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Enregistrement W2042800122 · doi:10.1002/ijc.23522

Non‐Hodgkin lymphoma and obesity

2008· letter· en· W2042800122 sur OpenAlexaboutno aff
Eleanor V. Willett

Notice bibliographique

RevueInternational Journal of Cancer · 2008
Typeletter
Langueen
DomaineMedicine
ThématiqueCancer Risks and Factors
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLymphomaObesityMedicineLeptinOverweightInternal medicineBody mass indexDiffuse large B-cell lymphomaOncologyCase-control studyAnthropometry

Résumé

récupéré en direct d'OpenAlex

We thank Dr. Kapoor for his interest in our report of non-Hodgkin lymphoma (NHL) and obesity.1 In our article, we examined the risk of NHL associated with obesity across 18 case–control studies which were conducted in USA, Canada, Europe, and Japan. Studies were identified through the InterLymph Consortium and constitute the majority of contemporary case–control studies of lymphoma with anthropometric data. We found increased risks of NHL among overweight and obese persons in some studies whereas in others there was no positive association. Overall, this led us to conclude that there was no consistent effect of obesity on the risk of NHL. We did however, like others, find that the risk of diffuse large B-cell lymphoma was elevated among persons considered morbidly obese (body mass index ≥ 40 kg m−2). Kapoor considers other evidence in support of the hypothesis that obesity confers an increased risk of NHL. Polymorphisms involved in energy homeostasis, and which may also have a role in immune regulation, have been investigated with respect to NHL. As well as the cited article by Skibola et al.,2 we too have examined the role of the genetic variants in the leptin (LEP 19G>A, LEP -2548G>A) and leptin receptor (LEPR 223Q>R) genes,3 and we found no association between these polymorphisms and diffuse large B-cell lymphoma in a large UK case–control study. Moreover, there seemed to be little relationship between obesity, the leptin polymorphisms and the risk of diffuse large B-cell lymphoma. Another proposed explanation in support of a relationship between NHL and obesity involved lipoproteins. In particular, Kapoor refers to levels of high-density lipoprotein cholesterol (HDL-C), which are low in obese persons but can also be altered by chronic inflammation. Following observations by others that NHL patients have low circulating levels of HDL-C, Lim and colleagues4 conducted a prospective cohort study to examine the lipoprotein's role in lymphomagenesis. A protective association with high levels of HDL-C was reported within the first 10 years of follow-up, but no association was found with thereafter. As such, the authors suggested that the relationship between NHL and HDL-C may not be causal, and could be a consequence of underlying chronic immune stimulation arising from, for instance, chronic inflammatory conditions or autoimmune diseases. Although the associations between obesity and other illnesses and some cancers are well-established, the relationship with NHL is unclear. As stated in our article,1 many studies show an effect but several have not. Our meta-analysis was based on individual data from—to the best of our knowledge—all but one5 of the current case–control studies of lymphoma with anthropometric information. We found that our study-specific risk estimates demonstrated some quite marked heterogeneity. Heterogeneous risks are found too across recently published prospective cohort studies (Fig. 1). Our self-reported anthropometric data were collected retrospectively and could be biased by participation and reporting but in contrast to the data presented in Figure 1, are unaffected by publication bias. Taken as a whole, the interpretation of the findings on this topic are not straightforward. Given that associations between NHL and obesity are typically not strong, it seems reasonable to conclude that studying other factors (some of which may be related to anthropometry) may prove more informative. Published risks of non-Hodgkin lymphoma associated with obesity from prospective cohort studies. Obesity was defined as a body mass index of 30 kg m−2 in most studies except: the cut point for the most obese persons was 27 kg m−2 in Oh et al. (2005); 28 kg m−2 and 26 kg m−2 for men and women respectively in Chiu et al. (2006); 35 kg m−2 in Lim et al. (2007) and Calle et al. (2003); and 40 kg m−2 for women only in Engeland et al. (2006). Risk estimates were published for men (M), women (F) or both (M&F). [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.] Yours sincerely, Eleanor V. Willett. Eleanor V. Willett*, * Epidemiology and Genetics Unit, Department of Health Sciences, University of York, YO10 5DD, United Kingdom.

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)0,001
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,020

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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 Opus0,017
Tête enseignante GPT0,321
Écart entre enseignants0,304 · 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'étudeObservationnel
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

Citations1
Publié2008
Routes d'admission1
Résumé présentoui

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