Evidence map›Paper›PMID 37712677›Full record

ArticleCancer medicine2023

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 and 9 more

Abstract read
In one paragraph

Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Elle C MooreTempus Labs, Inc, Chicago, Illinois, USA.
Gerard C BlobeDivision of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Nicholas C DeVitoDivision of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Brent A HanksDivision of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Michael R HarrisonDivision of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Christopher J HoimesDivision of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Jingquan JiaDivision of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Michael A MorseDivision of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Parvathy JayaprakasanDuke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.
Andrew MacKelfreshDuke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.
Hillary MulderDuke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.
Adam J HockenberryTempus Labs, Inc, Chicago, Illinois, USA.ORCID 0000-0001-9476-0104
Alia ZanderTempus Labs, Inc, Chicago, Illinois, USA.
Martin C StumpeTempus Labs, Inc, Chicago, Illinois, USA.
Jackson MichudaTempus Labs, Inc, Chicago, Illinois, USA.
Kyle A BeauchampTempus Labs, Inc, Chicago, Illinois, USA.
Eric PerakslisDuke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA.
Timothy TaxterTempus Labs, Inc, Chicago, Illinois, USA.ORCID 0000-0001-6489-1007
Daniel J GeorgeDivision of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.ORCID 0000-0003-1499-7203

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRoughly 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.

methodsWe 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.

resultsResults 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.

conclusionsA 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.

Indexed as

Neoplasms, Second PrimaryNeoplasms, Unknown PrimaryHumansPathology, MolecularRetrospective Studies

Identifiers

PMID37712677
PMCPMC10587948

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.