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Improvement in Outcome of Patients with CD30+ HIV-Related Systemic B-Cell Non-Hodgkin’s Lymphoma (NHL) Providing HIV Infection Is Adequately Controlled.

2006· article· en· W2578034297 on OpenAlexaffabout
Hatoon Ezzat, Jonathan Wong, Douglas Filipenko, Linda M. Vickars, Paul F. Galbraith, Charles Li, Kevin Murphy, Joan Montaner, Marianne Harris, Robert S. Hogg, Suzanne Vercauteren, Chantal S. Leger, Leslie Zypchen, Heather A. Leitch

Bibliographic record

VenueBlood · 2006
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsAIDS VancouverBC Cancer AgencyUniversity of British Columbia
Fundersnot available
KeywordsCD30MedicineAnaplastic large-cell lymphomaLymphomaCHOPDiffuse large B-cell lymphomaInternal medicineT-cell lymphomaOncologyRituximabB symptomsPathologyImmunology

Abstract

fetched live from OpenAlex

Abstract Aberrant expression of the cell surface marker CD30 in systemic B-cell HIV-related NHL other than anaplastic large cell lymphoma (ALCL) has been reported. CD30 is a member of the tumor necrosis factor (TNF) family of receptors, and activation of CD30 mediates cell cycle regulation in preclinical models. The outcome of AIDS-related lymphoma (ARL) patients (pts) has improved dramatically in recent years with good control of HIV infection and the ability to intensify chemotherapy appropriate to the lymphoma. To determine whether CD30+ systemic ARL might have different clinical outcome and require a tailored approach to therapy, we performed a retrospective clinical-pathological correlation in pts seen at St. Paul’s Hospital in Vancouver, Canada (SPH) and focused on 39 B-cell lymphoma (BCL) pts since 1992. Clinical and HIV-related data were abstracted by chart review and from the CFE data-base. Stored biopsy material diagnostic of BCL was sectioned and stained for CD30 expression by immunohistochemistry. Median age was 41 (range 20–64) years and 37 pts were male. 16 pts had diffuse large B-cell lymphoma (DLBCL), 17 other B-cell NHL excluding ALCL, and 6 Hodgkin’s Lymphoma (HL); 29 were advanced stage. HIV risk was sexual in 31 and injection drug use (IDU) in 8. Median CD4 at diagnosis was 140 (10–770) cells/ul and 20 pts received HAART. Lymphoma therapy was administered according to era and histology: CHOP-like ± Rituximab (R) n=28; ABVD-like n= 6; CODOX-M/IVAC-R n=1; HAART alone n=1; resection n=1; declined therapy n= 2. 8 pts received added R and 4 added radiation therapy. 20 were CD30+ and 19 CD30−; the only baseline characteristic that differed significantly according to CD30 status was histology p<0.02 (6 of 6 HL were CD30+), no other HIV or lymphoma related characteristics differed by CD30 expression. In a Kaplan-Meier analysis, there was a trend toward improved overall survival (OS) in pts with CD30+ NHL; median survival (MS) was 16.3 (2.7–74.3) months (mo) for CD30+ vs. 5.9 (0–50) mo for CD30− (p<0.09). However, OS for HL was 100% at 11–66 mo vs. 7.2 (2.5–48) mo for DLBCL and 7.4 (0–74.3) mo for other NHL (p<0.04); when HL were removed from the analysis there was no difference in OS according to CD30 status (p<0.09), however progression-free survival (PFS) for all pts was; CD30+, 5.4 (0.8–20) mo and CD30−, 3.9 (0.03–6.2) mo (p<0.05). PFS for pts with a CD4 count at NHL Dx was; CD4<100, 3.3 (0–8.8) mo and CD4 ≤100, 5.9 (2.1–20) mo (p<0.04). PFS by CD4 count and CD30 status were as follows: CD4<100 and CD30+, 3.3 (0.8–8.8) mo; CD4<100 and CD30−, 2.0 (0.03–6.0) mo; CD4 ≤100 and CD30+, 6.7 (5.4–20) mo; CD4 ≤100 and CD30−, 4.5 (2.1–6.2) mo, (p<0.07). In conclusion, in this retrospective analysis, there was a trend toward improved PFS in pts with CD30+ B-cell NHL, particularly in pts with a CD4 count of at least 100. These data suggest that non-ALCL CD30+ NHL patients do not require intensified lymphoma therapy and underscores the importance of adequate control of HIV infection in the outcome of HIV-related lymphoma.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.209
Teacher spread0.204 · 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
Published2006
Admission routes2
Has abstractyes

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