Evidence map›Paper›PMID 28948495›Full record

ArticleDigestive diseases and sciences2017

Risk Assessment of Hepatocellular Carcinoma in Patients with Hepatitis C in China and the USA.

Neehar D Parikh, Sherry Fu, Huiying Rao, Ming Yang, Yumeng Li, Corey Powell, Elizabeth Wu, Andy Lin, Baocai Xing, Lai Wei and 1 more

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Digestive diseases and sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. [Chronic hepatitis C: achievement, challenge and strategy to eliminate as a public health threat].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2018
    Article
  10. 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

11 authors at 3 institutions in 2 countries.

Neehar D ParikhDivision of Gastroenterology and Hepatology, University of Michigan Health System, 1500 E Medical Center Dr, Taubman Center SPC 3912, Ann Arbor, MI, USA. ndparikh@med.umich.edu.ORCID 0000-0002-5874-9933
Sherry FuDivision of Gastroenterology and Hepatology, University of Michigan Health System, 1500 E Medical Center Dr, Taubman Center SPC 3912, Ann Arbor, MI, USA.
Huiying RaoPeking University Hepatology Institute, Peking University People's Hospital, Peking University Health Science Center, Beijing, China.
Ming YangPeking University Hepatology Institute, Peking University People's Hospital, Peking University Health Science Center, Beijing, China.
Yumeng LiConsulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor, MI, USA.
Corey PowellConsulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor, MI, USA.
Elizabeth WuDivision of Gastroenterology and Hepatology, University of Michigan Health System, 1500 E Medical Center Dr, Taubman Center SPC 3912, Ann Arbor, MI, USA.
Andy LinThe Molecular and Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA.
Baocai XingPeking University Cancer Hospital, Peking University Health Science Center, Beijing, China.
Lai WeiPeking University Hepatology Institute, Peking University People's Hospital, Peking University Health Science Center, Beijing, China.
Anna S F LokDivision of Gastroenterology and Hepatology, University of Michigan Health System, 1500 E Medical Center Dr, Taubman Center SPC 3912, Ann Arbor, MI, USA.
A. Alfred Taubman Health Care Center · USPeking University · CNUniversity of Michigan · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatitis C (HCV) infection is an increasingly common cause of hepatocellular carcinoma (HCC) in China.

aimsWe aimed to determine differences in demographic and behavioral profiles associated with HCC in HCV+ patients in China and the USA.

methodsConsecutive HCV+ patients were recruited from centers in China and the USA. Clinical data and lifestyle profiles were obtained through standardized questionnaires. Multivariable analysis was conducted to determine factors associated with HCC diagnosis within groups.

resultsWe included 41 HCC patients from China and 71 from the USA, and 931 non-HCC patients in China and 859 in China. Chinese patients with HCC were significantly younger, less likely to be male and to be obese than US patients with HCC (all p < 0.001). Chinese patients with HCC had a significantly lower rate of cirrhosis diagnosis (36.6 vs. 78.9%, p < 0.001); however, they also had a higher rate of hepatitis B core antibody positivity (63.4 vs. 36.8%, p = 0.007). In a multivariable analysis of the entire Chinese cohort, age > 55, male sex, the presence of diabetes, and time from maximum weight were associated with HCC, while tea consumption was associated with a decreased HCC risk (OR 0.37, 95% CI 0.16-0.88). In the US cohort, age > 55, male sex, and cirrhosis were associated with HCC on multivariable analysis.

conclusionsWith the aging Chinese population and increasing rates of diabetes, there will likely be continued increase in the incidence of HCV-related HCC in China. The protective effect of tea consumption on HCC development deserves further validation.

Indexed as

AgedAge FactorsCarcinoma, HepatocellularChinaChi-Square DistributionComorbidityCross-Sectional StudiesFemaleHepatitis C, ChronicHumansLife StyleLiver NeoplasmsMaleMiddle AgedMultivariate AnalysisOdds RatioDiabetesHCCHCVLifestyleTea

Identifiers

PMID28948495
OpenAlexW2758836626

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.