Evidence map›Paper›PMID 34887713›Full record

SynthesisContrast media & molecular imaging2021

Prognostic Value of MTV and TLG of

Weibo Wen, Yongnan Piao, Dongyuan Xu, Xiangdan Li

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Contrast media & molecular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Artificial intelligence for TNM staging in NSCLC: a critical appraisal of segmentation utility in [European journal of nuclear medicine and molecular imaging · 2026
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  4. Review
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  16. The baseline metabolism parameters ofQuantitative imaging in medicine and surgery · 2023
    Article
  17. Article
  18. Article
  19. Article
  20. Prediction value ofFrontiers in oncology · 2022
    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.

Weibo WenDepartment of Nuclear Medicine, Yanbian University Hospital, Yanji 133000, China.ORCID 0000-0003-3404-2738
Yongnan PiaoDepartment of Nuclear Medicine, Yanbian University Hospital, Yanji 133000, China.
Dongyuan XuCenter of Morphological Experiment, Medical College of Yanbian University, Yanji 133000, China.
Xiangdan LiCenter of Morphological Experiment, Medical College of Yanbian University, Yanji 133000, China.ORCID 0000-0001-6726-8819

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The present systematic literature review and meta-analysis focused on examining the significance of total lesion glycolysis (TLG) and metabolic tumor volume (MTV) in predicting the prognosis of stages I/II non-small-cell lung cancer (NSCLC) based on Methods: Electronic databases, including Cochrane Library, PubMed, and EMBASE, were comprehensively searched for retrieving relevant articles published in the English language. Furthermore, the significance of TLG and MTV in prognosis prediction was analyzed by pooled hazard ratios (HRs). Results: This work enrolled eight primary studies with 1292 I/II-stage NSCLC cases. The pooled HR (95% confidence interval [CI]) for the ability of increased TLG to predict progression-free survival (PFS) was 2.02 (1.30-2.13) ( Conclusion: The present work suggests the predictive value of PET/CT among stage I and II NSCLC patients. Our results verified that stage I/II NSCLC cases with increased TLG and MTV had a higher risk of side reactions, and TLG is related to increased mortality risk.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsFluorodeoxyglucose F18GlycolysisHumansPositron Emission Tomography Computed TomographyPrognosisRadiopharmaceuticalsTumor BurdenFluorodeoxyglucose F18Radiopharmaceuticals

Identifiers

PMID34887713
PMCPMC8629622

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.