Evidence map›Paper›PMID 40470045›Full record

ArticleFrontiers in medicine2025

Prognostic effect of CD74 and development of a radiomic model for predicting CD74 expression in non-small cell lung cancer.

Yancheng Wang, Zhen Gao, Meng Li, Zhen Feng, Hui Wang

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Yancheng Wang *Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong First Medical University, Jinan, China.
Zhen Gao *Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong First Medical University, Jinan, China.
Meng LiDepartment of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong First Medical University, Jinan, China.
Zhen FengDepartment of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong First Medical University, Jinan, China.
Hui WangDepartment of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong First Medical University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The classical prognostic indicators of lung cancer are no longer sufficient for prognostic stratification and individualized treatment of highly heterogeneous non-small cell lung cancer (NSCLC). This study aimed to establish a radiomics model to predict CD74 expression level in NSCLC patients and to explore its role in the tumor immune response and its prognostic value. Methods: The prediction model was developed based on 122 NSCLC transcriptome samples, including 68 paired enhanced CT and transcriptome samples. Survival analysis, gene set variation analysis, and immune cell infiltration analysis were used to investigate the relationship between CD74 expression and tumor immune response. Logistic regression (LG) and support vector machine (SVM) analysis were used to construct the prediction model. The performance of the model was assessed with respect to its calibration, discrimination, and clinical usefulness. Results: High CD74 expression is an independent prognostic factor for NSCLC and is positively correlated with antigen presentation and processing gene expression and antitumor immune cell infiltration. The radiomics prediction models for CD74 expression demonstrated good predictive performance. The areas under the receiver operating characteristic curves for the LG and SVM radiomics models were 0.778 and 0.729, respectively, in the training set and 0.772 and 0.701, respectively, in the validation set. The calibration and decision curve analysis curves demonstrated good fit and clinical benefit. Conclusion: CD74 expression significantly impacts the prognosis of NSCLC patients. The radiomics model based on contrast-enhanced CT exhibits good performance and clinical practicability in predicting CD74 expression.

Indexed as

CD74machine learningnon-small cell lung cancerprediction modelradiomics

Identifiers

PMID40470045
PMCPMC12133499

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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.