Evidence map›Paper›PMID 32979686›Full record

ArticleTranslational oncology2021

Preoperative prediction of microvascular invasion in non-metastatic hepatocellular carcinoma based on nomogram analysis.

Chihao Zhang, Ran Zhao, Fancheng Chen, Yiming Zhu, Liubo Chen

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.0field-weighted citation impact, top 12% 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

19 citing papers in PubMed, 26 citations in OpenAlex.

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  14. [Research progress of microvascular invasion in hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2022
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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

5 authors at 4 institutions in 1 country.

Chihao ZhangDepartment of General Surgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Baoshan, Shanghai, China.
Ran ZhaoDivision of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
Fancheng ChenZhongshan Hospital, School of Medicine, Fudan University, Shanghai, China.
Yiming ZhuDepartment of General Surgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Baoshan, Shanghai, China. Electronic address: zymamm@163.com.
Liubo ChenCancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, Key Laboratory of Molecular Biology in Medical Sciences, Zhejiang Province, China), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China. Electronic address: liubochen@zju.edu.cn.
Shanghai Ninth People's Hospital · CNShanghai Jiao Tong University · CNZhejiang University · CNZhongshan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe presence of microvascular invasion (MVI) is an unfavorable prognostic factor for hepatocellular carcinoma (HCC). This study aimed to construct a nomogram-based preoperative prediction model of MVI, thereby assisting to preoperatively select proper surgical procedures.

methodsA total of 714 non-metastatic HCC patients undergoing radical hepatectomy were retrospectively selected from Zhongshan Hospital between 2010 and 2018, followed by random assignment into training (N = 520) and validation cohorts (N = 194). Nomogram-based prediction model for MVI risk was constructed by incorporating independent risk factors of MVI presence identified from multivariate backward logistic regression analysis in the training cohort. The performance of nomogram was evaluated by calibration curve and ROC curve. Finally, decision curve analysis (DCA) was used to determine the clinical utility of the nomogram.

resultsIn total, 503 (70.4%) patients presented MVI. Multivariate analysis in the training cohort revealed that age (OR: 0.98), alpha-fetoprotein (≥400 ng/mL) (OR: 2.34), tumor size (>5 cm) (OR: 3.15), cirrhosis (OR: 2.03) and γ-glutamyl transpeptidase (OR: 1.61) were significantly associated with MVI presence. The incorporation of five risk factors into a nomogram-based preoperative estimation of MVI risk demonstrated satisfactory discriminative capacity, with C-index of 0.702 and 0.690 in training and validation cohorts, respectively. Calibration curve showed good agreement between actual and predicted MVI risks. Finally, DCA revealed the clinical utility of the nomogram.

conclusionThe nomogram showed a satisfactory discriminative capacity of MVI risk in HCC patients, and could be used to preoperatively estimate MVI risk, thereby establishing more rational therapeutic strategies.

Identifiers

PMID32979686
PMCPMC7516277
OpenAlexW3088782449

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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.