The Role Of Body Mass Index In Survival Outcome For Lymphoma Patients: US Intergroup Experience
Notice bibliographique
Résumé
Abstract Introduction The role of body mass index (BMI) impacting clinical outcome among lymphoma patients is controversial. Two recent studies suggest that increased BMI is associated with significantly improved survival. In this study the association between BMI at study entry and failure-free survival (FFS) and overall survival (OS) was evaluated in three phase III Eastern Cooperative Oncology Group-led trials, among patients with DLBCL (E4494), follicular lymphoma (FL) (E1496) and Hodgkin's lymphoma (HL) (E2496). Patients and Methods 537 patients with DLBCL, 730 patients with HD and 282 patients with FL were included in the analysis. BMI was calculated as weight (kilograms) divided by the square of height (meters), using data at study entry. BMI was analyzed both as continuous and categorical variables (underweight <18.5 kg/m2, normal weight: 18.5 to < 25 kg/ m2, overweight: 25 to < 30 kg/ m2, and obese :≥ 30 kg/ m2).The underweight group was excluded due to low (< 2%) prevalence. Baseline patient and clinical characteristics, treatment received and clinical outcomes were compared across BMI categories. PFS was defined as the time from study entry to relapse, progression, or death. OS was measured from study entry to death of any cause. The log-rank test and Cox regression models was used to check the association. The association between BMI and FFS/OS was also independently assessed among patients treated with rituximab. A sensitivity analysis was performed excluding patients with significant weight loss at baseline. Results Among patients with DLBCL, HL and FL, the median age was 70, 33 and 56; 29%, 29% and 37% were obese and 38%, 27% and 37% were overweight, respectively. Age was significantly different among BMI groups in all three studies. Higher BMI groups tended to have better prognosis at study entry among DLBCL and HL patients. BMI was not associated with clinical outcome, with p-values of 0.89, 0.30 and 0.40 for FFS, and p-values of 0.64, 0.67 and 0.09 for OS, for patients with DLBCL, HL and FL, respectively (Figure 1). In multivariate analysis adjusting for other clinical factors, BMI remains an insignificant predictor for all three histologies (Table 1). When limiting to patients treated with rituximab, the association remains non-significant for both FL patients (p=0.92 for PFS, p=0.36 for OS) and DLBCL patients (Figure 2). A subset analysis of males with DLBCL treated on R-CHOP, which matched the study cohort used in a recent report (Carson et al, 2012), revealed no differences in FFS (p=0.48) or OS (p=0.58) (Figure 2). Sensitivity analysis excluding patients with weight loss at study entry resulted in similar findings. Conclusion BMI was not significantly associated with clinical outcomes among patients with DLBCL, HL or FL, in three prospective phase III clinical trials. The findings contradict some previous reports of similar investigations. Further work is required to understand the observed discrepancies. Disclosures: Horning: Genentech: Employment.
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 | 0,005 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».