Evidence map›Paper›PMID 35913436›Full record

ArticleCancer2022

Coffee and tea consumption, patient-reported, and clinical outcomes in a longitudinal study of patients with breast cancer.

Davide Soldato, Julie Havas, Tracy E Crane, Daniele Presti, Pietro Lapidari, Nathalie Rassy, Barbara Pistilli, Elise Martin, Lucia Del Mastro, Anne-Laure Martin and 10 more

Registry-linked trialAbstract read
In one paragraph

Article in Cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01993498 (A Prospective Cohort to Investigate Survivorship Issues in Patients With Early Cancer), which is not on this map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 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.

NCT01993498 narecruitingnot on this map

A Prospective Cohort to Investigate Survivorship Issues in Patients With Early Cancer

TypeinterventionalSponsorUNICANCERRan2012 to 2034Enrolled14,750ConditionsBreast Cancer Nos Metastatic Recurrent, Early Lung CancerArmsblood sampling
3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
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

20 authors.

Davide SoldatoMolecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.ORCID 0000-0002-2090-3245
Julie HavasMolecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.
Tracy E CraneSylvester Comprehensive Cancer Center, University of Miami, Miami, Florida, USA.ORCID 0000-0002-4288-134X
Daniele PrestiMolecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.ORCID 0000-0003-4442-6700
Pietro LapidariMolecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.
Nathalie RassyMedical Oncology, Gustave Roussy, Villejuif, France.
Barbara PistilliMedical Oncology, Gustave Roussy, Villejuif, France.ORCID 0000-0002-9184-7199
Elise MartinMolecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.
Lucia Del MastroDepartment of Internal Medicine and Medical Specialties, School of Medicine, University of Genoa, Genoa, Italy.
Anne-Laure MartinUNICANCER, Paris, France.
Alexandra JacquetUNICANCER, Paris, France.
Charles CoutantMedical Oncology, Centre Georges Francois Leclerc, Dijon, France.
Paul CottuMedical Oncology, Institut Curie, Paris, France.
Asma MerimecheMedical Oncology, Centre Alexis Vautrin, Vandoeuvre-les-Nancy, France.
Florence LereboursMedical Oncology, Institut Curie, Saint-Cloud, France.
Olivier TredanMedical Oncology, Centre Léon Bérard, Lyon, France.
Laurence VanlemmensMedical Oncology, Centre Oscar Lambret, Lille, France.
Fabrice AndréMolecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.
Ines Vaz-LuisMolecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.ORCID 0000-0002-7194-2260
Antonio Di MeglioMolecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.ORCID 0000-0002-0233-3189

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigher consumption of coffee and tea has been associated with improved health outcomes in the general population and improved breast cancer (BC) prognosis. This study investigated patterns of coffee and tea consumption and association with patient-reported outcomes (PROs) and clinical outcomes among survivors of BC.

methodsThe authors included survivors of stage I-III BC enrolled in the CANTO cohort (NCT01993498) that provided post-treatment assessment of coffee and tea consumption from years 1 to 4 after diagnosis. Group-based trajectory modeling clustered patients according to daily consumption of coffee and tea. Multivariable mixed models and Cox models examined associations between consumption, PROs and clinical outcomes.

resultsAmong 3788 patients, the authors identified four stable patterns of consumption: "Low" (25.8%), "Moderate" (37.6%), "High" (25.3%), and "Very high" (11.3%), corresponding to <1, 2, 3, and ≥ 4 cups of coffee and/or tea per day. Patients in the "Very high" group (vs. "Low"), were more likely to be younger, smokers, with higher monthly income and education. PROs and survival outcomes were similar across the four groups.

conclusionsOver one in three survivors of BC reported high or very high consumption of coffee and/or tea. The authors found no association between higher consumption of coffee and/or tea, worse PROs and clinical outcomes.

Indexed as

Breast NeoplasmsCoffeeFemaleHumansLongitudinal StudiesPatient Reported Outcome MeasuresProspective StudiesRisk FactorsTeaCoffeeTeabreast cancercoffeepatient-reported outcome measuressurvivorstea

Identifiers

PMID35913436
PMCPMC9541449

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Registered trials

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.