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Enregistrement W2152318410 · doi:10.1200/jco.2013.49.0466

To Your Health: How Does the Latest Research on Alcohol and Breast Cancer Inform Clinical Practice?

2013· letter· en· W2152318410 sur OpenAlexaff
Wendy Demark‐Wahnefried, Pamela J. Goodwin

Notice bibliographique

RevueJournal of Clinical Oncology · 2013
Typeletter
Langueen
DomaineMedicine
ThématiqueAlcohol Consumption and Health Effects
Établissements canadiensLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
Organismes subventionnairesNational Cancer InstituteAmerican Cancer Society
Mots-clésMedicineBreast cancerCancerInternal medicineEstrogen receptorEndocrinologyPhysiologyMenopauseOncology

Résumé

récupéré en direct d'OpenAlex

In 1977, a report was published from data collected by the Third National Cancer Survey, which found significant associations between alcohol intake and increased risk of cancers of the oral cavity, larynx, esophagus, colorectum, and unexpectedly, cancer of the breast. Subsequent research and meta-analyses have found that alcohol intake is significantly associated with breast cancer risk, with relative risk (RR) estimates suggesting relative increases in risk that range from 5% to 11% with light drinking (ie, up to one drink or 10 g. of alcohol per day) and 22% to 40% with quantities of two to three drinks per day. The risk of alcohol use appears greater with more recent exposure (ie, later versus early adulthood), and for cancers that are estrogen receptor (ER) positive, and that occur after menopause, although there is no agreement as to whether the source of alcohol (beer, wine, or spirits) is a significant factor or not. Of concern, it has been suggested that hormone replacement therapy (HRT), obesity, and low folate status interact with alcohol intake and further exacerbate risk. Biologically, alcohol is thought to promote breast cancer development through the upregulation of aromatase, with resulting increases in estrogen levels which act on breast tissue either directly or via the ER. Other potential mechanisms may include oxidative stress with enhanced formation of DNA adducts, increased exposure to acetaldehyde, epigenetic changes due to altered methyl transfer, and decreased retinoic acid concentrations associated with a modified cell cycle. Given the centrality of these mechanisms—especially that of estrogen—to the growth of breast cancer, the potential contribution of alcohol intake to breast cancer prognosis has been an area of interest for women diagnosed with breast cancer, and the clinicians who treat them. Questions such as “Does my drinking history predict the course of my disease and overall health?” and “Must I now abstain from alcohol?” are common concerns addressed in the dialogue between patient and provider. The findings of Newcomb et al in the article that accompanies this editorial provide some reassurance that a history of alcohol use before, or after, breast cancer diagnosis does not seem to adversely affect survival. They studied the association of prediagnostic alcohol intake with breast cancer–specific and overall survival in 22,890 patients with breast cancer enrolled onto the Collaborative Women’s Longevity Study; they also examined the association of postdiagnosis intake with outcomes in a subset of 4,881 women who provided information an average of 5.7 years after diagnosis. In analyses adjusting for age, stage, body mass index, smoking, mammography, and several breast cancer risk factors there was evidence of a curvilinear association of preand postdiagnostic alcohol intake with mortality. Compared with nondrinkers, women who were modest alcohol drinkers before breast cancer diagnosis (three to six drinks per week) had a 15% relative reduction in breast cancer–specific mortality while those who consumed up to nine drinks per week had a 25% to 30% relative reduction in death from cardiovascular disease and a 15% to 25% relative reduction in death from any cause. More importantly, because cancer survivors can modify post(but not pre-) diagnosis alcohol consumption, moderate alcohol consumption after diagnosis (one to nine drinks per week) was not significantly associated with death from breast cancer but was associated with 40% to 50% relative reduction in cardiovascular mortality and a 10% to 15% relative reduction in all-cause mortality. These results are consistent with previous findings of Flatt et al, who reported similar reductions in overall mortality (hazard ratio [HR], 0.69; 95% CI, 0.49 to 0.97) among survivors of breast cancer (n 3,088) who regularly consumed alcohol after diagnosis while participating in the Women’s Healthy Eating and Living (WHEL) study. Although an early study by Kwan et al of 1,897 survivors of breast cancer participating in the Life After Cancer Epidemiology (LACE) study also found evidence of cardiovascular benefit for postdiagnosis alcohol consumption, a concern was raised about an elevated risk for breast cancer recurrence (HR, 1.35; 95% CI, 1.00 to 1.83) and breast-cancer specific death (HR, 1.51; 95% CI 1.00 to 2.29) among drinkers. More recent findings in an expanded LACE cohort (n 9,329) identified reduced cardiovascular mortality without increases in either recurrence or in breast cancer–specific mortality among drinkers. Together, these data are reassuring and they lend support to the American Cancer Society (ACS) Guidelines on Nutrition and Physical Activity for Cancer Survivors (Table 1). With the release of the original ACS “Guide for Informed Choices on Nutrition and Physical Activity During and After Cancer Treatment,”; and with subsequent updates, including the most recent “ACS Guidelines on Nutrition and Physical Activity for Cancer Survivors,”; expert panels have carefully considered recommendations related to alcohol consumption. This is a complex task because alcohol is associated with increased risk of several cancers, yet many cancer survivors are at significantly greater risk for cardiovascular JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 31 NUMBER 16 JUNE 1 2013

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,035
score de la tête « metaresearch » (Gemma)0,169
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,035
Score d'incertitude au seuil0,185

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0350,169
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0040,002
Bibliométrie0,0060,007
Études des sciences et des technologies0,0020,005
Communication savante0,0120,014
Science ouverte0,0030,004
Intégrité de la recherche0,0130,014
Charge utile insuffisante (le modèle a refusé de juger)0,0120,008

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,646
Tête enseignante GPT0,672
Écart entre enseignants0,026 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations13
Publié2013
Routes d'admission1
Résumé présentoui

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