Evidence map›Paper›PMID 42528814›Full record

ReviewFrontiers in immunology2026

Imaging predictors of response and outcomes after CAR T-cell therapy in lymphoma: from clinical trials to real-world practice.

Woojin Yi, Hyo Jin Lee, Nari Kim, Seongwon Na, Saurabh Pallod, Hyungwoo Cho, Dok Hyun Yoon, Kyung Won Kim

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Woojin Yi *Biomedical Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea.
Hyo Jin Lee *Department of Medical Device and Healthcare, Dongguk University, Seoul, Republic of Korea.
Nari KimDepartment of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Seongwon NaDepartment of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Saurabh PallodDepartment of Imaging, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.
Hyungwoo ChoDepartment of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Dok Hyun YoonDepartment of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Kyung Won KimDepartment of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chimeric antigen receptor (CAR) T-cell therapy has transformed the treatment of relapsed or refractory large B-cell lymphoma, with overall response rates in real-world practice broadly comparable to those in pivotal clinical trials. However, progression-free survival is consistently shorter in real-world cohorts, suggesting that baseline disease characteristics may influence long-term outcomes more than initial treatment sensitivity. This review examines the role of baseline Fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) features as predictors of response and survival after CAR T-cell therapy in lymphoma. We synthesize the evidence on established imaging predictors, including total metabolic tumor volume, extranodal disease distribution and site-specific organ involvement, and bulky disease, and discuss emerging biomarkers such as body composition metrics. Despite a growing body of evidence linking these imaging features to outcomes, clinical adoption has been limited by heterogeneous measurement methodologies, inconsistent definitions, and a lack of prospective validation. We propose practical considerations for structured baseline imaging assessment, including a reporting checklist designed to ensure systematic documentation of the imaging features with demonstrated or emerging prognostic relevance. By moving beyond descriptive staging toward structured, predictive baseline imaging evaluation, radiologists and lymphoma clinicians may improve pretreatment risk stratification and facilitate more informed therapeutic decision-making in the expanding landscape of CAR T-cell therapy.

Indexed as

Immunotherapy, AdoptiveLymphomaPositron Emission Tomography Computed TomographyClinical Trials as TopicHumansPrognosisTreatment Outcomebaseline imagingCAR T-cell therapyextranodal diseaselarge B-cell lymphomaPET/CTresponse predictionstructured reportingtotal metabolic tumor volume

Identifiers

PMID42528814
PMCPMC13415359

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.