Survival Outcomes for Plasmablastic Lymphoma: An International, Multicentre Study By the Australasian Lymphoma Alliance
Notice bibliographique
Résumé
Introduction Plasmablastic lymphoma (PBL) is a rare, aggressive large cell lymphoma, first described in 1997. PBL is strongly associated with immunodeficient states, such as HIV infection and solid organ transplantation, but up to one third of cases are reported to occur in immunocompetent patients. The pathogenesis of PBL is incompletely understood, though the oncogenic impact of EBV, in particular in the context of dysregulated immune surveillance, together with acquired abnormalities in the MYC pathway appear to play key roles in many cases. Plasma cell markers such as CD138 and CD38 are typically positive, as well as CD30 in a significant subset. Classical B cell markers such as CD20, CD19 and PAX5 are typically absent. The literature on clinical outcomes in PBL is generally limited to small, single-centre case series. Reports describe an aggressive disease of poor prognosis, with median survival of 8 to 15 months, with one series reporting a longer median survival of 32 months. Methods We retrospectively identified patients diagnosed with PBL between 1999 and 2019 from 16 sites across Australia, the United Kingdom and Canada. Patients aged ≥18 years with confirmed tissue diagnosis of PBL at their local treating centre were included. Factors associated with overall survival (OS) were analysed using Cox regression, stratified by site to account for heterogeneity across sites. Risk time for mortality began on the date of diagnosis and ended on the date of death. Patients who were alive, lost to follow-up or transferred to another centre for care, were censored on the date of last follow-up. Risk factors analysed included age, year of diagnosis, HIV status, MYC rearrangement status, CD30 status, lactate dehydrogenase level, disease stage by Lugano consensus criteria, and bone marrow involvement. Results We identified 197 patients with PBL (Table 1). The median age at diagnosis was 55 years (range 18-95) and there was a male predominance (69%). 37% of patients were HIV positive, 56% were HIV negative and 7% were either not tested or had missing results. Other immunosuppressive risk factors included solid organ transplant, allogeneic stem cell transplant (SCT), and immunosuppressive medication. No immunodeficient state was detected in 44%. Fifty per cent of patients were stage IV at diagnosis. Fifty-four per cent were staged using PET/CT. The median follow-up time from diagnosis was 1.36 years, with the longest follow up out to 18.4 years. There were 87 deaths (44%). For patients receiving first-line treatment with curative intent, the rate of complete remission was 57% (103 of 181 patients). Most patients (53%) received CHOP (cyclophosphamide, doxorubicin, vincristine, prednisolone)-based chemotherapy as first line, and 27% treatment of higher intensity than CHOP. Rituximab was administered to 20% and 10% were exposed to proteasome inhibitors as part of first line therapy. Five percent of patients underwent autologous SCT in first remission, and a further 5% after first relapse or later. The median survival time was 4.8 years, with a 5-year OS of 49% and 10-year OS of 45% (figure 1). In multivariate analysis the only adverse factors associated with OS were bone marrow involvement and stage IV disease. Patients without bone marrow involvement at diagnosis had improved OS, compared to those who did (hazard ratio (HR) 0.36, 95%CI 0.18-0.72, p=0.004) (figure 2). There was an increasing trend for mortality with higher disease stages (p-trend=0.002). The median survival was 14.1 years for stage I, 10.7 years for stage II, 5.1 years for stage III and 1.2 years for stage IV. However, only stage IV disease was independently associated with inferior OS in multivariate analysis (HR 2.93, 95%CI 1.43-6.00, p=0.003) (figure 3). OS did not change depending upon year of diagnosis. Conclusion We report a multinational retrospective cohort of patients diagnosed with PBL and to our knowledge the largest single series of PBL to date. OS was longer than previously published data, particularly in patients with early-stage disease. However, patients with stage IV disease and baseline bone marrow involvement had inferior OS. HIV infection did not affect outcome. These findings suggest that baseline bone marrow biopsy and PET staging are useful prognostic tools. There is also an ongoing need for the evaluation of the predictive value of PET imaging and novel agents in PBL, especially in higher-risk disease. Disclosures Di Ciaccio: Jansen: Honoraria, Other: travel and accomodation grant. Cwynarski:Takeda: Consultancy, Other: Conference/travel support; Roche: Consultancy, Other: Conference/travel support. Burton:Celgene: Honoraria; Leeds Teaching Hospitals NHS Trust: Current Employment; Takeda: Honoraria, Other: Travel Support; BMS: Honoraria; Roche: Honoraria, Other: Travel Support. Kuruvilla:Antengene: Honoraria; Janssen: Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; AbbVie: Consultancy; AstraZeneca Pharmaceuticals LP: Honoraria, Research Funding; Merck: Consultancy, Honoraria; Celgene Corporation: Honoraria; Amgen: Honoraria; TG Therapeutics: Honoraria; Pfizer: Honoraria; Novartis: Honoraria; Bristol-Myers Squibb Company: Consultancy. McKay:Greater Glasgow and Clyde Health Board: Current Employment; Roche, Gilead, Takeda, Janssen: Other: For lectures etc; Roche: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BeiGene: Membership on an entity's Board of Directors or advisory committees; Janssen: Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau; TAKEDA: Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau. Linton:BeiGene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Conference/travel support; Roche: Consultancy, Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Patents & Royalties; Janssen: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); Hartley-Taylor: Honoraria; The Christie NHS Foundation Trust and The University of Manchester: Current Employment. Manos:Bristol-Myers Squibb: Other: Conference sponsorship. Hamad:Abbvie: Honoraria; Novartis: 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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| 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 ».