Evidence map›Paper›PMID 30519931›Full record

ArticleEuropean radiology2019

Prognostic value of computed tomography radiomics features in patients with gastric cancer following curative resection.

Wuchao Li, Liwen Zhang, Chong Tian, Hui Song, Mengjie Fang, Chaoen Hu, Yali Zang, Ying Cao, Shiyuan Dai, Fang Wang and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 2 pooled it
–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

39 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  5. A radiomics nomogram for the prediction of overall survival in patients with hepatocellular carcinoma after hepatectomy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2020
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  15. Development and validation of a [European radiology · 2023
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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

13 authors.

Wuchao LiDepartment of Radiology, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Liwen ZhangCAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Chong TianDepartment of Radiology, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Hui SongDepartment of Radiology, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Mengjie FangCAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Chaoen HuCAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Yali ZangCAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Ying CaoGuizhou Provincial Key Laboratory of Intelligent Medical Image Analysis and Precision Diagnosis, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Shiyuan DaiGuizhou Provincial Key Laboratory of Intelligent Medical Image Analysis and Precision Diagnosis, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Fang WangGuizhou Provincial Key Laboratory of Intelligent Medical Image Analysis and Precision Diagnosis, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Di DongCAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Rongpin WangDepartment of Radiology, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China. wangrongpin@126.com.
Jie TianCAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China. tian@ieee.org.ORCID http://orcid.org/0000-0003-0498-0432

Funding

LIVER-SPECIFIC GENE EXPRESSION IN HEPATOMA CELLSF32CA007115 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KILLARY, ANN M · 1985 to 1985
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Beijing Municipal Science and Technology Commission Z171100000117023, Z161100002616022Guizhou Provincial Department of Science and Technology and Guizhou Provincial People's Hospital United Foundation QKHLHZ[2015]7115Guizhou Provincial People's Hospital Doctoral Foundation GZSYBS[2015]02Guizhou Science and Technology Department Key Project QKF[2017]25National Key R&D Program of China 2017YFA0205200National Key R&D Program of China 2017YFC1308700National Key R&D Program of China 2017YFC1309100National Natural Science Foundation of China 61231004National Natural Science Foundation of China 61661010National Natural Science Foundation of China 81227901National Natural Science Foundation of China 81360565National Natural Science Foundation of China 81501616National Natural Science Foundation of China 81527805National Natural Science Foundation of China 81771924Science and Technology Foundation of Guizhou Province QKHJC[2016]1096Science and Technology Service Network Initiative of the Chinese Academy of Sciences KFJ-SW-STS-160Technology and Innovation Foundation for the Returned Overseas Chinese Scholars QRXMZZ(2016)03
6 · The paper itself

Abstract

objectivesThe present study aimed to investigate the clinical prognostic significance of radiomics signature (R-signature) in patients with gastric cancer who had undergone radical resection.

methodsA total of 181 patients with gastric cancer who had undergone radical resection were enrolled in this retrospective study. The association between the R-signature and overall survival (OS) was assessed in the primary cohort and verified in the validation cohort. Furthermore, the performance of a radiomics nomogram integrating the R-signature and significant clinicopathological risk factors was evaluated.

resultsThe R-signature, which consisted of six imaging features, stratified patients with gastric cancer who had undergone radical resection into two prognostic risk groups in both cohorts. The radiomics nomogram incorporating R-signature and significant clinicopathological risk factors (T stage, N stage, and differentiation) exhibited significant prognostic superiority over clinical nomogram and R-signature alone (Harrell concordance index, 0.82 vs 0.71 and 0.82 vs 0.74, respectively, p < 0.001 in both analyses). All calibration curves showed remarkable consistency between predicted and actual survival, and decision curve analysis verified the usefulness of the radiomics nomogram for clinical practice.

conclusionsThe R-signature could be used to stratify patients with gastric cancer following radical resection into high- and low-risk groups. Furthermore, the radiomics nomogram provided better predictive accuracy than other predictive models and might aid clinicians with therapeutic decision-making and patient counseling. KEY POINTS: • Radiomics can stratify the gastric cancer patients following radical resection into high- and low-risk groups. • Radiomics can improve the prognostic value of TNM staging system. • Radiomics may facilitate personalized treatment of gastric cancer patients.

Indexed as

AdultFemaleGastrectomyHumansKaplan-Meier EstimateMaleMiddle AgedNeoplasm StagingNomogramsPrognosisRetrospective StudiesRisk FactorsStomach NeoplasmsTomography, X-Ray ComputedMultidetector computed tomographyStomach neoplasmsSurvival

Identifiers

PMID30519931

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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.