Evidence map›Paper›PMID 40218258›Full record

ReviewDiagnostics (Basel, Switzerland)2025

Clinical TNM Lung Cancer Staging: A Diagnostic Algorithm with a Pictorial Review.

Ivana Kuhtić, Tinamarel Mandić Paulić, Lucija Kovačević, Sonja Badovinac, Marko Jakopović, Margareta Dobrenić, Maja Hrabak-Paar

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 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. Article
  2. 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

7 authors.

Ivana KuhtićDepartment of Diagnostic and Interventional Radiology, University Hospital Centre Zagreb, 10000 Zagreb, Croatia.
Tinamarel Mandić PaulićDepartment of Diagnostic and Interventional Radiology, University Hospital Centre Zagreb, 10000 Zagreb, Croatia.
Lucija KovačevićDepartment of Diagnostic and Interventional Radiology, University Hospital Centre Zagreb, 10000 Zagreb, Croatia.ORCID 0000-0002-2132-9636
Sonja BadovinacDepartment of Pulmonology, University Hospital Centre Zagreb, 10000 Zagreb, Croatia.ORCID 0000-0002-2761-8615
Marko JakopovićDepartment of Pulmonology, University Hospital Centre Zagreb, 10000 Zagreb, Croatia.ORCID 0000-0002-4815-7512
Margareta DobrenićSchool of Medicine, University of Zagreb, 10000 Zagreb, Croatia.
Maja Hrabak-PaarDepartment of Diagnostic and Interventional Radiology, University Hospital Centre Zagreb, 10000 Zagreb, Croatia.ORCID 0000-0002-0390-8466

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is a prevalent malignant disease with the highest mortality rate among oncological conditions. The assessment of its clinical TNM staging primarily relies on contrast-enhanced computed tomography (CT) of the thorax and proximal abdomen, sometimes with the addition of positron emission tomography/CT scans, mainly for better evaluation of mediastinal lymph node involvement and detection of distant metastases. The purpose of TNM staging is to establish a universal nomenclature for the anatomical extent of lung cancer, facilitating interdisciplinary communication for treatment decisions and research advancements. Recent studies utilizing a large international database and multidisciplinary insights indicate a need to update the TNM classification to enhance the anatomical categorization of lung cancer, ultimately optimizing treatment strategies. The eighth edition of the TNM classification, issued by the International Association for the Study of Lung Cancer (IASLC), transitioned to the ninth edition on 1 January 2025. Key changes include a more detailed classification of the N and M descriptor categories, whereas the T descriptor remains unchanged. Notably, the N2 category will be split into N2a and N2b based on the single-station or multi-station involvement of ipsilateral mediastinal and/or subcarinal lymph nodes, respectively. The M1c category will differentiate between single (M1c1) and multiple (M1c2) organ system involvement for extrathoracic metastases. This review article emphasizes the role of radiologists in implementing the updated TNM classification through CT imaging for correct clinical lung cancer staging and optimal patient management.

Indexed as

computed tomography (CT)International Association for the Study of Lung Cancer (IASLC)lung cancerTNM staging

Identifiers

PMID40218258
PMCPMC11988785

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.