Evidence map›Paper›PMID 31502013›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2020

New insight on the correlation of metabolic status on

Yang Wang, Ning Zhao, Zhanbo Wu, Na Pan, Xuejie Shen, Ting Liu, Feng Wei, Jian You, Wengui Xu, Xiubao Ren

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In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 2 pooled it
6.4field-weighted citation impact, top 3% 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

65 citing papers in PubMed, 2 syntheses or guidelines pooled it, 94 citations in OpenAlex.

  1. Pooled it
  2. Prognostic value ofFrontiers in immunology · 2022
    Pooled it
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  11. Assessment of tertiary lymphoid structures viaCancer immunology, immunotherapy : CII · 2025
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  13. Metabolic tumor volume onTranslational lung cancer research · 2025
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  15. Comparison ofCancer science · 2025
    Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. Repeated dynamic [European journal of nuclear medicine and molecular imaging · 2024
    Observational

5 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Yang WangDepartment of Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China.
Ning ZhaoNational Clinical Research Center of Cancer, Tianjin, 300060, China.
Zhanbo WuNational Clinical Research Center of Cancer, Tianjin, 300060, China.
Na PanNational Clinical Research Center of Cancer, Tianjin, 300060, China.
Xuejie ShenNational Clinical Research Center of Cancer, Tianjin, 300060, China.
Ting LiuNational Clinical Research Center of Cancer, Tianjin, 300060, China.
Feng WeiNational Clinical Research Center of Cancer, Tianjin, 300060, China.
Jian YouNational Clinical Research Center of Cancer, Tianjin, 300060, China. youjiancn@gmail.com.
Wengui XuNational Clinical Research Center of Cancer, Tianjin, 300060, China. wxu06@tmu.edu.cn.
Xiubao RenDepartment of Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China. renxiubao@tjmuch.com.
National Clinical Research Center for Digestive Diseases · CNTianjin Medical University Cancer Institute and Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetabolic information obtained through

methodsFrom April 2008 to August 2014, 763 patients were enrolled in the analysis to investigate the role of maximum standardized uptake value (SUVmax) in lung cancer. One hundred twenty-two tumor specimens were analyzed by immunohistochemistry (IHC) to intra-tumor immune cells and programmed death protein ligand 1(PD-L1) expression on tumor cells. The correlation between metabolic variables and the expression of tissue immune markers were analyzed.

resultsSUVmax values have significant variations in different epidermal growth factor receptor (EGFR) statuses (wild type vs mutant type), high/low neutrophil-to-lymphocyte ratio (NLR) groups, and high/low platelets-to-lymphocyte ratio (PLR) groups (p < 0.001, p < 0.001, p = 0.003, respectively). SUVmax was an independent prognostic factor in lung cancer patients (p = 0.013). IHC demonstrated a statistically significant correlation between SUVmax and the expression of CD8 tumor-infiltrating lymphocytes (p = 0.015), CD163 tumor-associated macrophages (TAMs) (p = 0.003), and Foxp3-regulatory T cells (Tregs) (p = 0.004), as well as PD-1 and PD-L1 (p = 0.003 and p = 0.012, respectively). With respect to patient outcomes, disease stage, BMI, SUVmax, metabolic tumor volume (MTV), TLG (tumor lesion glycolysis), CD163-TAMs, CD11c-dendritic cells (DCs), PD-L1, and Tregs showed a statistically significant correlation with progression-free survival (PFS) (p < 0.001, 0.023, < 0.001, 0.007, 0.005, 0.004, 0.008, 0.048, and 0.014, respectively), and disease stage, SUVmax, MTV, TLG, CD163-TAMs, CD11c-DCs, and PD-L1 showed a statistically significant correlation with overall survival (OS) (p < 0.001, < 0.001, 0.014, 0.012, < 0.001, 0.001, and < 0.001, respectively).

conclusionThis study revealed an association between metabolic variable and immune cell expression in the tumor microenvironment and suggests that SUVmax on

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsBiomarkersFluorodeoxyglucose F18GlycolysisHumansPositron-Emission TomographyPositron Emission Tomography Computed TomographyPrognosisRetrospective StudiesTumor BurdenTumor MicroenvironmentBiomarkersFluorodeoxyglucose F1818F-FDG PET/CTImmunomarkersNon-small cell lung cancerPrognosisStandardized uptake value

Identifiers

PMID31502013
OpenAlexW2972555250

What OpenQuestion holds

Textmetadata
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.