Evidence map›Paper›PMID 36875072›Full record

ArticleFrontiers in immunology2023

Repeatability of metabolic tumor burden and lesion glycolysis between clinical readers.

Jung W Choi, Erin A Dean, Hong Lu, Zachary Thompson, Jin Qi, Gabe Krivenko, Michael D Jain, Frederick L Locke, Yoganand Balagurunathan

Abstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. The prognostic utility ofFrontiers in immunology · 2024
    Pooled it
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. 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

9 authors.

Jung W ChoiDepartment of Diagnostic Imaging and Interventional Radiology, H Lee Moffitt Cancer Center, Tampa, FL, United States.
Erin A DeanBlood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
Hong LuCancer Physiology, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
Zachary ThompsonBiostatistics & Bioinformatics, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
Jin QiCancer Physiology, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
Gabe KrivenkoBlood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
Michael D JainBlood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
Frederick L LockeBlood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
Yoganand BalagurunathanMachine Learning, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI Christine O'Connell · 1998 to 2026
$93.5M
NCI NIH HHS P30 CA076292
6 · The paper itself

Abstract

The Metabolic Tumor Volume (MTV) and Tumor Lesion Glycolysis (TLG) has been shown to be independent prognostic predictors for clinical outcome in Diffuse Large B-cell Lymphoma (DLBCL). However, definitions of these measurements have not been standardized, leading to many sources of variation, operator evaluation continues to be one major source. In this study, we propose a reader reproducibility study to evaluate computation of TMV (& TLG) metrics based on differences in lesion delineation. In the first approach, reader manually corrected regional boundaries after automated detection performed across the lesions in a body scan (Reader M using a manual process, or manual). The other reader used a semi-automated method of lesion identification, without any boundary modification (Reader A using a semi- automated process, or auto). Parameters for active lesion were kept the same, derived from standard uptake values (SUVs) over a 41% threshold. We systematically contrasted MTV & TLG differences between expert readers (Reader M & A). We find that MTVs computed by Readers M and A were both concordant between them (concordant correlation coefficient of 0.96) and independently prognostic with a P-value of 0.0001 and 0.0002 respectively for overall survival after treatment. Additionally, we find TLG for these reader approaches showed concordance (CCC of 0.96) and was prognostic for over -all survival (p ≤ 0.0001 for both). In conclusion, the semi-automated approach (Reader A) provides acceptable quantification & prognosis of tumor burden (MTV) and TLG in comparison to expert reader assisted measurement (Reader M) on PET/CT scans.

Indexed as

GlycolysisPositron Emission Tomography Computed TomographyBiological TransportReproducibility of ResultsTumor BurdenCART-therapyimaging in CAR-T therapylymphoma – diagnosismetaboloic tumor burdenreproducible imaging biomarkers

Identifiers

PMID36875072
PMCPMC9975754

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.