Evidence map›Paper›PMID 40663374›Full record

ReviewThe British journal of radiology2025

Something old something new-introduction to the ninth edition TNM classification of lung cancer.

Daria Kifjak, Rebecca Mura, Natallia Khenkina, Svitlana Pochepnia, Benedikt H Heidinger, Ruxandra-Iulia Milos, Lucian Beer, Helmut Prosch

Abstract readReview
In one paragraph

Review in The British journal of radiology, 2025. 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

8 authors.

Daria KifjakDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0001-8087-4303
Rebecca MuraDepartment of Medicine and Surgery (diMeC), University of Parma, 43125 Parma, Italy.ORCID 0009-0002-0240-1142
Natallia KhenkinaPostgraduate School in Radiodiagnostics, University of Milan, 20122 Milan, Italy.
Svitlana PochepniaDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Benedikt H HeidingerDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Ruxandra-Iulia MilosDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Lucian BeerDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Helmut ProschDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-6119-6364

Funding

Austrian Federal Ministry of Labor and EconomyChristian Doppler Research AssociationNational Foundation for Research, Technology and Development
6 · The paper itself

Abstract

The tumour, node, and metastasis (TNM) classification system is fundamental for describing the anatomical extent of lung cancer, encompassing the primary tumour (T), lymph node involvement (N), and distant metastases (M). It is crucial for patient stratification, treatment planning, and survival prognosis. Clinical staging (cTNM) relies on imaging and physical exams, while pathological staging (pTNM) uses surgical specimens. Advances in tumour biology, imaging, surgery, and treatments necessitate periodic updates to ensure the system reflects current knowledge and practices effectively. The International Association for the Study of Lung Cancer (IASLC), alongside the American Joint Committee on Cancer (AJCC) and Union for International Cancer Control (UICC), updates the system through a global, multidisciplinary approach supported by international data and statistical analysis. The ninth edition of the TNM classification, effective January 1, 2025, introduces revisions to the N and M categories while the T categories remain identical. N2 (ipsilateral mediastinal nodal disease) is now divided into N2a (single lymph node station involvement) and N2b (multiple N2 stations involvement). Similarly, M1c category is split into M1c1 (metastases confined to 1 organ system) and M1c2 (metastases involving multiple organ systems). These updates aim to improve the accuracy and utility of lung cancer staging in clinical practice and research.

Indexed as

Lung NeoplasmsNeoplasm StagingHumansLymphatic Metastasislung cancermetastasesneoplasm staging

Identifiers

PMID40663374
PMCPMC12515044

What OpenQuestion holds

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Registered trials

None linked

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.