Evidence mapPaperPMID 42006866Full record

SynthesisFrontiers in medicine2026

Diagnostic accuracy of CT-based radiomics for predicting occult lymph node metastasis in early-stage lung adenocarcinoma: a systematic review and meta-analysis.

Jiarong Huang, Ya Su, Lu Chen, Yuqin Long

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Jiarong Huang *Department of Respiratory and Critical Care Medicine, The Affiliated Dazu's Hospital of Chongqing Medical University, Chongqing, China.
Ya Su *Department of Medical Affairs, The Affiliated Dazu's Hospital of Chongqing Medical University, Chongqing, China.
Lu ChenDepartment of Medical Affairs, The Affiliated Dazu's Hospital of Chongqing Medical University, Chongqing, China.
Yuqin LongDepartment of Respiratory and Critical Care Medicine, The Affiliated Dazu's Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aims to evaluate the diagnostic accuracy of CT-based radiomics for predicting occult lymph node metastasis (OLNM) in early-stage lung adenocarcinoma. Methods: Relevant studies up to December 2025 were systematically searched in the databases of PubMed, Embase, Cochrane Library, and Web of Science. Diagnostic accuracy was assessed by pooled estimates of sensitivity, specificity, likelihood ratios, the diagnostic odds ratio, and the summary receiver operating characteristic curve. Subgroup analyses was then conducted to determine sources of heterogeneity. Results: This study evaluated 10 articles and 6,349 patients. By meta-analysis, CT-based radiomics demonstrated good diagnostic performance for OLNM. The pooled sensitivity and specificity were 0.85 and 0.78 in internal validation cohorts and 0.72 and 0.75 in external validation cohorts, respectively. The area under the summary receiver operating characteristic curve was 0.89 and 0.80 for internal and external validation, respectively. Subgroup analyses of the external validation cohorts suggested possible variation in diagnostic performance according to sample size, CT protocol, and segmentation method. Conclusion: CT-based radiomics shows potential for non-invasive prediction of OLNM in early-stage lung adenocarcinoma. Further multicenter prospective studies with harmonized imaging and radiomics pipelines are needed to confirm its clinical applicability. Systematic review registration: CRD420261299869.

Indexed as

diagnostic accuracylung adenocarcinomameta-analysisoccult lymph node metastasisradiomics

Identifiers

PMID42006866
PMCPMC13083186

What Socratic 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 Socratic graph.