ArticleCancer medicine2021
Refined pancreatobiliary UroVysion criteria and an approach for further optimization.
Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Morpho-molecular approach (NGSPathologica · 2025Article
- Diagnostic Accuracy Performance of Fluorescence In Situ Hybridization (FISH) for Biliary Strictures: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2024Review
- Review
- Applications of Exosomes in Diagnosing Muscle Invasive Bladder Cancer.Pharmaceutics · 2022Review
- Refined pancreatobiliary UroVysion criteria and an approach for further optimization.Cancer medicine · 2021Article
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pancreatobiliary strictures are a common source of false negatives for malignancy detection. UroVysion is more sensitive than any other method but remains underutilized because of conflicting sensitivities and specificities due to a lack of standardized cutoff criteria and confusion in interpreting results in the context of primary sclerosing cholangitis. We set out to determine the sensitivities and specificities of UroVysion, brushing cytology, forceps biopsies, and fine needle aspiration (FNAs) for pancreatobiliary stricture malignancy detection. A retrospective review was performed of all biopsied pancreatobiliary strictures at our institution over 5 years. UroVysion was unquestionably the most sensitive method and all methods were highly specific. Sensitivity was highest while maintaining specificity when a malignant interpretation was limited to cases with 5+ cells with the same polysomic signal pattern and/or loss of one or both 9p21 signals. Only UroVysion detected the metastases and a neuroendocrine tumor. In reviewing and analyzing the signal patterns, we noticed trends according to location and diagnosis. Herein we describe our method for analyzing signal patterns and propose cutoff criteria based upon observations gleaned from such analysis.
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Registered trials
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