Evidence map›Paper›PMID 41816373›Full record

ArticleJournal of thoracic disease2026

Maximum standardized uptake value significance in clinical stage IB-IIIB non-small cell lung cancer.

Shunsuke Shigefuku, Hiroyuki Ito, Yui Kaburaki, Naoko Shigeta, Ryotaro Matsuyama, Chiaki Kanno, Tetsuya Isaka, Takuya Nagashima, Norihiko Ikeda

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

9 authors.

Shunsuke ShigefukuDepartment of Thoracic Surgery, Kanagawa Cancer Center, Kanagawa, Japan.ORCID https://orcid.org/0000-0002-6116-6376
Hiroyuki ItoDepartment of Thoracic Surgery, Kanagawa Cancer Center, Kanagawa, Japan.
Yui KaburakiDepartment of Thoracic Surgery, Kanagawa Cancer Center, Kanagawa, Japan.
Naoko ShigetaDepartment of Thoracic Surgery, Kanagawa Cancer Center, Kanagawa, Japan.
Ryotaro MatsuyamaDepartment of Thoracic Surgery, Kanagawa Cancer Center, Kanagawa, Japan.
Chiaki KannoDepartment of Thoracic Surgery, Kanagawa Cancer Center, Kanagawa, Japan.
Tetsuya IsakaDepartment of Thoracic Surgery, Kanagawa Cancer Center, Kanagawa, Japan.
Takuya NagashimaDepartment of Thoracic Surgery, Kanagawa Cancer Center, Kanagawa, Japan.
Norihiko IkedaDepartment of Surgery, Tokyo Medical University, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In recent years, the number of treatment options for locally advanced non-small cell lung cancer (NSCLC) has increased, including neoadjuvant therapy. Accurate preoperative evaluation of malignancy can assist in planning of therapeutic strategies for NSCLC. We evaluated whether the maximum standardized uptake value (SUVmax) could serve as a predictive prognostic factor for locally advanced clinical stage IB to IIIB NSCLC. Methods: We enrolled 396 patients with clinical stage IB-IIIB NSCLC who underwent lobectomy at the Kanagawa Cancer Center between January 2012 and December 2021. All patients underwent preoperative positron-emission tomography/computed tomography at our institution. The SUVmax cutoff value was determined using a receiver operating characteristic curve. Recurrence-free survival (RFS) and overall survival (OS) were analyzed using Kaplan-Meier curves and were compared using log-rank tests. Factors associated with RFS and OS were determined using a Cox proportional hazards model. Results: Multivariate analysis demonstrated that the SUVmax of the primary tumor was independently associated with RFS and OS in clinical stage IB to IIIB NSCLC patients. SUVmax could stratify both the RFS and OS of patients, particularly from clinical stage IB to IIB. Furthermore, the rates of pathological upstaging and distant recurrence were higher in patients with resected clinical stage IB to IIIB NSCLC with a high SUVmax (>6.0) than in those with a low SUVmax (≤6.0). Conclusions: The SUVmax of the primary tumor is an important preoperative predictor of prognosis in clinical stage IB to IIIB NSCLC.

Indexed as

locally advanced non-small cell lung cancer (locally advanced NSCLC)maximum standardized uptake value (SUVmax)Non-small cell lung cancer (NSCLC)prognosisupstaging

Identifiers

PMID41816373
PMCPMC12972766

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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.