Evidence map›Paper›PMID 37711790›Full record

ArticleQuantitative imaging in medicine and surgery2023

Prognostic impact of highly solid component in early-stage solid lung adenocarcinoma.

Taketo Kato, Shingo Iwano, Yuki Hanamatsu, Masato Nakaguro, Ryo Emoto, Shoji Okado, Keiyu Sato, Osamu Noritake, Keita Nakanishi, Yuka Kadomatsu and 8 more

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

18 authors.

Taketo KatoDepartment of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Shingo IwanoDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Yuki HanamatsuDepartment of Pathology and Translational Research, Gifu University School of Medicine, Gifu, Japan.
Masato NakaguroDepartment of Pathology and Laboratory Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Ryo EmotoDepartment of Biostatistics, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Shoji OkadoDepartment of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Keiyu SatoDepartment of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Osamu NoritakeDepartment of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Keita NakanishiDepartment of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Yuka KadomatsuDepartment of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Harushi UenoDepartment of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Naoki OzekiDepartment of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Shota NakamuraDepartment of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Koichi FukumotoDepartment of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Tamotsu TakeuchiDepartment of Pathology and Translational Research, Gifu University School of Medicine, Gifu, Japan.
Kennosuke KarubeDepartment of Pathology and Laboratory Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Shigeyuki MatsuiDepartment of Biostatistics, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Toyofumi Fengshi Chen-YoshikawaDepartment of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Based on computed tomography (CT) findings of lung cancer, solid nodules have a much worse prognosis than subsolid nodules, even if the nodules are subcentimeter in size. There is, however, no systematic method for determining the prognosis of solid tumors on CT. This study aimed to discover the prognostic factor of early-stage solid lung adenocarcinoma using three-dimensional CT volumetry. Methods: Patients with pathological stage I solid lung adenocarcinoma who underwent complete resection between 2007 and 2012 were selected in this retrospective study. Clinicopathological data and preoperative multidetector CT findings, such as tumor size on the two-dimensional axial image, three-dimensional tumor volume between -600 and 199 HU, and three-dimensional solid volume between 0 and 199 HU, which corresponded to highly solid components, were compared between recurrence and non-recurrence. Furthermore, these radiological values were compared to pathological invasive volume (PIV). Results: During this time, 709 patients had their lung cancer completely removed. From this cohort, 90 patients with pathological stage I solid lung adenocarcinoma were selected. In addition, recurrence was found in 26 patients (28.9%). Although two-dimensional axial image, serum carcinoembryonic antigen (CEA) level, and SUVmax on 18F fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) did not differ statistically between recurrent and non-recurrent patients, three-dimensional tumor and solid tumor volume did. Multivariate analysis indicated that three-dimensional solid tumor volume [hazard ratio: 2.440; 95% confidence interval (CI): 1.110-5.361, P=0.026] and epidermal growth factor receptor (EGFR) mutation (hazard ratio: 4.307; 95% CI: 1.328-13.977, P=0.015) were significantly associated with disease-free survival (DFS). When three-dimensional tumor and solid tumor volume were compared to PIV, three-dimensional solid tumor volume (3,091 mm Conclusions: In patients with early-stage solid lung adenocarcinoma, the measurement of three-dimensional solid tumor volume, which is correlated with PIV, accurately predicted the postoperative outcome.

Indexed as

computed tomography volumetryinvasive volumeprognostic predictionSolid lung cancer

Identifiers

PMID37711790
PMCPMC10498257

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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.