Evidence map›Paper›PMID 42449615›Full record

ReviewCancers2026

Contemporary Lung Cancer Nodal Staging and Therapeutic Decision-Making in the 9th TNM Era.

Takahiro Nakajima, George A Eapen

Abstract readReview
In one paragraph

Review in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Takahiro NakajimaDepartment of General Thoracic Surgery, Dokkyo Medical University, Mibu 321-0293, Tochigi, Japan.ORCID 0000-0002-4937-5378
George A EapenDepartment of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the era of precision medicine, managing non-small cell lung cancer (NSCLC) requires pathological confirmation, accurate nodal staging, and comprehensive biomarker profiling performed rapidly and concurrently. In the 9th edition of the TNM classification, the N2 category is subdivided into single-station (N2a) and multistation (N2b) subcategories, highlighting the clinical importance of precise mediastinal staging. This refinement necessitates systematic nodal evaluation using minimally invasive modalities such as endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) to appropriately stratify patients for surgery, neoadjuvant therapy, and definitive chemoradiotherapy. Concurrently, although N1 has not been formally subclassified because of the lack of standardized clinical diagnostic criteria, the increasing use of sublobar resection for early-stage NSCLC requires more precise hilar and intrapulmonary nodal assessments, which can potentially be facilitated by emerging technologies such as thin convex-probe EBUS. Concurrently, adequate tissue acquisition is essential for timely biomarker testing. Before administering neoadjuvant immune checkpoint inhibitors, actionable driver alterations, such as epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) rearrangements, must be identified to select appropriate treatment and prevent severe sequential toxicities associated with subsequent targeted therapies. This review highlights the indispensable role of endoscopic nodal staging and multidisciplinary collaboration in adapting to the updated TNM classification and optimizing personalized treatment strategies for patients with NSCLC.

Indexed as

9th edition of the TNM classificationbiomarker testingneoadjuvant treatmentnodal stagingnon-small cell lung cancerpersonalized treatment

Identifiers

PMID42449615
PMCPMC13359463

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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.