Evidence map›Paper›PMID 36341372›Full record

ArticleFrontiers in immunology2022

Tumor metabolic and secondary lymphoid organ metabolic markers on 18F-fludeoxyglucose positron emission tomography predict prognosis of immune checkpoint inhibitors in advanced lung cancer.

Peng Jin, Menglin Bai, Jie Liu, Jinming Yu, Xue Meng

Abstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Molecular imaging usingAnnals of nuclear medicine · 2025
    Trial
  2. Article
  3. Prognostic value of [BMC medical imaging · 2026
    Article
  4. Prognostic Value ofJournal of clinical medicine · 2026
    Article
  5. Baseline immune-organFrontiers in medicine · 2026
    Article
  6. Article
  7. The regulatory roles and clinical significance of glycolysis in tumor.Cancer communications (London, England) · 2024
    Review
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

5 authors.

Peng JinDepartment of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Menglin BaiDepartment of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Jie LiuDepartment of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Jinming YuDepartment of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Xue MengDepartment of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The purpose of this study was to investigate the predictive value of tumor metabolic parameters in combination with secondary lymphoid metabolic parameters on positron emission tomography (PET)/computed tomography (CT) for immune checkpoint inhibitor (ICI) prognosis in advanced lung cancer. Methods: This study retrospectively included 125 patients who underwent 18F-fludeoxyglucose (FDG) PET/CT before ICI therapy, including 41 patients who underwent a second PET/CT scan during ICI treatment. The measured PET/CT parameters included tumor metabolism parameters [maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), total lesion glycolysis (TLG), and total metabolic tumor volume (TMTV)] and secondary lymphoid organ metabolism parameters [spleen-to-liver SUVmax ratio (SLR) and bone marrow-to-liver SUVmax ratio (BLR)]. The correlation of PET/CT metabolic parameters with early ICI treatment response, progression-free survival (PFS), and overall survival (OS) was analyzed. Results: Within a median follow-up of 28.7 months, there were 44 responders and 81 non-responders. The median PFS was 8.6 months (95% confidence interval (CI): 5.872-11.328), and the median OS was 20.4 months (95% CI: 15.526-25.274). Pretreatment tumor metabolic parameters were not associated with early treatment responses. The high bone marrow metabolism (BLR >1.03) was significantly associated with a shorter PFS (p = 0.008). Patients with a high TMTV (>168 mL) and high spleen metabolism (SLR >1.08) had poor OS (p = 0.019 and p = 0.018, respectively). Among the 41 patients who underwent a second PET/CT scan, the ΔSUVmax was significantly lower (p = 0.01) and the SLR was significantly higher (p = 0.0086) in the responders. Populations with low-risk characteristics (low TMTV, low SLR, and ΔSLR > 0) had the longest survival times. Conclusion: High pretreatment TMTV and SLR are associated with poor OS, and increased spleen metabolism after ICI therapy predicts treatment benefit. This indicates that the combination of tumor and spleen metabolic parameters is a valuable prognostic strategy.

Indexed as

Lung NeoplasmsPositron Emission Tomography Computed TomographyFluorodeoxyglucose F18HumansImmune Checkpoint InhibitorsPositron-Emission TomographyPrognosisRetrospective StudiesFluorodeoxyglucose F18Immune Checkpoint InhibitorsFDG-PET/CTimmune checkpoint inhibitorsmetabolic tumor burdenprognosissecondary lymphoid organs

Identifiers

PMID36341372
PMCPMC9634068

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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.