Evidence map›Paper›PMID 35962578›Full record

ArticleThoracic cancer2022

Clinical significance of the combination of preoperative SUVmax and CEA in patients with clinical stage IA lung adenocarcinoma.

Asato Hashinokuchi, Naoki Haratake, Tomoyoshi Takenaka, Kyoto Matsudo, Taichi Nagano, Kenji Watanabe, Keisuke Kosai, Yuka Oku, Yuki Ono, Shinkichi Takamori and 4 more

Open access · goldAbstract read
In one paragraph

Article in Thoracic cancer, 2022. 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
1.4field-weighted citation impact, top 18% of its field
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, 9 citations in OpenAlex.

  1. A PET/CT-based 3D deep learning model for predicting spread through air spaces in stage I lung adenocarcinoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
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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

14 authors at 1 institution in 1 country.

Asato HashinokuchiDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.ORCID 0000-0001-9659-3485
Naoki HaratakeDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Tomoyoshi TakenakaDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Kyoto MatsudoDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Taichi NaganoDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Kenji WatanabeDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Keisuke KosaiDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Yuka OkuDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Yuki OnoDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.ORCID 0000-0003-4403-431X
Shinkichi TakamoriDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Mikihiro KohnoDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Shingo BabaDepartment of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Kousei IshigamiDepartment of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Tomoharu YoshizumiDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Kyushu University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreoperative maximum standardized uptake value (SUVmax) of 2-[18F]-fluoro-2-deoxy-D-glucose positron emission tomography and serum carcinoembryonic antigen (CEA) have been reported as prognostic factors for lung adenocarcinoma. However, the significance of combined SUVmax and CEA in early-stage lung adenocarcinoma is not well known.

methodsWe retrospectively evaluated the relationship between the combination of SUVmax and CEA and the prognosis of 410 patients with clinical stage IA lung adenocarcinoma who underwent resection. The cutoff values for SUVmax and CEA were determined by receiver operating characteristic curve analysis, and patients were categorized into high SC (SUVmax and CEA) group (SUVmax ≥2.96 and CEA ≥5.3), moderate SC group (either SUVmax <2.96 and CEA ≥5.3 or SUVmax ≥2.96 and CEA <5.3) and low SC group (SUVmax <2.96 and CEA <5.3).

resultsKaplan-Meier curve analysis showed that patients with clinical stage IA lung adenocarcinoma in the high SC group had significantly shorter overall survival (OS) and recurrence-free survival (RFS) than the other groups (p = 0.011 and p < 0.0001, respectively). Multivariate analysis showed that high SC was an independent prognostic factor of OS (p = 0.029) and RFS (p < 0.0001).

conclusionsHigh values of SUVmax and CEA were associated with poor OS and RFS in patients with stage IA lung adenocarcinoma. Simultaneous evaluation of SUVmax and CEA may be an effective prognostic marker to determine the optimal treatment strategy of early-stage lung adenocarcinoma.

Indexed as

Adenocarcinoma of LungLung NeoplasmsCarcinoembryonic AntigenFluorodeoxyglucose F18HumansNeoplasm StagingPrognosisRadiopharmaceuticalsRetrospective StudiesCarcinoembryonic AntigenFluorodeoxyglucose F18Radiopharmaceuticalscarcinoembryonic antigen (CEA)lung adenocarcinomastandardized uptake value (SUV)

Identifiers

PMID35962578
PMCPMC9475234
OpenAlexW4291179440

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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.