Evidence map›Paper›PMID 27199512›Full record

ArticleChinese journal of cancer research = Chung-kuo yen cheng yen chiu2016

Risk prediction models for hepatocellular carcinoma in different populations.

Xiao Ma, Yang Yang, Hong Tu, Jing Gao, Yu-Ting Tan, Jia-Li Zheng, Freddie Bray, Yong-Bing Xiang

Open access · greenAbstract read
In one paragraph

Article in Chinese journal of cancer research = Chung-kuo yen cheng yen chiu, 2016. 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
1.7field-weighted citation impact, top 16% 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

5 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Frequency and Outcomes of Abnormal Imaging in Patients With Cirrhosis Enrolled in a Hepatocellular Carcinoma Surveillance Program.Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society · 2019
    Article
  3. Clinicopathological features and surgical outcomes of four rare subtypes of primary liver carcinoma.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2018
    Article
  4. Article
  5. Article
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

8 authors at 5 institutions in 3 countries.

Xiao Ma1State Key Laboratory of Oncogene and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;; 2Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;
Yang Yang1State Key Laboratory of Oncogene and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;; 2Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;
Hong Tu1State Key Laboratory of Oncogene and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;
Jing Gao1State Key Laboratory of Oncogene and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;; 2Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;
Yu-Ting Tan1State Key Laboratory of Oncogene and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;; 2Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;
Jia-Li Zheng3University of South Carolina, Arnold School of Public Health, Department of Epidemiology and Biostatistics, Columbia SC29208, USA;
Freddie Bray4Cancer Surveillance Section, International Agency for Research on Cancer, 150 Cours Albert Thomas, F-69372 Lyon Cedex 08, France.
Yong-Bing Xiang1State Key Laboratory of Oncogene and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;; 2Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;
Renji Hospital · CNShanghai Cancer Institute · CNState Key Laboratory of Oncogene and Related Genes · CNCentre International de Recherche sur le Cancer · FRUniversity of South Carolina · US

Funding

World Health Organization 001
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a malignant disease with limited therapeutic options due to its aggressive progression. It places heavy burden on most low and middle income countries to treat HCC patients. Nowadays accurate HCC risk predictions can help making decisions on the need for HCC surveillance and antiviral therapy. HCC risk prediction models based on major risk factors of HCC are useful and helpful in providing adequate surveillance strategies to individuals who have different risk levels. Several risk prediction models among cohorts of different populations for estimating HCC incidence have been presented recently by using simple, efficient, and ready-to-use parameters. Moreover, using predictive scoring systems to assess HCC development can provide suggestions to improve clinical and public health approaches, making them more cost-effective and effort-effective, for inducing personalized surveillance programs according to risk stratification. In this review, the features of risk prediction models of HCC across different populations were summarized, and the perspectives of HCC risk prediction models were discussed as well.

Indexed as

chronic hepatitis Bchronic hepatitis Ccirrhosiscohort studygeneral populationhepatocellular carcinomarisk factorsRisk prediction models

Identifiers

PMID27199512
PMCPMC4865607
OpenAlexW2404121679

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.