Evidence map›Paper›PMID 31531761›Full record

ArticleHepatology international2019

Clinical and morpho-molecular classifiers for prediction of hepatocellular carcinoma prognosis and recurrence after surgical resection.

Xiuming Zhang, Yanfeng Bai, Lei Xu, Buyi Zhang, Shi Feng, Liming Xu, Han Zhang, Linjie Xu, Pengfei Yang, Tianye Niu and 2 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Hepatology international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

12 authors.

Xiuming ZhangDepartment of Pathology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China.
Yanfeng BaiDepartment of Pathology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China.
Lei XuSir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310020, China.
Buyi ZhangDepartment of Pathology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China.
Shi FengDepartment of Pathology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China.
Liming XuDepartment of Pathology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China.
Han ZhangDepartment of Pathology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China.
Linjie XuDepartment of Pathology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China.
Pengfei YangSir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310020, China.
Tianye NiuSir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310020, China.
Shusen ZhengDivision of Hepatobiliary and Pancreatic Surgery, Department of Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China. shusenzheng@zju.edu.cn.
Jimin LiuDepartment of Pathology and Molecular Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, L8S 4K1, Canada. nliu@haltonhealthcare.com.ORCID http://orcid.org/0000-0003-1145-3999

Funding

National High-tech R&D Program for Young Scientists by the Ministry of Science and Technology of China 2015AA020917National Key Research Plan by the Ministry of Science and Technology of China 2016YFC0104507National Natural Science Foundation of China 81871351the National S&T Major Project 2017ZX10203205Zhejiang Medical and Health Science and Technology Project 2018KY389
6 · The paper itself

Abstract

backgroundApproximately 50% hepatocellular carcinoma (HCC) patients die within 5 year after surgical resection. The present staging systems do not fully allow to accurately predict the HCC prognosis and recurrence. This study aimed to identify clinicopathological characteristics and molecular markers to establish classifiers to predict the 5-year overall survival (OS) and the 3-year recurrence in HCC patients post-operatively.

methodsWe enrolled 647 HCC patients from two institutions, underwent surgical resection and divided the patients into one training and two validation cohorts. Clinicopathologic characteristics and tumor protein expression of 29 biomarkers by immunohistochemical (IHC) analysis were used to develop and validate a prognostic and a recurrent classifier, using the maximum relevance minimum redundancy algorithm jointly with the multivariable regression method.

resultsThe prognostic classifier distinguished HCC patients into high- and low-probability survival groups with significant differences in 5-year OS rate in all three cohorts (training cohort: 57.36% vs. 22.97%; p < 0.0001; internal validation cohort: 61.90% vs. 28.85%; p < 0.0001; independent validation cohort: 64.28% vs. 22.45%; p < 0.0001). The recurrent classifier also demonstrated good discrimination in all three cohorts.

conclusionThis study presented a prognostic classifier and a recurrent classifier using clinicopathologic and IHC characteristics. The developed classifiers stratified HCC patients into high- and low-probability survival or recurrent groups, which can help clinicians judge whether adjuvant therapy is beneficial post-operatively.

Indexed as

Neoplasm StagingAdultAgedAged, 80 and overBiomarkers, TumorCarcinoma, HepatocellularChinaDisease-Free SurvivalFemaleHumansLiver NeoplasmsMaleMiddle AgedNeoplasm Recurrence, LocalPredictive Value of TestsPrognosisBiomarkers, TumorHepatocellular carcinomaImmunomarkersPredicting classifiersPrognosisRecurrence

Identifiers

PMID31531761

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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.