Association of interleukin-6 and interleukin-8 with poor prognosis in elderly patients with chronic lymphocytic leukemia
Bibliographic record
Abstract
In population studies, the relative survival in chronic lymphocytic leukemia (CLL) decreases with age. In this study, we demonstrated in a cohort of 189 patients from a CLL clinic that overall survival was lower in the sub-cohort of patients aged ≥ 70 years, but causes of death were similar for all age groups, being progressive CLL, secondary malignancies and infections. As normal individuals age, the plasma levels of inflammatory cytokines, such as interleukin-6 (IL-6) and IL-8, can increase. In our patients with CLL, IL-6, IL-8 and tumor necrosis factor-α (TNF-α) levels increased with age to a greater degree than in normal individuals, and the levels correlated closely with plasma β(2)-microglobulin and with one another. In addition, in patients ≥ 70 years, IL-6 was found to be a better prognostic marker than immunoglobulin variable heavy chain gene (IgV(H)) status. In vitro studies demonstrated that IL-6 and IL-8 could enhance the binding of CLL cells to stromal cells, suggesting that their clinical activity may be mediated through their effects on the microenvironment. Thus, plasma IL-6 is an important prognostic marker for the elderly with CLL, and this study highlights that the utility of prognostic markers may depend on patient age.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".