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Prognostic Factors in Patients with HIV-Associated Hodgkin Lymphoma: An Analysis of 199 Cases

2012· article· en· W2979981237 on OpenAlexaffabout
Michael Furman, Jeremy S. Abramson, Brady Beltrán, Michele Bibas, Mark Bower, Jaime A. Collins, Joseph M. Connors, Kate Cwynarski, Minh-Li Nguyen, Josep‐María Ribera, Paula Yurie Tanaka, Julie M. Vose, Jorge J. Castillo

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsABVDMedicineInternal medicineDacarbazineVinblastineUnivariate analysisLymphomaHodgkin's lymphomaHodgkin lymphomaIncidence (geometry)Multivariate analysisGastroenterologyOncologyChemotherapyVincristineCyclophosphamide

Abstract

fetched live from OpenAlex

Abstract Abstract 1528 Background: Hodgkin Lymphoma (HL) accounts for approximately 15% of all lymphomas. The incidence of HL is increased in HIV infection. The International Prognostic Score (IPS) is the most commonly used tool to risk-stratify patients with advanced HL but it has not been validated in HIV-associated HL (HIV-HL). We conducted a retrospective study to describe characteristics and evaluate the IPS and other prognostic factors for survival in HIV-HL. Methods: Institutions in the United States (US) and internationally submitted clinical and pathological patient-level data on HIV-positive individuals with a pathological diagnosis of HL who were treated concurrently with doxorubicin, bleomycin, vinblastine and dacarbazine (ABVD) and highly-active antiretroviral therapy (HAART). Continuous and categorical variables are presented using descriptive statistics. Univariate and multivariate analyses were performed for progression-free survival (PFS) and overall survival (OS). P-values <0.05 were considered statistically significant. Results: Data on 199 patients were obtained from 12 institutions; 148 cases (74%) were from Europe, 28 (14%) from North America (US, Canada), and 23 (12%) from South America. All patients were diagnosed between 1996 and 2010. The most common subtype was mixed cellularity (51%). Median age at diagnosis of HL was 42 years (range: 22–73 years), and 87% (n=184) were men. Median CD4+ count was 245 cells/mm3 (range: 4–1209 cells/mm3), and 51% (n=98) had a CD4+ count <200 cells/mm3. Median duration of HIV infection prior to HL diagnosis was 7 years (range: 0–30 years). In 24 patients (12%) HIV and HL were diagnosed concurrently, and 49% (n=95) had a previous diagnosis of AIDS. At presentation, 86% (n=170) of patients exhibited B symptoms, 56% (n=111) presented with stage IV disease, 79% (n=127) had albumin level <4 g/dl, 43% (n=74) had hemoglobin level <10.5 g/dl, 1% (n=1) had WBC >15,000 cells/mm3, 26% (n=44) had lymphocyte count <600 cells/mm3, and 41% (n=68) of patients had an IPS >3. All patients received concurrent HAART and ABVD chemotherapy, opportunistic infection prophylaxis was used in 89% (n=146), and 71% (n=128) received G-CSF therapy. Complete response (CR) was obtained in 82% (n=159) of patients. After a median follow-up of 5 years, the 5-year PFS and OS were 75% and 78%, respectively. In univariate analyses, adverse prognostic factors for PFS included albumin <4 g/dl (p=0.04) and CD4+ count <200 cells/mm3 (p=0.0002) while diagnosis of AIDS (p=0.03) and CD4+ count <200 cells/mm3 (p=0.002) were adversely prognostic of OS. In multivariate analyses, CD4+ count <200 cells/mm3 was the only independent adverse prognostic factor for PFS and OS (p=0.002 and p=0.004, respectively). Separately, an IPS >3 was significant for a worse PFS (p=0.04) and had a trend towards significance for a worse OS (p=0.06). When compared side-to-side, CD4+ count <200 cells/mm3 was a stronger adverse factor than IPS >3 for PFS and OS. Conclusions: HIV-HL commonly presents with high-risk features such as advanced stage, B symptoms and hypoalbuminemia. Despite high-risk presentations, we demonstrate an encouraging prognosis when these patients are treated with ABVD and concurrent HAART. Low CD4+ count was the strongest adverse predictor of prognosis in this population. Disclosures: No relevant conflicts of interest to declare.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.236
Teacher spread0.226 · 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
Published2012
Admission routes2
Has abstractyes

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