Evidence map›Paper›PMID 27910873›Full record

SynthesisScientific reports2016

An updated dose-response meta-analysis of coffee consumption and liver cancer risk.

Chengbo Yu, Qing Cao, Ping Chen, Shigui Yang, Min Deng, Yugang Wang, Lanjuan Li

Abstract readMeta-Analysis
In one paragraph

Synthesis in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 5 pooled it
–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

15 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Coffee Consumption and Cancer Risk: An Assessment of the Health Implications Based on Recent Knowledge.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2021
    Pooled it
  4. Pooled it
  5. Coffee Consumption and the Risk of Thyroid Cancer: A Systematic Review and Meta-Analysis.International journal of environmental research and public health · 2017
    Pooled it
  6. Article
  7. Review
  8. Review
  9. Article
  10. A Decade of Research on Coffee as an Anticarcinogenic Beverage.Oxidative medicine and cellular longevity · 2021
    Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. 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

7 authors.

Chengbo YuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, 310003, China.
Qing CaoState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, 310003, China.
Ping ChenState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, 310003, China.
Shigui YangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, 310003, China.
Min DengState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, 310003, China.
Yugang WangDepartment of Gastroenterology, Shanghai Tongren Hospital, Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Lanjuan LiState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, 310003, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prospective cohort studies of the relationship between coffee consumption and liver cancer risk have drawn different conclusions. Therefore, a dose-response meta-analysis of prospective cohort studies was performed to disentangle this causal relationship. Prospective cohort studies of the association between coffee consumption and liver cancer risk published prior to Jan 9, 2016 were identified by searching in the PubMed and EMBASE databases. Extracted data were analyzed using a random-effects model. Of the 2892 records identified using the search strategy, a total of twenty cohort studies from ten publications were included in the final meta-analysis. The pooled estimate of relative risk (RR) with 95% confidence interval (CI) for highest vs. non/occasional coffee drinkers was 0.55(0.44-0.67). No evidence of publication bias was observed (p for Egger's test = 0.229). Sensitivity analysis indicated the results were robust. Dose-response analysis revealed a significant linear dose-response relationship between coffee consumption and liver cancer risk (p = 0.36). Subgroup analyses stratified by pre-specified variables (gender, geographic region, and adjusted factors) indicated similar results within individual subgroups. Our meta-analysis suggested that coffee consumption is inversely associated with liver cancer risk.

Indexed as

Carcinoma, HepatocellularCholangiocarcinomaCoffeeFemaleHumansLinear ModelsLiver NeoplasmsMaleProspective StudiesProtective FactorsRisk FactorsCoffee

Identifiers

PMID27910873
PMCPMC5133591

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.