Soy Consumption and the Risk of Prostate Cancer in Men: An Updated Systematic Review and Meta‐analysis
Notice bibliographique
Résumé
Background Prostate cancer (PCa) is the third most commonly diagnosed cancer and the sixth most common cause of cancer‐related deaths in the United States. Worldwide, PCa is the second most commonly diagnosed cancer and the fifth leading cause of cancer‐related deaths. PCa incidence is higher in more developed countries, with Australia/New Zealand and North America having the highest rates, while rates remain lowest in Asian countries. The lower incidence of PCa in Asian populations has been associated with the consumption of soy foods. Soy has been under intensifying scrutiny in recent years for its potential role in the prevention of hormone‐driven cancers. The purpose of this study is to provide an updated systematic review and meta‐analysis focused on the association of soy foods on the risk of PCa in men. Methods A systematic review and meta‐analysis to determine the influence of soy food consumption on the risk of PCa in men is currently underway. Eligible studies were published before October 10, 2016 and were identified from PubMed, Web of Science, and the Cochrane Library. Articles were identified using the following key words and their variants: prostate cancer, prostate neoplasm, soy, soymilk, soy milk, isoflavone, bean curd, tofu, soy protein, daidzein, and genistein. For studies to have been included in this meta‐analysis, they must have met the following criteria: (a) evaluated the association between soy food consumption and PCa risk by using randomized control trials and cohort, cross‐sectional, retrospective, prospective, or case‐control studies; (b) methodology was documented in replicable detail; (c) evaluated the relationship between soy and prostate cancer risk; (d) included relative risk ratio with 95% confidence intervals for exposure categories; (e) were written in English; and (f) peer‐reviewed publications or theses. We will utilize a Newcastle‐Ottawa Scale in order to assess the quality of this data. Additionally, data from included articles were utilized for comparisons of highest to lowest consumption, dose‐response relationships, and for potential publication bias. From these comparisons, we will estimate pooled relative risk ratios (RR) and 95% confidence intervals (CI) using random and fixed effects models. Results After screening the literature, a total of 3,309 articles were identified. Eight hundred and thirty‐six articles were immediately removed as duplicates. Of the 2,473 remaining articles, 2,444 were removed through the abstract screening process, and 29 articles were identified for full‐text review. After reviewing the full text, 22 articles met the inclusion criteria and will be analyzed in the meta‐analysis. Significance Data gleaned from this study will result in an updated systematic review and meta‐analysis of the effect of soy consumption on the risk of PCa, providing support or nonsupport for the potential beneficial effect of increased soy food consumption on PCa risk.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,014 | 0,031 |
| Bibliométrie | 0,005 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».