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Enregistrement W4392786917 · doi:10.1093/ije/dyae008

Adherence to the World Cancer Research Fund lifestyle recommendations and incidence of prostate cancer in UK Biobank

2024· article· en· W4392786917 sur OpenAlexaff
Ilona Csizmadi, Stephen J. Freedland

Notice bibliographique

RevueInternational Journal of Epidemiology · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueGlobal Cancer Incidence and Screening
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésBiobankMedicineLibrary scienceFamily medicineIncidence (geometry)Prostate cancerEpidemiologyMEDLINEOriginal researchPublic healthCancerGerontologyPolitical scienceInternal medicinePathologyBioinformatics

Résumé

récupéré en direct d'OpenAlex

In their recent analysis of the UK Biobank data, Byrne and colleagues1 reported that adherence to the 2018 World Cancer Research Fund/American Institute of Cancer Research (WCRF/AICR) lifestyle recommendations was associated with an ‘increase’ in the risk of prostate cancer (Figure 2 and Supplementary Table S4, available as Supplementary data at IJE online: hazard ratio, 1.04; 95% CI, 1.01, 1.07). The authors acknowledge that this finding was inconsistent with the majority of earlier studies that found null or inverse associations between lifestyle behaviours and prostate cancer risk.1 They speculate that ‘healthy volunteer bias’ may have played a role in the results—implying that men recruited into the study were healthier at baseline than men in the general population of interest; however, the authors do not elaborate on this point. We believe that detection bias warrants consideration as a potential explanation for the findings, wherein men who were more health conscious, i.e. men who reported greater adherence to WCRF/AICR lifestyle recommendations, were also more likely to seek preventive healthcare measures such as prostate-specific antigen (PSA) testing and hence were more likely to undergo a diagnostic biopsy. Specifically, in prostate cancer, the vast majority of cancers are detected at an asymptomatic stage due to PSA testing. Indeed, the advent of PSA screening in the USA in the late 1980s and early 1990s, despite lacking a well-organized national-level screening programme, nonetheless substantially increased prostate cancer incidence, indicating that the strongest risk factor for a prostate cancer diagnosis is undergoing PSA testing. As such, risk factors that are associated with health-seeking behaviours (e.g., greater adherence to WCRF/AICR lifestyle recommendations) may be linked to increased medical care and subsequently increased prostate cancer detection. This phenomenon makes the study of prostate cancer aetiology particularly challenging. A potential solution to this problem is to study the grade of the cancer at diagnosis. Since PSA testing detects more indolent (i.e. lower-grade cancers), studying the tumour grade can shed some light on the risk factors for aggressive, potentially fatal, prostate cancers. Though there is some inconsistency in the evidence for lifestyle behaviours and risk of high-grade and aggressive prostate cancer subtypes,2 in numerous analyses in which distinctions have been made, compared with non-aggressive prostate cancer control groups, the risk of aggressive prostate cancer has been inversely associated with healthy dietary patterns,3 increased physical activity4 and increased adherence to 2007 WCRF/AICR recommendations.5 Similarly, in studies with control groups comprising men not diagnosed with cancer, the risks of aggressive and/or high-grade prostate cancer have been shown to be inversely associated with healthy lifestyle behaviours and positively associated with diets characterized as unhealthy (e.g. dietary patterns that are hyperinsulinaemic and pro-inflammatory), whereas results for non-aggressive and/or low-grade prostate cancers have been null.6–8 Prostate cancer is known to be a biologically heterogeneous disease and it has been suggested that aetiologies may vary across tumour subtypes with respect to modifiable risk factors. To this end, supportive evidence is also emerging from metabolomic studies that have identified lifestyle-related metabolic profiles associated with aggressive prostate cancers but not less aggressive tumour subtypes.9,10 Unfortunately, in the study by Byrne et al.,1 tumour-grade data were not presented to tease apart such associations. Since the diagnosis of aggressive and high-grade prostate cancer is less likely to be associated with health-seeking behaviour than the diagnosis of ‘overall prostate cancer’, studies that distinguish between tumour subtype are better positioned to report findings related to lifestyle behaviours of greater clinical relevance. Moreover, most indolent low-grade prostate cancers are now managed without active treatment and thus detecting these cancers early does not improve long-term outcomes for patients, but merely presents a burden to the patient, physician and healthcare system. Until all studies are designed to differentiate between prostate cancer clinical subtypes, e.g. indolent vs aggressive cancers, results from observational studies will continue to be difficult to interpret with respect to associations with modifiable lifestyle variables. To conclude, we believe that detection bias rather than healthy volunteer bias played a role in the findings reported by Byrne et al.1 Furthermore, the results do not provide insight into whether a healthy lifestyle is associated with lower (or higher) risk of aggressive potentially fatal prostate cancer and hence should not be considered as evidence for a lack of benefit associated with adherence to WCRF/AICR lifestyle recommendations. I.C. wrote the first draft; I.C. and S.J.F. co-wrote the final version. None. None declared.

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)0,010
score de la tête « metaresearch » (Gemma)0,070
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: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,084
Score d'incertitude au seuil0,167

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0100,070
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,007
Études des sciences et des technologies0,0010,000
Communication savante0,0020,002
Science ouverte0,0010,002
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0080,001

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 Opus0,373
Tête enseignante GPT0,566
Écart entre enseignants0,193 · 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
GenreEmpirique

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
Publié2024
Routes d'admission1
Résumé présentoui

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