Evidence map›Paper›PMID 36819184›Full record

ArticleEJHaem2023

Investigating and modeling positron emission tomography factors associated with large cell transformation from low-grade lymphomas.

Jean-Pierre Obeid, Susan M Hiniker, Joseph Schroers-Martin, H Henry Guo, Hyunsoo Joshua No, Everett J Moding, Ranjana H Advani, Ash A Alizadeh, Richard T Hoppe, Michael S Binkley

Open access · diamondAbstract read
In one paragraph

Article in EJHaem, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 37% of its field
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 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
  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

10 authors at 2 institutions in 1 country.

Jean-Pierre ObeidDepartment of Radiation Oncology Stanford University School of Medicine Stanford California USA.
Susan M HinikerDepartment of Radiation Oncology Stanford University School of Medicine Stanford California USA.
Joseph Schroers-MartinDepartment of Medicine Division of Oncology, Stanford University School of Medicine Stanford California USA.
H Henry GuoDepartment of Radiology Stanford University School of Medicine Stanford California USA.
Hyunsoo Joshua NoDepartment of Radiation Oncology Stanford University School of Medicine Stanford California USA.ORCID https://orcid.org/0000-0002-4285-5141
Everett J ModingDepartment of Radiation Oncology Stanford University School of Medicine Stanford California USA.
Ranjana H AdvaniDepartment of Medicine Division of Oncology, Stanford University School of Medicine Stanford California USA.
Ash A AlizadehDepartment of Medicine Division of Oncology, Stanford University School of Medicine Stanford California USA.
Richard T HoppeDepartment of Radiation Oncology Stanford University School of Medicine Stanford California USA.
Michael S BinkleyDepartment of Radiation Oncology Stanford University School of Medicine Stanford California USA.ORCID https://orcid.org/0000-0002-5461-2438
Stanford University · USStanford Medicine · US

Funding

Translational Oncology Research Program (Project-005)P30CA124435 · NCI · STANFORD UNIVERSITY · PI Vittorio Sebastiano · 2007 to 2026
$71.4M
NCI NIH HHS P30 CA124435
6 · The paper itself

Abstract

Low-grade lymphomas have a 1%-3% annual risk of transformation to a high-grade histology, and prognostic factors remain undefined. We set to investigate the role of positron emission tomography (PET) metrics in identification of transformation in a retrospective case-control series of patients matched by histology and follow-up time. We measured PET parameters including maximum standard uptake value (SUV-max) and total lesion glycolysis (TLG), and developed a PET feature and lactate dehydrogenase (LDH)-based model to identify transformation status within discovery and validation cohorts. For our discovery cohort, we identified 53 patients with transformation and 53 controls with a similar distribution of follicular lymphoma (FL). Time to transformation and control follow-up time was similar. We observed a significant incremental increase in SUV-max and TLG between control, pretransformation and post-transformation groups (

Indexed as

lymphomasmathematical modelingpet

Identifiers

PMID36819184
PMCPMC9928791
OpenAlexW4310022271

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.