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Current Practices and Novel Techniques in the Diagnosis and Management of Neuroendocrine Tumors of Unknown Primary
Neuroendocrine tumors (NETs) comprise a heterogeneous group of neoplasms in which tumor staging/prognosis and response to treatments depend heavily on accurate and timely identification of the anatomic primary site or NET subtype. Despite recent technological advancements and use of multiple diagnos...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6830950/ https://www.ncbi.nlm.nih.gov/pubmed/31609931 http://dx.doi.org/10.1097/MPA.0000000000001391 |
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author | Hendifar, Andrew E. Ramirez, Robert A. Anthony, Lowell B. Liu, Eric |
author_facet | Hendifar, Andrew E. Ramirez, Robert A. Anthony, Lowell B. Liu, Eric |
author_sort | Hendifar, Andrew E. |
collection | PubMed |
description | Neuroendocrine tumors (NETs) comprise a heterogeneous group of neoplasms in which tumor staging/prognosis and response to treatments depend heavily on accurate and timely identification of the anatomic primary site or NET subtype. Despite recent technological advancements and use of multiple diagnostic modalities, 10% to 14% of newly diagnosed NETs are not fully characterized based on subtype or anatomic primary site. Inability to fully characterize NETs of unknown primary may cause delays in surgical intervention and limit potential treatment options. To address this unmet need, clinical validity and utility are being demonstrated for novel approaches that improve NET subtype or anatomic primary site identification. Functional imaging using (68)Ga-radiolabeled DOTATATE positron emission tomography/computed tomography has been shown to overcome some false-positive and resolution issues associated with octreotide scanning and computed tomography/magnetic resonance imaging. Using a genomic approach, molecular tumor classification based on differential gene expression has demonstrated high diagnostic accuracy in blinded validation studies of different NET types and subtypes. Given the widespread availability of these technologies, we propose an algorithm for the workup of NETs of unknown primary that integrates these approaches. Including these technologies in the standard workup will lead to better NET subtype identification and improved treatment optimization for patients. |
format | Online Article Text |
id | pubmed-6830950 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-68309502019-11-26 Current Practices and Novel Techniques in the Diagnosis and Management of Neuroendocrine Tumors of Unknown Primary Hendifar, Andrew E. Ramirez, Robert A. Anthony, Lowell B. Liu, Eric Pancreas Reviews Neuroendocrine tumors (NETs) comprise a heterogeneous group of neoplasms in which tumor staging/prognosis and response to treatments depend heavily on accurate and timely identification of the anatomic primary site or NET subtype. Despite recent technological advancements and use of multiple diagnostic modalities, 10% to 14% of newly diagnosed NETs are not fully characterized based on subtype or anatomic primary site. Inability to fully characterize NETs of unknown primary may cause delays in surgical intervention and limit potential treatment options. To address this unmet need, clinical validity and utility are being demonstrated for novel approaches that improve NET subtype or anatomic primary site identification. Functional imaging using (68)Ga-radiolabeled DOTATATE positron emission tomography/computed tomography has been shown to overcome some false-positive and resolution issues associated with octreotide scanning and computed tomography/magnetic resonance imaging. Using a genomic approach, molecular tumor classification based on differential gene expression has demonstrated high diagnostic accuracy in blinded validation studies of different NET types and subtypes. Given the widespread availability of these technologies, we propose an algorithm for the workup of NETs of unknown primary that integrates these approaches. Including these technologies in the standard workup will lead to better NET subtype identification and improved treatment optimization for patients. Lippincott Williams & Wilkins 2019-10 2019-10-15 /pmc/articles/PMC6830950/ /pubmed/31609931 http://dx.doi.org/10.1097/MPA.0000000000001391 Text en Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Reviews Hendifar, Andrew E. Ramirez, Robert A. Anthony, Lowell B. Liu, Eric Current Practices and Novel Techniques in the Diagnosis and Management of Neuroendocrine Tumors of Unknown Primary |
title | Current Practices and Novel Techniques in the Diagnosis and Management of Neuroendocrine Tumors of Unknown Primary |
title_full | Current Practices and Novel Techniques in the Diagnosis and Management of Neuroendocrine Tumors of Unknown Primary |
title_fullStr | Current Practices and Novel Techniques in the Diagnosis and Management of Neuroendocrine Tumors of Unknown Primary |
title_full_unstemmed | Current Practices and Novel Techniques in the Diagnosis and Management of Neuroendocrine Tumors of Unknown Primary |
title_short | Current Practices and Novel Techniques in the Diagnosis and Management of Neuroendocrine Tumors of Unknown Primary |
title_sort | current practices and novel techniques in the diagnosis and management of neuroendocrine tumors of unknown primary |
topic | Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6830950/ https://www.ncbi.nlm.nih.gov/pubmed/31609931 http://dx.doi.org/10.1097/MPA.0000000000001391 |
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