Follicular Lymphoma In Young Adults: Clinical Characteristics and Early Treatment Outcomes
Notice bibliographique
Résumé
Abstract Introduction Adolescents and young adults with hematologic malignancies have distinct tumor biology, treatment outcomes and psychosocial consequences from cancer diagnosis and its treatment. Follicular lymphoma (FL) is generally considered to be a disease of the elderly, with a median age at diagnosis of 67 years and 65% of patients 60 years or older. FL is rare among young adults (age<40, YA), and the clinical features, natural history and treatment outcomes have not been well defined in this vulnerable patient population, who have unique life challenges while facing what is often considered an incurable lymphoma. We describe the characteristics and outcomes of a large group of YA with newly diagnosed FL treated at our center and compare them to older patients Methods The Princess Margaret Cancer Centre lymphoma database was interrogated for patients registered with FL between 1995 and 2009. Database and retrospective chart review was undertaken to collect data on FLIPI score at diagnosis, time to first and subsequent second treatments, histologic transformation and overall survival (OS). Outcomes were compared between YA and older patients (age 40-65). The older age group was limited to< 65 years to ensure comparable therapies, and because patients in this age range may be potentially eligible for intensive therapy including stem cell transplantation. Results 410 patients with newly diagnosed FL were identified. Stage at diagnosis: I:34.1%; II: 18.3%, III: 21%, IV: 26.7%; FLIPI score: 0 22.9%, 1: 25.8%, 2: 32.8%, 3: 15%, 4: 2.6%, 5: 1%. Fifty five patients (13.4%) were age< 40 at diagnosis. Median age in the YA cohort was 36 years, and 53 years in the older adults. Chi-square testing showed no difference in sex, stage or FLIPI score at diagnosis between YA and older adults. Initial treatment consisted of observation in 105 patients (25.7%); 11 of those managed expectantly were YA. With median follow-up in the observed group of 7.3 years (range 0.68-14.64), 52.3% required therapy (radiation, chemotherapy or combined modality), with median time to therapy from diagnosis of 22 months. Among all patients eventually treated, intial treatment included chemotherapy alone in 37.4%, radiotherapy in 33.8% and combined modality therapy in 25.6%. The most common chemotherapy regimens were CHOP and CVP, alone or with rituximab. Probability of requiring second treatment following initial radiation or chemotherapy was 54.5% at 2 years. FLIPI score strongly predicted time to second treatment (0=0.0047). Time to second treatment was similar for those initially observed compared to those receiving treatment at time of diagnosis, and for young compared to older adults. For the entire cohort, with median follow-up of 8.1 years (range 0.34-17.75), 5-year OS was 86.9%. On univariable analysis there was a significant difference in survival between YA and older patients: 10-year OS 89.3% v 74.2%, p=0.04. On analysis of lymphoma-specific death, there was lower probability of death in YA at 10 years: 4% compared to 15.3% for older adults, although this was not statistically significant (p=0.088). There was no significant difference in survival for patients initially observed compared to those receiving therapy at diagnosis (10-year OS 82.9% v 74%, respectively, p=0.18). Multivariable analysis demonstrated that FLIPI score at diagnosis and age<40 were significant independent variables predictive of OS. Furthermore, despite lack of significance on univariable analysis, in this model patients managed initially with observation had significantly improved OS compared to patients treated at diagnosis with radiation, chemotherapy or both (HR 2.05, p=0.0223). Histologic transformation occurred in 53 patients, 8 in YA (14.5% of all YA) and 45 in the older cohort (12.7% of all older patients). Conclusions YA with follicular lymphoma present with similar clinical characteristics to older patients, and comparable proportions of patients requiring therapy at diagnosis for symptomatic disease. YA demonstrate improved OS independent of FLIPI score compared to older adults. Whether this reflects competing mortality risks or age-related differences in lymphoma biology warrants further investigation. Disclosures: Kuruvilla: Roche: Honoraria. Kukreti:Millennium Pharmaceuticals: Research Funding; Onyx: Research Funding. Tiedemann:Celgene: Honoraria; Janssen: Honoraria. Crump:Roche: Honoraria; Jansen-Ortho: Honoraria; Celgene: Honoraria; Lundbeck: Honoraria; Novartis: Research Funding; Seattle Genetics: Honoraria.
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 | 0,000 | 0,001 |
| 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 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».