Cancer Medicine (Oct 2023)

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

  • Elle C. Moore,
  • Gerard C. Blobe,
  • Nicholas C. DeVito,
  • Brent A. Hanks,
  • Michael R. Harrison,
  • Christopher J. Hoimes,
  • Jingquan Jia,
  • Michael A. Morse,
  • Parvathy Jayaprakasan,
  • Andrew MacKelfresh,
  • Hillary Mulder,
  • Adam J. Hockenberry,
  • Alia Zander,
  • Martin C. Stumpe,
  • Jackson Michuda,
  • Kyle A. Beauchamp,
  • Eric Perakslis,
  • Timothy Taxter,
  • Daniel J. George

DOI
https://doi.org/10.1002/cam4.6532
Journal volume & issue
Vol. 12, no. 19
pp. 19394 – 19405

Abstract

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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.