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Enregistrement W2019862164 · doi:10.1111/add.12787

Alcohol and ischaemic heart disease risk—finally moving beyond interpretation of observational epidemiology

2015· editorial· en· W2019862164 sur OpenAlexaff
Michael Roerecke, Jürgen Rehm

Notice bibliographique

RevueAddiction · 2015
Typeeditorial
Langueen
DomaineMedicine
ThématiqueAlcohol Consumption and Health Effects
Établissements canadiensPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
Organismes subventionnairesEuropean Commission
Mots-clésMendelian randomizationObservational studyEpidemiologyDiseaseMedicinePsychologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Studies involving Mendelian randomization appear to be casting doubt on the idea that moderate alcohol consumption is protective against coronary heart disease. However, these studies make certain assumptions that may not be warranted. While the methodology is opening up new possibilities with regard to addressing this important question, there is still much work to do before we can be confident in the conclusions. A recent Mendelian randomization analysis 1 challenged the current view that light to moderate consumption of alcohol is associated causally with lower risk of ischaemic heart disease (IHD 2-6). Mendelian randomization has several advantages: (i) it can be considered as almost experimental, thus being associated with stronger control than usual observational studies in epidemiology 7; (ii) its argumentation relies on more or less drinking among drinkers, only thus avoiding the problems of different types of abstention and their differential risks 8, 9 and their measurement problems 10; and (iii) it deals in part with the measurement problem of single versus multiple observations across the life-time, as it is plausible that the genetic constellation has an impact on alcohol intake at not only one time-point. Furthermore, Holmes and colleagues' study is based on a meta-analysis of several studies, thus avoiding errors linked to specific operationalizations. Figure 1 (based on Roerecke & Rehm 4) shows the typical J-shaped curve found in epidemiological investigations. The logic of Holmes and colleagues 1 is as follows: in area (a), (lower than the nadir), any increase in average consumption is linked to a decrease in IHD risk, and in area (b) (higher than the nadir) the reverse is true and the increase in IHD risk accelerates with increasing alcohol intake. Change in ischaemic heart disease mortality risk by average alcohol intake in men. Source: adapted from Roerecke & Rehm 5 The conclusion of Holmes and colleagues 1 is based on their comparison of alcohol intake and risk of IHD by carriers versus non-carriers of the ADH1B rs1229984 A-allele in different strata of average alcohol intake. This allele is part of the primary pathway of alcohol metabolism 11, and is associated with a flushing response, lower levels of usual alcohol consumption and blood ethanol levels 12. The existence of a protective effect implies that less drinking below the nadir should result in an increase of IHD risk whereas, empirically, allele carriers in that category had lower but not higher IHD risks 1. Unfortunately, there is still some doubt as to whether these assumptions are true. First, several risk factors for IHD were associated with allele status across strata of average alcohol intake 1: i.e. the effect could be mediated by other risk factors than alcohol consumption. Secondly, with respect to mediation of the effect via alcohol consumption, there are at least three dimensions of alcohol shown to impact IHD risk: average volume 3, 4, heavy drinking occasions 16 and regularity versus irregularity of drinking 5, 6, 17. There is a complex interaction between these dimensions, and simply focusing on one dimension may lead to problematic results. Holmes and colleagues showed that carriers had both lower average consumption and a lower probability of binge drinking across studies. This becomes particularly important when looking at light to moderate drinkers below the nadir [area (a)]. Based on current epidemiological evidence 16, ceteris paribus, we would expect carriers among light to moderate drinkers to show lower IHD risk because of the lower probability of binge drinking 16. Thirdly, the described analysis was based on aggregate data 1, and we do not know if the average level of alcohol intake of the allele carriers within the strata of average consumption was indeed lower than that of the non-carriers. In order to increase our confidence in the conclusions of the Mendelian randomization analysis the assumptions should be controlled for, at best with a pooled analysis of the underlying individual data. However, despite the large sample size in Holmes and colleagues' study, there might be problems with statistical power to investigate these limitations thoroughly because allele carriers are rare in many European countries. Mendelian randomization studies in populations with more variation in these genotypes may thus be a useful addition to the evidence base of the association between alcohol intake and IHD risk. Finally, let us add some observations for the wider picture regarding the relationship between alcohol and IHD. Unless new confounders are derived theoretically, repeating cohort analyses on average alcohol intake and IHD incidence is probably of limited value (see Rehm & Roerecke 14 for a listing of major confounders already tested). After more than 100 studies in this area with fairly stable associations we will probably not be able to resolve questions of causality with more descriptive epidemiological studies and by discussing their results 18, 19, but only by new and better designs such as, but not limited to, Mendelian randomization studies or more comprehensive experimental trials on biomarkers. None other than acknowledged above. The research leading to these results has been conducted in the context of the European Community's Seventh Framework Programme under grant agreement no. 266813—Addiction and Lifestyles in Contemporary Europe—Reframing Addictions Project (ALICE RAP). Participant organizations in ALICE RAP can be found at http://www.alicerap.eu/about-alice-rap/partners.html. The views expressed here reflect only the author's and the European Union is not liable for any use that may be made of the information contained therein.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,011
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,252
Score d'incertitude au seuil0,997

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,011
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,095
Tête enseignante GPT0,403
Écart entre enseignants0,308 · 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 tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

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
Publié2015
Routes d'admission1
Résumé présentoui

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