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Record W2089775846 · doi:10.1158/1538-7445.am2011-4162

Abstract 4162: The importance of age-related cytokines in chronic lymphocytic leukemia

2011· article· en· W2089775846 on OpenAlexaff
Ju‐Yoon Yoon, Sandrine Lafarge, David E. Dawe, Sunjay Lakhi, Rajat Kumar, Aaron J. Marshall, Spencer B. Gibson, James B. Johnston

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineChronic lymphocytic leukemiaCytokineInternal medicinePopulationProinflammatory cytokineCD38ImmunologyDiseaseInterleukin 6GastroenterologyLeukemiaInflammationBiology

Abstract

fetched live from OpenAlex

Abstract Chronic lymphocytic leukemia (CLL) is a disease of the elderly with the median age at diagnosis being 72 years. Prognosis is highly variable with the relative survival progressively worsening after age 65 years. In this study we have evaluated whether the age-related cytokines, IL-6, IL-8 and TNF-alpha, play a role in the poor survival of elderly patients with CLL. The plasma levels and biological effects of the age-related cytokines, IL-6, IL-8 and TNF-alpha, were evaluated in 193 CLL patients of varying ages. Patients were chosen randomly to reflect the age spectrum and sex distribution of the Manitoban CLL population. As predicted from population studies, the survival of patients progressively worsened with age, with the primary causes of death being CLL or one of its complications (infection or second tumors). Cytokine levels were increased in CLL compared to 37 age- and sex-matched controls. A third of patients aged </=65 years had increased IL-6, compared to 10% in patients < 65. A high correlation was found between the plasma levels of these three cytokines with age and Beta2-microglobulin (a measure of tumor burden). The plasma levels of the cytokines also correlated with each other, suggesting they increased in parallel. In contrast, the standard CLL prognostic markers IgVH mutational status, ZAP-70, CD38 and Rai stage did not correlate with cytokine levels or age. Patients with increased IL-6 or IL-8 had a poorer survival than those with normal levels. For IL-6, this difference was more marked for those </=65 years. Furthermore, focusing on older patients, multivariate analysis with backward selection of variables showed IL-6 and Beta2-microlgobulin to be significant predictors of survival, while the mutational status and Rai stage were not significant. The cause of death was due to CLL-related causes and not to frailty or cardiovascular disease. However, increased cytokine levels correlated with a higher lifetime incidence of cardiovascular disease. Thus, one source of cytokines may be cardiovascular disease, although CLL cells also secreted low amounts of IL-6 and IL-8. The two cytokines, in turn, significantly increased the adhesion of leukemic cells to stromal cells, suggesting that these cytokines may influence the microenvironment, which would contribute to poor survival. In summary, IL-6 and IL-8 are predictors of survival in CLL, where IL-6 is a stronger predictor of survival in older patients than mutational status or Rai stage. Importance of IL-6 and IL-8 may be associated with their role in facilitating the leukemic-stromal cell interaction. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4162. doi:10.1158/1538-7445.AM2011-4162

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 score0.001
Threshold uncertainty score0.005

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 head0.112
GPT teacher head0.397
Teacher spread0.285 · 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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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