MétaCan
Menu
Retour à la cohorte
Enregistrement W2153625246 · doi:10.1200/jco.2012.42.5496

NEW and RENEW: Building the Case for Weight Loss in Breast Cancer

2012· letter· en· W2153625246 sur OpenAlexaff
Jennifer A. Ligibel, Pamela J. Goodwin

Notice bibliographique

RevueJournal of Clinical Oncology · 2012
Typeletter
Langueen
DomaineMedicine
ThématiqueCancer Risks and Factors
Établissements canadiensPrincess Margaret Cancer CentreLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineBreast cancerWeight lossObservational studyRandomized controlled trialCancerCalorieObesityWeight changeInternal medicineOncology

Résumé

récupéré en direct d'OpenAlex

Obesity has been linked to poor outcomes in women with early breast cancer. A meta-analysis of 43 studies examining the relationship between weight at the time of breast cancer diagnosis and prognosis in women with early-stage breast cancer demonstrated a 33% increase in the risk of breast cancer–related and overall mortality in obese versus nonobese women. Observational studies have also shown that physical activity, an important mediator of weight maintenance, is associated with better survival in women with early-stage breast cancer. Finally, two large-scale randomized trials testing the impact of dietary modification on cancer outcomes in breast cancer survivors have provided indirect evidence that weight loss after diagnosis could lead to lower rates of recurrence. The WINS (Women’s Interventional Nutrition Study) trial reported a 24% reduction in the risk of recurrence in breast cancer survivors randomly assigned to a low-fat diet group, who decreased dietary fat to 20% of calories and lost an average of 6 lbs, as compared with controls. In contrast, the WHEL (Women’s Healthy Eating and Living) study did not demonstrate a lower risk of recurrence in breast cancer survivors randomly assigned to a low-fat, high fruit and vegetable dietary intervention. Intervention participants in this study did not experience weight loss, and although there were a number of other differences between the studies, the weight change in WINS has been suggested as one potential reason for the difference in the outcomes of the two studies. Despite strong observational evidence that weight and related factors could influence cancer outcomes, there are no data from randomized trials testing the impact of purposeful weight loss after breast cancer diagnosis on the risk of cancer recurrence and mortality. A number of small and moderate-sized weight loss and physical activity intervention studies in breast cancer populations have demonstrated the feasibility of lifestyle change and documented additional beneficial effects on quality of life, fitness, and fatigue. To optimally design more definitive studies, interventions that reliably, cost effectively, and durably change lifestyle behaviors in large groups of breast cancer survivors are needed. Enhanced understanding of the impact of lifestyle change on biologic factors implicated in the lifestylecancer association will guide study design and strengthen the scientific rationale for such studies. Two reports in Journal of Clinical Oncology (JCO) provide crucial information for the development of large-scale trials testing the impact of lifestyle change on disease outcomes in patients with cancer. In the first report, Demark-Wahnefried et al demonstrate the efficacy of a telephone-based lifestyle intervention in effecting long-lasting changes in diet, physical activity, and weight in 641 survivors of colon, prostate, and breast cancers, providing feasibility data for large-scale, distance-based lifestyle interventions among cancer survivors. In the second report, Campbell et al describe the impact of different types of lifestyle interventions on biomarkers linked to breast cancer risk and prognosis in postmenopausal women, providing some of the first data comparing the effect of physical activity and weight loss, with or without a physical activity component, on putative pathways linking lifestyle and breast cancer. The RENEW (Reach Out to Enhance Wellness) study enrolled 641 survivors of breast, prostate, and colon cancers. Key eligibility criteria included age 65, body mass index 25 kg/m, sedentary activity pattern, and cancer diagnosis at least 5 years before enrollment. The study employed a cross-over design; participants were randomly assigned to immediate participation in a 1-year telephoneand print materials–based lifestyle intervention, designed to increase physical activity and improve dietary quality, or to delayed participation after a 1-year control period. The primary end point was change in physical functioning. A previous report demonstrated that intervention-group participants experienced significantly less decline in their functional status, improvements in dietary quality, increased physical activity, and modest weight loss, as compared with control participants. The updated report from the RENEW study shows that favorable changes in physical activity, dietary behaviors, and weight were maintained in the immediate intervention group 1 year after the discontinuation of the lifestyle intervention. Additionally, the delayed intervention group experienced significant changes in physical functioning, weight, dietary quality, and physical activity during their participation in the lifestyle intervention. These data provide key information on the durability of telephone-based lifestyle coaching. However, there are important caveats, including the small proportion of eligible individuals who opted to participate in the study (approximately 6%), the 25% attrition rate at 2 years, and the fact that all study measures, including weight, were selfreported. Despite these caveats, the efficacy of the RENEW intervention is consistent with that of other large-scale trials of distanced-based lifestyle interventions, including the WHEL study, JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 30 NUMBER 19 JULY 1 2012

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)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesIntégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,198
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,004
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 Opus0,116
Tête enseignante GPT0,487
Écart entre enseignants0,371 · 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
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

Citations21
Publié2012
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueJournal of Clinical OncologyMême sujetCancer Risks and FactorsTravaux en français237 207