Evidence map›Paper›PMID 34677742›Full record

SynthesisCancer causes & control : CCC2022

Coffee consumption and risk of renal cancer: a meta-analysis of cohort evidence.

Jongeun Rhee, Rachel K Lim, Mark P Purdue

Open access · greenAbstract readMeta-Analysis
In one paragraph

Synthesis in Cancer causes & control : CCC, 2022. 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
1.6field-weighted citation impact, top 17% 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, 14 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. The Epigenetic Effects of Coffee.Molecules (Basel, Switzerland) · 2023
    Review
  8. Review
  9. 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

3 authors at 2 institutions in 1 country.

Jongeun RheeOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
Rachel K LimBrown University, Providence, RI, USA.
Mark P PurdueOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA. mark.purdue@nih.gov.ORCID http://orcid.org/0000-0003-1177-3108
National Cancer Institute · USBrown University · US

Funding

Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

purposeThere is increasing evidence that coffee consumption is related to reduced risks for some cancers, but the evidence for renal cancer is inconclusive. Therefore, we conducted a meta-analysis to summarize the cohort evidence of this relationship.

methodsA literature search was performed in PubMed and Embase through February 2021. Meta-analyses using a random effects model were conducted for reported relative risk estimates (RRs) relating coffee intake and renal cancer incidence or mortality. We also performed a two-stage random effects exposure-response meta-analysis. Between-study heterogeneity was assessed.

resultsIn a meta-analysis of the ten identified cohort studies, we found a summary RR of 0.88 [95% confidence interval (CI) 0.78-0.99] relating the highest vs. the lowest category of coffee intake and renal cancer, with no significant between-study heterogeneity observed (I

conclusionsOur findings from this meta-analysis of the published cohort evidence are suggestive of an inverse association between coffee consumption and renal cancer risk.

Indexed as

CoffeeKidney NeoplasmsCohort StudiesHumansIncidenceRisk FactorsCoffeeCoffeeCohort studyKidney cancerMeta-analysis

Identifiers

PMID34677742
PMCPMC8738141
OpenAlexW3205446847

What OpenQuestion holds

Textmetadata
LicenceTDM
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.