Evidence map›Paper›PMID 36313719›Full record

ArticleFrontiers in oncology2022

The staging performance of a modified tumor-node-metastasis staging system incorporated with lymphovascular invasion in patients with esophageal squamous cell carcinoma.

Weitao Zhuang, Hansheng Wu, Rixin Chen, Xiaosong Ben, Shujie Huang, Zihao Zhou, Junhan Wu, Yong Tang, Guibin Qiao

Abstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Weitao ZhuangDepartment of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Hansheng WuDepartment of Thoracic Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Rixin ChenDepartment of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Xiaosong BenDepartment of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Shujie HuangDepartment of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Zihao ZhouDepartment of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Junhan WuDepartment of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Yong TangDepartment of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Guibin QiaoDepartment of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lymphovascular invasion (LVI) is recognized as an unfavorable prognostic factor for many solid tumors. However, its staging value has not been adequately illustrated in esophageal squamous cell carcinoma (ESCC). Methods: The clinicopathologic relevance and prognostic impact of LVI were retrospectively analyzed in 822 patients with surgically treated ESCC. Univariate and multivariate analyses were used to determine the independent prognostic factors. Subgroup analyses stratified by pathological stages, nodal status and invasive depth were conducted using Kaplan-Meier method and log-rank test. Multiple staging models based on overall survival (OS) were constructed using Cox regression and evaluated by Harrell's concordance index (C-index), integrated discrimination improvement (IDI), and net reclassification index (NRI). Results: LVI was detected in 24.6% of ESCC patients, and its prevalence increased with a higher pathological stage (p < 0.001). In multivariate analysis, LVI was found to be an independent prognostic factor for OS [Hazard ratio (HR) = 1.545, 95% CI, 1.201-1.986), and was associated with unfavorable outcomes in stage I to III ESCC, regardless of nodal status and invasive depth. The staging model that incorporated LVI as an independent factor achieved the greatest improvement in accuracy (ΔC-index: 2.9%), and the greatest added value (IDI 2.8%, p < 0.01; NRI 13.7%, p < 0.05) for prediction of OS in ESCC patients. Conclusions: LVI can facilitate further survival stratification in ESCC patients. The adoption of LVI as an independent staging factor in the current cancer staging system should be considered and further validated.

Indexed as

esophageal cancerlymphovascular invasionpathologyprognosisstaging

Identifiers

PMID36313719
PMCPMC9608179

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