Evidence map›Paper›PMID 39878903›Full record

SynthesisEuropean radiology2025

Diagnostic accuracy of node-RADS for the detection of lymph node invasion: a systematic review and meta-analysis.

Feng Lu, Yanjun Zhao, Zhongjuan Wang, Ninghan Feng

Abstract readSystematic ReviewMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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

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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

4 authors.

Feng Lu *Department of Radiology, JiangNan University Medical Center, Wuxi, China.
Yanjun Zhao *Department of Radiology, JiangNan University Medical Center, Wuxi, China.
Zhongjuan WangDepartment of Radiology, JiangNan University Medical Center, Wuxi, China.
Ninghan FengDepartment of Urological Surgical, JiangNan University Medical Center, Wuxi, China. ninghan__feng@126.com.ORCID http://orcid.org/0009-0001-0347-3132

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo conduct a meta-analysis assessing the diagnostic performance of the node reporting and data system (Node-RADS) for detecting lymph node (LN) invasion.

methodWe performed a systematic literature search of online scientific publication databases from inception up to July 31, 2024. We used the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) to assess the study quality, and heterogeneity was determined by the Q-test and measured with I

resultsA total of 13 studies involving 1341 participants met the inclusion criteria. Pooled summary estimates of sensitivity, specificity, and area under the curve of HSROC were 0.79 (95% CI: 0.66-0.88), 0.86 (95% CI: 0.80-0.90), and 0.90 (95% CI: 0.87-0.92). Subgroup analysis showed that the pooled sensitivity and specificity for CT were 0.74 (95% CI: 0.63-0.83) and 0.84 (95% CI: 0.74-0.91), whereas for MRI were 0.84 (95% CI: 0.59-0.95) and 0.88 (95% CI: 0.81-0.93), respectively.

conclusionNode-RADS demonstrates the promising potential for the prediction of LN invasion, with high specificity but moderate sensitivity, particularly with optimal cutoff value ≥ 3. Indirect comparisons showed no significant difference between CT and MRI regarding overall diagnostic accuracy. KEY POINTS: Question Since the Node-RADS has been proposed, a number of studies have assessed its diagnostic performance for evaluating LN invasion. Findings Node-RADS demonstrated high specificity but moderate sensitivity, and cutoff ≥ 3 is the optimal threshold; indirect comparison suggested no significant difference between CT and MRI. Clinical relevance This study synthesized currently available evidence on studies of utilizing Node-RADS for assessing LNI in patients with various cancers, providing valuable insights for radiologists for utilizing this new risk scoring system in clinical practice.

Indexed as

Breast NeoplasmsLymphatic MetastasisLymph NodesHumansMagnetic Resonance ImagingNeoplasm InvasivenessSensitivity and SpecificityTomography, X-Ray ComputedClassificationDiagnosisLymph nodesMeta-analysisNeoplasms

Identifiers

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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.