Evidence map›Paper›PMID 38024636›Full record

ArticleEJHaem2023

PET-based radiomics signature can predict durable responses to CAR T-cell therapy in patients with large B-cell lymphoma.

Marta Ligero, Marc Simó, Cecilia Carpio, Gloria Iacoboni, Maria Balaguer-Montero, Victor Navarro, Mario Andres Sánchez-Salinas, Sabela Bobillo, Ana Marín-Niebla, Josu Iraola-Truchuelo and 5 more

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 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
3.2field-weighted citation impact, top 7% 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. PD-L1 Immuno-PET Reveals Systemic Effects of Localized Oncolytic Virotherapy in a Mouse Model of Head and Neck Cancer.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026
    Article
  5. Article
  6. Review
  7. Predictive value of maximum tumor dissemination (Dmax) in lymphoma patients treated with CD19-specific CAR T-Cells.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025
    Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Review
  13. Semiquantitative 2-[Frontiers in medicine · 2024
    Review
  14. 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

15 authors at 4 institutions in 2 countries.

Marta LigeroRadiomics Group Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron Barcelona Hospital Campus (VHUH) Barcelona Spain.ORCID https://orcid.org/0000-0001-9824-7316
Marc SimóNuclear Medicine Department Vall d'Hebron University Hospital, Autonomous University of Barcelona Barcelona Spain.
Cecilia CarpioDepartment of Hematology Experimental Hematology, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital Barcelona Barcelona Spain.ORCID https://orcid.org/0000-0001-9346-0134
Gloria IacoboniDepartment of Hematology Experimental Hematology, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital Barcelona Barcelona Spain.
Maria Balaguer-MonteroRadiomics Group Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron Barcelona Hospital Campus (VHUH) Barcelona Spain.
Victor NavarroOncology Data Science (ODysSey) Group Vall d'Hebron Institute of Oncology (VHIO) Barcelona Spain.
Mario Andres Sánchez-SalinasDepartment of Hematology Experimental Hematology, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital Barcelona Barcelona Spain.
Sabela BobilloDepartment of Hematology Experimental Hematology, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital Barcelona Barcelona Spain.
Ana Marín-NieblaDepartment of Hematology Experimental Hematology, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital Barcelona Barcelona Spain.
Josu Iraola-TruchueloDepartment of Hematology Experimental Hematology, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital Barcelona Barcelona Spain.
Pau AbrisquetaDepartment of Hematology Experimental Hematology, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital Barcelona Barcelona Spain.
Roser Sala-LlonchFaculty of Medicine Department of Biomedicine Institute of Neurosciences, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) University of Barcelona Barcelona Spain.
Francesc BoschDepartment of Hematology Experimental Hematology, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital Barcelona Barcelona Spain.
Raquel Perez-LopezRadiomics Group Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron Barcelona Hospital Campus (VHUH) Barcelona Spain.ORCID https://orcid.org/0000-0002-9176-0130
Pere BarbaDepartment of Hematology Experimental Hematology, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital Barcelona Barcelona Spain.
Vall d'Hebron Hospital Universitari · ESHebron University · PSBiomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine · ESVall d'Hebron Institut de Recerca · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chimeric antigen receptor (CAR) T-cell therapy is a promising treatment option for relapsed or refractory (R/R) large B-cell lymphoma (LBCL). However, only a subset of patients will present long-term benefit. In this study, we explored the potential of PET-based radiomics to predict treatment outcomes with the aim of improving patient selection for CAR T-cell therapy. We conducted a single-center study including 93 consecutive R/R LBCL patients who received a CAR T-cell infusion from 2018 to 2021, split in training set (73 patients) and test set (20 patients). Radiomics features were extracted from baseline PET scans and clinical benefit was defined based on median progression-free survival (PFS). Cox regression models including the radiomics signature, conventional PET biomarkers and clinical variables were performed for most relevant outcomes. A radiomics signature including 4 PET-based parameters achieved an AUC = 0.73 for predicting clinical benefit in the test set, outperforming the predictive value of conventional PET biomarkers (total metabolic tumor volume [TMTV]: AUC = 0.66 and maximum standardized uptake value [SUV

Indexed as

CAR T cellsDLBCLnon‐Hodgkin lymphomaPETprogression‐free survivalradiomics

Identifiers

PMID38024636
PMCPMC10660117
OpenAlexW4386640379

What OpenQuestion holds

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LicenceCC BY
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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.