Evidence map›Paper›PMID 34268370›Full record

ArticleAnnals of translational medicine2021

An excellent nomogram predicts microvascular invasion that cannot independently stratify outcomes of small hepatocellular carcinoma.

Huanhuan Chong, Peiyun Zhou, Chun Yang, Mengsu Zeng

Open access · diamondAbstract read
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Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 34% 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.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Huanhuan ChongShanghai Institute of Medical Imaging, Shanghai, China.
Peiyun ZhouDepartment of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, and Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China.
Chun YangDepartment of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.
Mengsu ZengShanghai Institute of Medical Imaging, Shanghai, China.
Fudan University · CNShanghai Medical College of Fudan University · CNThe First Affiliated Hospital, Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhether microvascular invasion is a prognosis factor for small hepatocellular carcinoma (sHCC) is controversial, and a preoperatively predictive model based on gadoxetate disodium (Gd-EOB-DTPA) MRI is clinically needed for MVI in sHCC.

methodsBetween March 2012 and September 2020, 455 consecutive patients with pathologically confirmed HCC ≤3 cm who underwent hepatectomy and preoperative Gd-EOB-DTPA MRI were retrospectively enrolled. Univariate and multivariate logistic regression combined with cox regression were conducted to find the confounding factors in the cohorts. Propensity score matching (PSM) was employed to balance the biases between MVI and non-MVI groups. Nomogram with C-index visualized the predictive model of MVI.

resultsMultivariate logistic regression identified that 5 characteristics (AFP, tumor size, tumor margin, peritumoral enhancement, radiologic capsule) were markedly associated with MVI of sHCC and incorporated into the nomogram with excellent predictive performance in the training (AUC/C-index: 0.884/0.874, n=288), validation (AUC/C-index: 0.845/0.828, n=123) and test cohorts (AUC/C-index: 0.903/0.954, n=44). Before PSM, histologic MVI independently affected tumor recurrence (hazard ratio: 1.555, 95% CI: 1.055-2.293, P=0.026). However, due to the confounder of tumor size, there was a significant bias between MVI-positive and MVI-negative groups (propensity score: 0.249±0.105

conclusionsA preoperative model, mainly based on the peritumoral hallmarks of Gd-EOB-DTPA MRI, showed an excellent performance to predict the occurrence of MVI. Nevertheless, MVI was a potential but not an independent risk factor for recurrence and mortality in sHCC ≤3 cm.

Indexed as

Gadoxetate disodiumhepatocellular carcinomamagnetic resonance imagingmicrovascular invasionneoplasm prognosis

Identifiers

PMID34268370
PMCPMC8246205
OpenAlexW3163698594

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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.