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Assessing the utility of molecular diagnostic classification for cancers of unknown primary

BACKGROUND: Roughly 5% of metastatic cancers present with uncertain origin, for which molecular classification could influence subsequent management; however, prior studies of molecular diagnostic classifiers have reported mixed results with regard to clinical impact. In this retrospective study, we...

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Autores principales: Moore, Elle C., Blobe, Gerard C., DeVito, Nicholas C., Hanks, Brent A., Harrison, Michael R., Hoimes, Christopher J., Jia, Jingquan, Morse, Michael A., Jayaprakasan, Parvathy, MacKelfresh, Andrew, Mulder, Hillary, Hockenberry, Adam J., Zander, Alia, Stumpe, Martin C., Michuda, Jackson, Beauchamp, Kyle A., Perakslis, Eric, Taxter, Timothy, George, Daniel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10587948/
https://www.ncbi.nlm.nih.gov/pubmed/37712677
http://dx.doi.org/10.1002/cam4.6532
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author Moore, Elle C.
Blobe, Gerard C.
DeVito, Nicholas C.
Hanks, Brent A.
Harrison, Michael R.
Hoimes, Christopher J.
Jia, Jingquan
Morse, Michael A.
Jayaprakasan, Parvathy
MacKelfresh, Andrew
Mulder, Hillary
Hockenberry, Adam J.
Zander, Alia
Stumpe, Martin C.
Michuda, Jackson
Beauchamp, Kyle A.
Perakslis, Eric
Taxter, Timothy
George, Daniel J.
author_facet Moore, Elle C.
Blobe, Gerard C.
DeVito, Nicholas C.
Hanks, Brent A.
Harrison, Michael R.
Hoimes, Christopher J.
Jia, Jingquan
Morse, Michael A.
Jayaprakasan, Parvathy
MacKelfresh, Andrew
Mulder, Hillary
Hockenberry, Adam J.
Zander, Alia
Stumpe, Martin C.
Michuda, Jackson
Beauchamp, Kyle A.
Perakslis, Eric
Taxter, Timothy
George, Daniel J.
author_sort Moore, Elle C.
collection PubMed
description BACKGROUND: Roughly 5% of metastatic cancers present with uncertain origin, for which molecular classification could influence subsequent management; however, prior studies of molecular diagnostic classifiers have reported mixed results with regard to clinical impact. In this retrospective study, we evaluated the utility of a novel molecular diagnostic classifier by assessing theoretical changes in treatment and additional testing recommendations from oncologists before and after the review of classifier predictions. METHODS: We retrospectively analyzed de‐identified records from 289 patients with a consensus diagnosis of cancer of uncertain/unknown primary (CUP). Two (or three, if adjudication was required) independent oncologists separately reviewed patient clinical information to determine the course of treatment before they reviewed results from the molecular diagnostic classifier and subsequently evaluated whether the predicted diagnosis would alter their treatment plan. RESULTS: Results from the molecular diagnostic classifier changed the consensus oncologist‐reported treatment recommendations for 235 out of 289 patients (81.3%). At the level of individual oncologist reviews (n = 414), 64.7% (n = 268) of treatment recommendations were based on CUP guidelines prior to review of results from the molecular diagnostic classifier. After seeing classifier results, 98.1% (n = 207) of the reviews, where treatment was specified (n = 211), were guided by the tissue of origin‐specific guidelines. Overall, 89.9% of the 414 total reviews either expressed strong agreement (n = 242) or agreement (n = 130) that the molecular diagnostic classifier result increased confidence in selecting the most appropriate treatment regimen. CONCLUSIONS: A retrospective review of CUP cases demonstrates that a novel molecular diagnostic classifier could affect treatment in the majority of patients, supporting its clinical utility. Further studies are needed to prospectively evaluate whether the use of molecular diagnostic classifiers improves clinical outcomes in CUP patients.
