Evidence map›Paper›PMID 37975876›Full record

ArticleEuropean journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery2023

Lack of incremental value of three-dimensional measurement in assessing invasiveness for lung cancer.

Meng-Min Wang, Jia-Qi Li, Shi-Hua Dou, Hong-Ji Li, Zhen-Bin Qiu, Chao Zhang, Xiong-Wen Yang, Jia-Tao Zhang, Xin-Hua Qiu, Hong-Sheng Xie and 8 more

Abstract read
In one paragraph

Article in European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Meng-Min WangGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.ORCID 0000-0002-2136-2348
Jia-Qi LiBioinformatics Division, BNRIST and MOE Key Lab of Bioinformatics, Department of Automation, Tsinghua University, Beijing, China.
Shi-Hua DouDepartment of Thoracic Surgery, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China.
Hong-Ji LiGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Zhen-Bin QiuGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Chao ZhangGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Xiong-Wen YangGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Jia-Tao ZhangGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Xin-Hua QiuGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Hong-Sheng XieDepartment of Thoracic Surgery, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China.
Wen-Fang TangDepartment of Cardiothoracic Surgery, Zhongshan City People's Hospital, Zhongshan, China.
Mei-Ling ChengGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Hong-Hong YanGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Xue-Ning YangGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Yi-Long WuGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Xue-Gong ZhangBioinformatics Division, BNRIST and MOE Key Lab of Bioinformatics, Department of Automation, Tsinghua University, Beijing, China.
Lin YangDepartment of Thoracic Surgery, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China.ORCID 0000-0002-1922-0519
Wen-Zhao ZhongGuangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.ORCID 0000-0003-4302-9332

Funding

Guangdong Basic and Applied Basic Research Foundation 2019B1515130002Guangdong Provincial Key Laboratory of Lung Cancer Translational Medicine 2017B030314120High-level Hospital Construction Project DFJH201801National Natural Science Foundation of China Major Joint Project on Key scientific issues of lung Cancer 82241235
6 · The paper itself

Abstract

objectivesThe aim of this study was to evaluate the performance of consolidation-to-tumour ratio (CTR) and the radiomic models in two- and three-dimensional modalities for assessing radiological invasiveness in early-stage lung adenocarcinoma.

methodsA retrospective analysis was conducted on patients with early-stage lung adenocarcinoma from Guangdong Provincial People's Hospital and Shenzhen People's Hospital. Manual delineation of pulmonary nodules along the boundary was performed on cross-sectional images to extract radiomic features. Clinicopathological characteristics and radiomic signatures were identified in both cohorts. CTR and radiomic score for every patient were calculated. The performance of CTR and radiomic models were tested and validated in the respective cohorts.

resultsA total of 818 patients from Guangdong Provincial People's Hospital were included in the primary cohort, while 474 patients from Shenzhen People's Hospital constituted an independent validation cohort. Both CTR and radiomic score were identified as independent factors for predicting pathological invasiveness. CTR in two- and three-dimensional modalities exhibited comparable results with areas under the receiver operating characteristic curves and were demonstrated in the validation cohort (area under the curve: 0.807 vs 0.826, P = 0.059) Furthermore, both CTR in two- and three-dimensional modalities was able to stratify patients with significant relapse-free survival (P < 0.000 vs P < 0.000) and overall survival (P = 0.003 vs P = 0.001). The radiomic models in two- and three-dimensional modalities demonstrated favourable discrimination and calibration in independent cohorts (P = 0.189).

conclusionsThree-dimensional measurement provides no additional clinical benefit compared to two-dimensional.

Indexed as

Adenocarcinoma of LungLung NeoplasmsHumansNeoplasm Recurrence, LocalRetrospective StudiesTomography, X-Ray ComputedConsolidation-to-tumour ratioEarly-stage lung adenocarcinomaRadiomic modelsSurgery

Identifiers

PMID37975876
PMCPMC10753921

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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.