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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.
Affiliation
  • Moore EC; Tempus Labs, Inc, Chicago, Illinois, USA.
  • Blobe GC; Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
  • DeVito NC; Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, USA.
  • Hanks BA; Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
  • Harrison MR; Center for Cancer Immunotherapy, Duke University Medical Center, Durham, North Carolina, USA.
  • Hoimes CJ; Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
  • Jia J; Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, USA.
  • Morse MA; Center for Cancer Immunotherapy, Duke University Medical Center, Durham, North Carolina, USA.
  • Jayaprakasan P; Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
  • MacKelfresh A; Duke Cancer Institute Center for Prostate and Urologic Cancers, Durham, North Carolina, USA.
  • Mulder H; Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
  • Hockenberry AJ; Center for Cancer Immunotherapy, Duke University Medical Center, Durham, North Carolina, USA.
  • Zander A; Duke Cancer Institute Center for Prostate and Urologic Cancers, Durham, North Carolina, USA.
  • Stumpe MC; Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
  • Michuda J; Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
  • Beauchamp KA; Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.
  • Perakslis E; Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.
  • Taxter T; Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.
  • George DJ; Tempus Labs, Inc, Chicago, Illinois, USA.
Cancer Med ; 12(19): 19394-19405, 2023 10.
Article in En | MEDLINE | ID: mdl-37712677
ABSTRACT

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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neoplasms, Unknown Primary / Neoplasms, Second Primary Type of study: Diagnostic_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Cancer Med Year: 2023 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neoplasms, Unknown Primary / Neoplasms, Second Primary Type of study: Diagnostic_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Cancer Med Year: 2023 Type: Article Affiliation country: United States