Evidence map›Paper›PMID 27590191›Full record

ArticleEuropean radiology2017

The role of

Jeong Won Lee, Ki Hyun Seo, Eun-Seog Kim, Sang Mi Lee

Abstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Molecular imaging usingAnnals of nuclear medicine · 2025
    Trial
  3. [EJNMMI research · 2026
    Article
  4. Article
  5. Article
  6. Multi-Organ metabolic profiling with [European journal of nuclear medicine and molecular imaging · 2025
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  7. 3'-deoxy-3'-EJNMMI research · 2025
    Article
  8. Article
  9. Healthy tissue metabolism assessed by [Scientific reports · 2024
    Article
  10. Article
  11. Article
  12. Prognostic Value of Dual-Time-Point [Journal of personalized medicine · 2022
    Article
  13. Predicting treatment outcomes usingTherapeutic advances in medical oncology · 2022
    Article
  14. Article
  15. Article
  16. Article
  17. [EJNMMI research · 2020
    Article
  18. Disseminated focalTherapeutic advances in hematology · 2020
    Article
  19. Article
  20. 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

4 authors.

Jeong Won LeeDepartment of Nuclear Medicine, Catholic Kwandong University College of Medicine, International St. Mary's Hospital, Incheon, Korea.
Ki Hyun SeoDivision of Pulmonary Medicine, Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, Korea.
Eun-Seog KimDepartment of Radiation Oncology, Soonchunhyang University Cheonan Hospital, Cheonan, Korea.
Sang Mi LeeDepartment of Nuclear Medicine, Soonchunhyang University Cheonan Hospital, 23-20 Byeongmyeong-dong, Dongnam-gu, Cheonan, 330-721, Chungcheongnam-do, Korea. gareen@naver.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to assess the relationship between bone marrow (BM) FDG uptake on PET/CT and serum inflammatory markers and to evaluate the prognostic value of BM FDG uptake for predicting clinical outcomes in non-small cell lung cancer (NSCLC) patients.

methodsOne hundred and six NSCLC patients who underwent FDG PET/CT for staging work-up and received chemoradiotherapy were enrolled. Mean BM FDG uptake (BM SUV) and BM-to-liver uptake ratio (BLR) were measured, along with volumetric parameters of PET/CT. The relationship of BM SUV and BLR with hematologic parameters and serum inflammatory markers was evaluated. Prognostic values of BM SUV and BLR for predicting progression-free survival (PFS) and overall survival (OS) were assessed.

resultsBM SUV and BLR were significantly correlated with white blood cell count and C-reactive protein level. On univariate analysis, BLR was a significant prognostic factor for both PFS and OS. On multivariate analysis, TNM stage and BLR were independent prognostic factors for PFS, and only TNM stage was an independent prognostic factor for OS.

conclusionsIn NSCLC patients, FDG uptake of BM reflects the systemic inflammatory response and can be used as a biomarker to identify patients with poor prognosis. KEY POINTS: • Bone marrow FDG uptake is correlated with serum inflammatory markers. • Bone marrow FDG uptake is an independent prognostic factor for progression-free survival. • Bone marrow FDG uptake can provide information on predicting lung cancer progression.

Indexed as

AdultAgedAged, 80 and overBone MarrowCarcinoma, Non-Small-Cell LungChemoradiotherapyC-Reactive ProteinDisease-Free SurvivalFemaleFluorodeoxyglucose F18HumansLungLung NeoplasmsMaleMiddle AgedPositron Emission Tomography Computed TomographyC-Reactive ProteinFluorodeoxyglucose F18RadiopharmaceuticalsSerum AlbuminBone marrowFDGLung cancerPositron emission tomographyPrognosis

Identifiers

What OpenQuestion holds

Textmetadata
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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.