with the true-negatives, false-negative lesions showed significantly older age (p=0.037), higher maximum standardized uptake value (SUVmax) on positron emission tomography (p=0.001), larger lesion size (p=0.007), and lesion characteristics of a subsolid nodule (p=0.007). On multivariate logistic regression analysis, SUVmax, lesion size, and lesion characteristics were significant predictors of falsenegative results. Conclusion: Among the clinical, radiologic, and procedure-related factors analyzed, high SUVmax, large lesion size, and subsolid lesions were useful for predicting malignancy in pulmonary lesions with nonspecific benign cytology results on FNAB.

Original languageEnglish
Pages (from-to)1243-1251
Number of pages9
JournalYonsei medical journal
Volume57
Issue number5
DOIs
Publication statusPublished - 2016 Sept

Bibliographical note

Publisher Copyright:
© Yonsei University College of Medicine 2016.

All Science Journal Classification (ASJC) codes

  • Medicine(all)

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