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spelling pubmed-105879482023-10-21 Assessing the utility of molecular diagnostic classification for cancers of unknown primary Moore, Elle C. Blobe, Gerard C. DeVito, Nicholas C. Hanks, Brent A. Harrison, Michael R. Hoimes, Christopher J. Jia, Jingquan Morse, Michael A. Jayaprakasan, Parvathy MacKelfresh, Andrew Mulder, Hillary Hockenberry, Adam J. Zander, Alia Stumpe, Martin C. Michuda, Jackson Beauchamp, Kyle A. Perakslis, Eric Taxter, Timothy George, Daniel J. Cancer Med RESEARCH ARTICLES BACKGROUND: Roughly 5% of metastatic cancers present with uncertain origin, for which molecular classification could influence subsequent management; however, prior studies of molecular diagnostic classifiers have reported mixed results with regard to clinical impact. In this retrospective study, we evaluated the utility of a novel molecular diagnostic classifier by assessing theoretical changes in treatment and additional testing recommendations from oncologists before and after the review of classifier predictions. METHODS: We retrospectively analyzed de‐identified records from 289 patients with a consensus diagnosis of cancer of uncertain/unknown primary (CUP). Two (or three, if adjudication was required) independent oncologists separately reviewed patient clinical information to determine the course of treatment before they reviewed results from the molecular diagnostic classifier and subsequently evaluated whether the predicted diagnosis would alter their treatment plan. RESULTS: Results from the molecular diagnostic classifier changed the consensus oncologist‐reported treatment recommendations for 235 out of 289 patients (81.3%). At the level of individual oncologist reviews (n = 414), 64.7% (n = 268) of treatment recommendations were based on CUP guidelines prior to review of results from the molecular diagnostic classifier. After seeing classifier results, 98.1% (n = 207) of the reviews, where treatment was specified (n = 211), were guided by the tissue of origin‐specific guidelines. Overall, 89.9% of the 414 total reviews either expressed strong agreement (n = 242) or agreement (n = 130) that the molecular diagnostic classifier result increased confidence in selecting the most appropriate treatment regimen. CONCLUSIONS: A retrospective review of CUP cases demonstrates that a novel molecular diagnostic classifier could affect treatment in the majority of patients, supporting its clinical utility. Further studies are needed to prospectively evaluate whether the use of molecular diagnostic classifiers improves clinical outcomes in CUP patients. John Wiley and Sons Inc. 2023-09-15 /pmc/articles/PMC10587948/ /pubmed/37712677 http://dx.doi.org/10.1002/cam4.6532 Text en © 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle RESEARCH ARTICLES
Moore, Elle C.
Blobe, Gerard C.
DeVito, Nicholas C.
Hanks, Brent A.
Harrison, Michael R.
Hoimes, Christopher J.
Jia, Jingquan
Morse, Michael A.
Jayaprakasan, Parvathy
MacKelfresh, Andrew
Mulder, Hillary
Hockenberry, Adam J.
Zander, Alia
Stumpe, Martin C.
Michuda, Jackson
Beauchamp, Kyle A.
Perakslis, Eric
Taxter, Timothy
George, Daniel J.
Assessing the utility of molecular diagnostic classification for cancers of unknown primary
title Assessing the utility of molecular diagnostic classification for cancers of unknown primary
title_full Assessing the utility of molecular diagnostic classification for cancers of unknown primary
title_fullStr Assessing the utility of molecular diagnostic classification for cancers of unknown primary
title_full_unstemmed Assessing the utility of molecular diagnostic classification for cancers of unknown primary
title_short Assessing the utility of molecular diagnostic classification for cancers of unknown primary
title_sort assessing the utility of molecular diagnostic classification for cancers of unknown primary
topic RESEARCH ARTICLES
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10587948/
https://www.ncbi.nlm.nih.gov/pubmed/37712677
http://dx.doi.org/10.1002/cam4.6532
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