Evidence map›Paper›PMID 36313714›Full record

ArticleFrontiers in oncology2022

Combined clinical features and MRI parameters for the prediction of VEGFR2 in hepatocellular carcinoma patients.

Laizhu Zhang, Chunxiao Cheng, Binghua Li, Jun Chen, Jin Peng, Yajuan Cao, Yang Yue, Xiaoli Mai, Decai Yu

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.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 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

9 authors.

Laizhu ZhangHepatobiliary and Pancreatic Center & Liver Transplantation Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.
Chunxiao ChengNanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China.
Binghua LiHepatobiliary and Pancreatic Center & Liver Transplantation Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.
Jun ChenDepartment of Pathology, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.
Jin PengHepatobiliary and Pancreatic Center & Liver Transplantation Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.
Yajuan CaoHepatobiliary and Pancreatic Center & Liver Transplantation Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.
Yang YueHepatobiliary and Pancreatic Center & Liver Transplantation Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.
Xiaoli MaiDepartment of Radiology, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.
Decai YuHepatobiliary and Pancreatic Center & Liver Transplantation Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To develop a prediction model for estimating the expression of vascular endothelial growth factor receptor 2 (VEGFR2) in hepatocellular carcinoma (HCC) patients using clinical features and the contrast-enhanced MRI Liver Imaging Reporting and Data System (LI-RADS). Methods: A total of 206 HCC patients were subjected to preoperative contrast-enhanced MRI, radical resection, and VEGFR2 immunohistochemistry labeling. The intensity of VEGFR2 expression was used to split patients into either the positive group or the negative group. For continuous data, the Mann-Whitney U test was employed, and for categorical variables, the χ2 test was utilized. Results: VEGFR2-positivity was identified in 41.7% (86/206) of the patients. VEGFR2-positive HCCs were confirmed by higher serum alpha-fetoprotein (AFP) levels, larger tumor dimensions (either on MRI or upon final pathology), and a higher LI-RADS score (all p < 0.001). LI-RADS scores and AFP levels were independent predictors for high VEGFR2 expression. These two parameters were used to establish a VEGFR2-positive risk nomogram, which was validated to possess both good discrimination and calibration. The area under the curve was 0.830 (sensitivity 83.6%, specificity 72.5%) and the mean absolute error was 0.021. The threshold probabilities ranged between 0.07 and 0.95, and usage of the model contributed net benefits. Conclusion: A nomogram including clinical features and contrast-enhanced MRI parameters was developed and was demonstrably effective at predicting VEGFR2 expression in HCC patients.

Indexed as

hepatocellular carcinomaLI-RADSnomogramtargeted therapyVEGFR2

Identifiers

PMID36313714
PMCPMC9608502

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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.