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Record W3096812044 · doi:10.1182/blood-2020-134972

Survival Outcomes for Plasmablastic Lymphoma: An International, Multicentre Study By the Australasian Lymphoma Alliance

2020· article· en· W3096812044 on OpenAlexaffabout
Pietro R Di Ciaccio, Mark N. Polizzotto, Kate Cwynarski, Cathy Burton, Awachana Jiamsakul, Mark Bower, John Kuruvilla, Silvia Montoto, Pam McKay, Wendy Osborne, Sam Milliken, Kim Linton, Kate Manos, Shireen Kassam, Nicole Wong Doo, Anne-Marie Watson, Pasquale L. Fedele, Costas K. Yannakou, Stewart Hunt, Hanna Renshaw, Nisha Thakrar, Alexandra Smith, Daniel Painter, Alice Maxwell, Qin Liu, Rageshri Dhairyawan, Graeme Ferguson, Keir Pickard, Nada Hamad

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsPlasmablastic lymphomaMedicineContext (archaeology)LymphomaAggressive lymphomaDiffuse large B-cell lymphomaOncologyInternal medicineRituximab

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.292
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations5
Published2020
Admission routes2
Has abstractyes

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