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Record W3211368441 · doi:10.1182/blood-2021-147837

Comparative Analysis of Mature T-Cell and NK/T-Cell Lymphomas in Patients with and without HIV: Results from the NA-Accord and Complete Cohorts

2021· article· en· W3211368441 on OpenAlexaboutno aff
Min Jung Koh, Mwanasha H. Merrill, Min Ji Koh, Robert Stuver, Carolyn D. Alonso, Francine M. Foss, Ángel M. Mayor, M. John Gill, Marta Epeldegui, Edward R. Cachay, Jennifer E. Thorne, Michael J. Silverberg, Michael A. Horberg, Keri N. Atlhoff, Ank E. Nijhawan, Kathleen A. McGinnis, Charles S. Rabkin, Sonia Napravnik, Changyu Shen, Salvia Jain

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLymphomaCohortPopulationInternal medicineDiffuse large B-cell lymphomaOncologyPediatrics

Abstract

fetched live from OpenAlex

Abstract Background: Clinicopathological characteristics and prognosis for patients with HIV (PWH) and T-cell lymphomas (TCLs) in the current antiretroviral therapy (ART) era remains unknown. The primary objective of this study was to determine outcomes of patients with mature T and NK/T-cell lymphomas with and without HIV (PWoH) in North America. A secondary objective was to define variations in the survival of patients with TCLs and AIDS-defining B-cell lymphomas (A-BCLs) in the presence of ART. Methods: The study population included patients from two source populations, the NA-ACCORD (The North American AIDS Cohort Collaboration on Research and Design) and COMPLETE (Comprehensive Oncology Measures for Peripheral T-cell Lymphoma), both of which have been previously described. The NA-ACCORD collaborates with >20 longitudinal cohorts of adults (aged ≥ 18 years) with HIV in the United States and Canada. Within the NA-ACCORD cohort, we included patients with a validated incidental diagnosis of mature T and NK/TCL (n=52) or the most common A-BCLs including Burkitt's lymphoma (n=101), diffuse large B-cell lymphoma (DLBCL, n=500) and primary CNS lymphoma (PCNSL, n=64) between 1996 and 2016. COMPLETE is a prospective, multicenter cohort study of patients with newly diagnosed incidental mature TCLs in the United States between 2010 and 2014. Of the 452 eligible patients, 450 were included for analysis after exclusion of two patients with HIV infection. Patients were followed from diagnosis to the first of death, loss to follow-up or administrative censoring at 5 years. Kaplan-Meier and log-rank tests were used to estimate and compare survival. Results: At the time of TCL diagnosis, PWH were significantly younger than patients without HIV (PWoH) (49 years vs. 60 years respectively; p<0.001). PWH were predominantly men (96% vs. 63%; p<0.001), of white race (64% vs. 77%; p<0.006), with chronic kidney disease (19% vs. 2.2%; p<0.001) and with co-infections such as hepatitis B virus (13% vs. 0.9%; p<0.001) and hepatitis C virus (19% vs. 1.1%; p<0.001). Anaplastic large-cell lymphoma (ALCL, n=26) was the most common histological subtype within PWH relative to peripheral T-cell lymphoma-not otherwise specified (PTCL-NOS, n=143) among PWoH. More than 92% of the patients within the NA-ACCORD cohort were on at least one class of ART during their cohort enrollment period. Median duration of ART prior to lymphoma diagnosis was 2.9 years (0.7-9.4) and comparable for patients with TCLs and A-BCLs. The median time from NA-ACCORD cohort enrollment to lymphoma diagnosis was 2.3 years (IQR: 0.3-5.9 years) for TCLs and comparable for patients with the A-BCL subgroups (2.8 years, IQR: 0.6-7.2 years; p=0.21). At the end of the 5-year follow-up period, the survival probability since TCL diagnosis was markedly lower at 0.32 (95% confidence interval [CI]: 0.21-0.49) among PWH in contrast to 0.45 (95% CI: 0.41-0.51) for PWoH. Specifically, survival probability since ALCL diagnosis was distinctively lower at 0.23 (95% CI: 0.11-0.47) among PWH in contrast to 0.76 (95% CI: 0.66-0.87) for PWoH. Mortality following lymphoma diagnosis was elevated for PWH vs. PWoH even after adjusting for statistically significant baseline clinical characteristics such as age, race, and ALCL status in multivariate analysis (adjusted HR: 1.92; 95% CI: 1.27, 2.91). Among PWH with TCL, CD4 <200 and viral load (VL) >500 (n=10) was associated with a lower survival relative to those with counts >200 and/or VL <500 (n=12, p=0.031). Upon stratification of PWH into different calendar periods based on year of diagnosis (1996-1999 vs. 2000-2009 vs. 2010-2016), we observed an improvement in survival for all subgroups over time. Overall, among PWH, PCNSL had the worst median overall survival (3.8 months, 95% Cl: 2.0-7.2 months) followed by ALCL (10.6 months, 95% Cl: 2.1-33.4 months), DLBCL (15.6 months, 95% CI: 12.7-22.2 months) and Burkitt's lymphoma. Conclusions: Our report based on two large observational cohorts in North America highlights poor outcomes for TCLs among PWH compared to PWoH. In addition, within the PWH group, our study is the first to delineate inferior survival for patients with ALCLs relative to DLBCL and Burkitt's lymphoma accentuating the need for novel therapies. However, the overall prognosis for these lymphomas among PWH has improved in the last two decades, particularly among those with CD4>200, underscoring the impact of early and sustained ART. Disclosures Alonso: Merck: Research Funding. Foss: Kyowa: Honoraria; Acrotech: Honoraria, Speakers Bureau; Seattle Genetics: Honoraria, Speakers Bureau; Mallinckrodt: Honoraria; Daiichi Sankyo: Honoraria; Kura: Honoraria. Jain: Trillium Therapeutics, Inc: Research Funding; Acro Biotech, Inc: Research Funding; Abcuro, Inc: Research Funding.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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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Citations0
Published2021
Admission routes1
Has abstractyes

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