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Enregistrement W4417004896 · doi:10.1182/blood-2025-8057

The association between neighbourhood walkability and diffuse large B-cell lymphoma: A population-based Study

2025· article· en· W4417004896 sur OpenAlexaffabout
Elliot Smith, Gillian L. Booth, Wing C. Chan, Ning Liu, Mithunan Ravindran, Matthew C. Cheung, Kelvin Chan, Abi Vijenthira, Peter Gozdyra, Ethan Lin, Lee Mozessohn

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueUrban Transport and Accessibility
Établissements canadiensPrincess Margaret Cancer CentreSunnybrook Health Science CentreInstitute for Clinical Evaluative SciencesSt. Michael's HospitalUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésWalkabilityNeighbourhood (mathematics)PopulationDiffuse large B-cell lymphomaIncidence (geometry)Built environmentProxy (statistics)

Résumé

récupéré en direct d'OpenAlex

Abstract Background Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive lymphoma and has shown a significant global rise in incidence. While disease-related characteristics are well-established risk factors for pathogenesis and survival, recent studies suggest that obesity and limited physical activity are associated with worse overall survival. However, there is limited population-level evidence exploring modifiable, patient-related risk factors for DLBCL incidence and survival. Neighbourhood walkability (a measure of the built environment and proxy for physical activity) has been previously linked to reduced rates of obesity-related cancers and other important health outcomes but has not yet been studied in relation to DLBCL diagnosis and survival. Objectives The primary objective of this study was to determine the association between neighbourhood walkability and DLBCL using population-based data. The secondary outcome of this study was to evaluate the impact of neighbourhood walkability on overall survival (OS) amongst patients with DLBCL. Methods This was a population-based study in Ontario, Canada using linked administrative healthcare databases. Adults (≥18 years) with primary or transformed DLBCL who received curative-intent, rituximab-containing chemotherapy from Jan 2005 to Dec 2021 were included. Neighbourhood walkability was assessed using a validated index which includes 4 equally weighted components: residential density, population density, walkable destinations, and street connectivity and was derived from geographic information software (ArcGIS) and categorized into quintiles (Q1: least walkable to Q5: most walkable). A case-control design was used for the primary objective, where DLBCL cases were matched 1:4 to cancer-free controls by age (birth year) and sex, with a 5-year lookback for assessing neighbourhood walkability from the index date (date of first rituximab treatment). Conditional logistic regression was used to assess for the association between neighbourhood walkability and DLBCL diagnosis adjusting for comorbidities and marginalization (Ontario Marginalization Index; OnMarg). The OnMarg consists of 4 dimensions: material resources, racialized and newcomer population, age and labour force, and household and dwellings. A retrospective-cohort design was used for the secondary objective, to compare the 5-year OS among DLBCL cases with neighbourhood walkability determined at the index date. Cox regression explored the association between neighbourhood walkability and OS adjusting for age, sex, income quintile, comorbidities, and Ann Arbor stage. Results For the primary analysis, 6,445 patients with DLBCL (median age 61 years, 46% female) were included and matched to 25,780 cancer-free controls. On univariate analysis, those residing in neighbourhood walkability quintiles Q1-Q3 had a significantly higher proportion of individuals who developed DLBCL ompared to Q5 (OR 1.12, 95% CI 1.04 – 1.20), however, individuals in Q4 did not (OR 1.05, 95% CI 0.96, 1.14). This association remained significant after adjusting for comorbidities and marginalization (OR 1.09, 95% CI 1.01 – 1.17). The overall effect of neighbourhood walkability on the hazard of developing DLBCL was significant (Type III Wald χ² = 10.39, df = 2, p = 0.005).The same association was seen when neighbourhood walkability was determined 10-years prior to index. Within our univariate OS analysis, neighbourhood walkability quintiles Q1-3 had an inferior 5-year OS compared with Q5 (HR 1.11, 95% CI 1.00 –1.23) though this was not significant when adjusting for disease and sociodemographic covariates (HR 0.97, 95% CI 0.87 – 1.09), whereas age (HR 1.35, 95% CI 1.31–1.40), individuals from the lowest income quintile (HR 1.39, 95% CI 1.23–1.58), comorbidities (HR 1.29, 95% CI 1.25 – 1.34), and advanced DLBCL stage (HR 2.91, 95% CI 2.37 – 3.58) were independently associated with inferior 5-year OS. Conclusion In this large population-based study, controlling for other sociodemographic factors, individuals residing in the least walkable neighbourhoods had an increase in DLBCL diagnosis. This suggests a potential association between the built environment, physical activity and DLBCL oncogenesis, however, an association was not observed between neighbourhood walkability and overall survival. Further studies will be directed at investigating associations between neighbourhood walkability and healthcare utilization in patients with DLBCL.

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)0,000
score de la tête « metaresearch » (Gemma)0,001
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 enseignants0,390
Score d'incertitude au seuil0,776

Scores du classifieur distillé par catégorie (deux têtes)

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

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 Opus0,009
Tête enseignante GPT0,270
Écart entre enseignants0,262 · 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

Citations0
Publié2025
Routes d'admission2
Résumé présentoui

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