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Enregistrement W2403295133 · doi:10.1182/blood.v122.21.4273.4273

Follicular Lymphoma In Young Adults: Clinical Characteristics and Early Treatment Outcomes

2013· article· en· W2403295133 sur OpenAlexaff
Shane Gangatharan, John Kuruvilla, Vishal Kukreti, Rodger E. Tiedemann, Mary Gospodarowicz, David Hodgson, A. Sun, Richard Tsang, Manjula Maganti, Melania Pintilie, Michael Crump

Notice bibliographique

RevueBlood · 2013
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensUniversity of TorontoPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineFollicular lymphomaPopulationCancerPediatricsYoung adultTransplantationInternal medicineLymphomaPsychosocialSurgery

Résumé

récupéré en direct d'OpenAlex

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 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 enseignants0,004
Score d'incertitude au seuil0,008

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
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,015
Tête enseignante GPT0,277
Écart entre enseignants0,261 · 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
Publié2013
Routes d'admission1
Résumé présentoui

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