Evidence map›Paper›PMID 38893178›Full record

ArticleCancers2024

Reasons for Discordance between

Jade Wang, Elisabeth O'Dwyer, Juana Martinez Zuloaga, Kritika Subramanian, Jim C Hu, Yuliya S Jhanwar, Himanshu Nagar, Arindam RoyChoudhury, John Babich, Sandra Huicochea Castellanos and 2 more

Abstract read
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

12 authors.

Jade WangDepartment of Internal Medicine, New York-Presbyterian Hospital, New York, NY 10065, USA.
Elisabeth O'DwyerDepartment of Radiology, Weill Cornell Medical College, New York, NY 10065, USA.
Juana Martinez ZuloagaDepartment of Radiology, Weill Cornell Medical College, New York, NY 10065, USA.
Kritika SubramanianDepartment of Radiology, Weill Cornell Medical College, New York, NY 10065, USA.
Jim C HuDepartment of Urology, Weill Cornell Medical College, New York, NY 10065, USA.
Yuliya S JhanwarDepartment of Radiology, Weill Cornell Medical College, New York, NY 10065, USA.
Himanshu NagarDepartment of Radiation Oncology, Weill Cornell Medical College, New York, NY 10065, USA.ORCID 0000-0003-2381-6910
Arindam RoyChoudhuryDepartment of Population Health Sciences, Weill Cornell Medical College, New York, NY 10065, USA.
John BabichRatio Therapeutics, Inc., Boston, MA 02210, USA.
Sandra Huicochea CastellanosDepartment of Radiology, Weill Cornell Medical College, New York, NY 10065, USA.
Joseph R OsborneDepartment of Radiology, Weill Cornell Medical College, New York, NY 10065, USA.
Daniel J A MargolisDepartment of Radiology, Weill Cornell Medical College, New York, NY 10065, USA.ORCID 0000-0001-8212-707X

Funding

Disparities in COVID Disease Severity and Outcomes in New York CityUL1TR002384 · NCATS · WEILL MEDICAL COLL OF CORNELL UNIV · PI JULIANNE L IMPERATO-MCGINLEY · 2017 to 2026
$86.2M
NCATS NIH HHS UL1 TR002384
6 · The paper itself

Abstract

backgroundPSMA PET has emerged as a "gold standard" imaging modality for assessing prostate cancer metastases. However, it is not universally available, and this limits its impact. In contrast, whole-body MRI is much more widely available but misses more lesions. This study aims to improve the interpretation of whole-body MRI by comparing false negative scans retrospectively to PSMA PET.

methodsThis study was a retrospective sub-analysis of a prospectively collected database of patients who participated in a clinical trial of PSMA PET/MRI comparing PSMA PET and whole-body MRI from 2018-2021. Subjects whose separately read PSMA PET and MRI diagnostic reports showed discrepancies ("false negative" MRI cases) were selected for sub-analysis. The cases were reviewed by the same attending radiologist who originally read the scans. The radiologist noted specific features on MRI indicating metastatic disease that were initially missed.

resultsOf 263 cases, 38 (14%) met the inclusion criteria and were reviewed. Six classes of mpMRI false negatives were identified: anatomically normal (18, 47%), atypical MRI appearance (6, 16%), mischaracterization (1, 3%), undercall (6, 16%), obscured (4, 11%), and no abnormality on MRI (3, 8%). Considering that the atypical and undercalled cases could have been adjusted in retrospect, and that 4 additional cases had positive lesions to the same extent and 11 further cases had disease confined to the pelvis, only 11 (4%) of the original 263 would have had disease outside of a conventional radiation treatment plan.

conclusionNotably, almost 50% of the cases, including most lymph node metastases, were anatomically normal using standard criteria. This suggests that current anatomic criteria for evaluating prostate cancer lymph node metastases are not ideal, and there is a need for improved criteria. In addition, 32% of cases involved some element of human interpretive error, and, therefore, improving reader training may lead to more accurate results.

Indexed as

cancerMRIPETprostatePSMAwhole-body

Identifiers

PMID38893178
PMCPMC11171071

What OpenQuestion holds

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Registered trials

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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.