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


Journal

Cancer medicine
ISSN: 2045-7634
Titre abrégé: Cancer Med
Pays: United States
ID NLM: 101595310

Informations de publication

Date de publication:
10 2023
Historique:
received: 11 07 2023
accepted: 02 09 2023
medline: 23 10 2023
pubmed: 15 9 2023
entrez: 15 9 2023
Statut: ppublish

Résumé

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. 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 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. 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.

Sections du résumé

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.

Identifiants

pubmed: 37712677
doi: 10.1002/cam4.6532
pmc: PMC10587948
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

19394-19405

Informations de copyright

© 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

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Auteurs

Elle C Moore (EC)

Tempus Labs, Inc, Chicago, Illinois, USA.

Gerard C Blobe (GC)

Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, USA.

Nicholas C DeVito (NC)

Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Center for Cancer Immunotherapy, Duke University Medical Center, Durham, North Carolina, USA.

Brent A Hanks (BA)

Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, USA.
Center for Cancer Immunotherapy, Duke University Medical Center, Durham, North Carolina, USA.

Michael R Harrison (MR)

Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Duke Cancer Institute Center for Prostate and Urologic Cancers, Durham, North Carolina, USA.

Christopher J Hoimes (CJ)

Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Center for Cancer Immunotherapy, Duke University Medical Center, Durham, North Carolina, USA.
Duke Cancer Institute Center for Prostate and Urologic Cancers, Durham, North Carolina, USA.

Jingquan Jia (J)

Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.

Michael A Morse (MA)

Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.

Parvathy Jayaprakasan (P)

Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.

Andrew MacKelfresh (A)

Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.

Hillary Mulder (H)

Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.

Adam J Hockenberry (AJ)

Tempus Labs, Inc, Chicago, Illinois, USA.

Alia Zander (A)

Tempus Labs, Inc, Chicago, Illinois, USA.

Martin C Stumpe (MC)

Tempus Labs, Inc, Chicago, Illinois, USA.

Jackson Michuda (J)

Tempus Labs, Inc, Chicago, Illinois, USA.

Kyle A Beauchamp (KA)

Tempus Labs, Inc, Chicago, Illinois, USA.

Eric Perakslis (E)

Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.

Timothy Taxter (T)

Tempus Labs, Inc, Chicago, Illinois, USA.

Daniel J George (DJ)

Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Duke Cancer Institute Center for Prostate and Urologic Cancers, Durham, North Carolina, USA.

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