<p>IL-6 −572C>G and CARD8 304T>A Genetic Polymorphisms are Associated with the Absolute Neutrophil Count in Patients with Hematological Malignancies Under Chemotherapy: An Application of Multilevel Models to a Preliminary Pharmacogenetic Study</p>
Bibliographic record
Abstract
Purpose: Neutropenia is a common event in patients undergoing cytotoxic chemotherapy for the treatment of a hematological malignancy. Some polymorphisms, as IL-6 − 572C>G (rs1800796), IL-1β − 31 G>A (rs1143627), and CARD8 304T>A (rs2043211), in genes related to the inflammatory process, could affect the level of absolute neutrophil count (ANC) after chemotherapy. Since an efficient inflammatory process enhances neutrophil survival, we hypothesize that these polymorphisms are associated with ANC. Patients and Methods: We carried out a prospective cohort study in two hospitals in Santiago, Chile. The patients included were adults diagnosed with acute myeloblastic leukemia, acute lymphoblastic leukemia, or non-Hodgkin’s lymphoma, undergoing cytotoxic chemotherapy. We use a multilevel linear regression model to test our hypothesis. The best model was selected using the Akaike’s information criterion (AIC). Results: We analyzed 1726 hemograms and ANCs from 172 hospitalizations from 32 patients. The results show that CC and CG genotypes of IL-6 − 572 C>G polymorphism are associated with higher ANCs compared with the GG genotype (Ln (ANC) ∼ 0.81 IC95% 0.02– 1.55). Similarly, TT and AT genotypes of CARD8 304T>A polymorphism were related to higher ANCs compared with AA (Ln (ANC) ∼ 0.95 IC95% 0.02– 1.82). IL-1β genetic polymorphism had no statistically significant association with ANC. Conclusion: IL-6 rs1800796 − 572C>G and CARD8 rs2043211 304T>A polymorphisms are associated with the absolute neutrophil count in patients undergoing cytotoxic chemotherapy for treatment of hematological malignancies. Our findings might be useful to improve the safety of chemotherapy through predictive ANC models. Keywords: pharmacogenetics, neutropenia, hematological neoplasms, leukemia, lymphoma, interleukin-6, CARD8 protein
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".