Evidence map›Paper›PMID 39430315›Full record

ArticleTranslational lung cancer research2024

Establishing a predictive model for tumor mutation burden status based on

Zheng Chen, Xueping Chen, Linjun Ju, Yue Li, Wenbo Li, Hua Pang

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PubMed Full text at PMC Publisher
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Article in Translational lung cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
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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

6 authors.

Zheng Chen *Department of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xueping Chen *The Center for Clinical Molecular Medical detection, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Linjun JuDepartment of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yue LiDepartment of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Wenbo LiDepartment of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Hua PangDepartment of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tumor mutation burden (TMB) has emerged as a promising biomarker for immune checkpoint inhibitors (ICI) response, but its detection through whole exome sequencing (WES) is costly and invasive. This study aims to establish a predictive model for TMB using baseline metabolic parameters (MPs) of Methods: A total of 223 NSCLC patients with baseline Results: Two clinical features and two PET parameters were identified through lasso regression and logistic regression analysis including pathology type, cancer antigen 125 (CA125) level, maximum standardized uptake value (SUV Conclusions: In this study, a predictive model combining

Indexed as

18F-fluorodeoxyglucose uptake on positron emission tomography/computed tomography (18F-FDG PET/CT)immune checkpoint inhibitors (ICIs)maximum standardized uptake value (SUVmax)non-small cell lung cancer (NSCLC)tumor mutation burden (TMB)

Identifiers

PMID39430315
PMCPMC11484715

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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.