Control of Oxidant-Stress and Inflammation by Iron Chelators Deferasirox (ICL670) or Deferoxamine in β-Thalassemia: An Ancillary Study of the Novartis CICL670A0107 Trial.
Bibliographic record
Abstract
Abstract Objective: We examined whether oxidant-stress and inflammation in β-thalassemia can be controlled by deferasirox as effectively as by deferoxamine (DFO) through analysis of body iron burden and biomarkers of lipid peroxidation and inflammation. Methods: Thalassemia Clinical Research Network patients participating in the Novartis CICL670A0107 trial (a randomized comparison of deferasirox, an oral iron chelator, vs. DFO) were eligible and 44 (25 male, 21.8±11.1 yrs) were enrolled in the study. Blood samples were obtained fasting after a 5-day washout of DFO prior to commencing treatment with study drug, and 24 hours post-chelator and antioxidant supplementation at 1, 6, and 12 months on study. Thirty healthy untreated controls matched for age, sex, and race (15 male, 24.5±9 yrs) were also studied. Plasma levels of malondialdehyde (MDA), a marker of lipid peroxidation, were determined by GC-MS; vitamin C by spectrophotometry; α-tocopherol by HPLC; and high-sensitivity C-reactive protein (hsCRP), a marker of inflammation, by nephelometry. In patients with thal, liver iron concentration (LIC) was analyzed by atomic absorption spectrometry and ferritin by immuno-assay. MDA, α-tocopherol, and hsCRP were log-transformed prior to analysis. Back-transformed means are reported. Results: Mean MDA concentrations (nmol/L) at 0, 1, 6, and 12 months were as follows: deferasirox: 78, 77, 46, 48; DFO: 40, 44, 37, 33. Mean MDA concentration in control subjects was 19 nmol/L (range 2–76 nmol/L). MDA was elevated in both treatment groups as compared to controls (p<.05). Mean MDA was highest prior to commencing study treatment and after 1 mo of study treatment with a significant decrease noted in both treatment groups over the course of treatment (deferasirox −27 nmol/L, DFO −12 nmol/L, p<.001 for average decline, p=.34 for difference in rate of decline). This parallels significant declines in both groups in LIC (mean 2.0 mg/g dry/yr, p=.01) and ferritin (mean 444 ng/mL/yr, p<.001). In cross-sectional analysis, MDA was positively correlated with ferritin (r2=.21, p=.06) and LIC (r2=.42, p<.001) and negatively correlated with Vitamin C (r2= −.37, p<.001) and α-tocopherol (r2= −.38, p<.001). Mean hsCRP (mg/L) at months 0, 1, 6, and 12 were as follows: deferasirox: 1.4, 2.1, 0.9, 0.6; DFO: 0.8, 1.1, 0.9, 1.2. Mean hsCRP concentration in control subjects was 0.66 mg/L (range 0.2–5.1 mg/L). In contrast with MDA trajectories, hsCRP showed significant decrease only in the group receiving deferasirox (deferasirox −1.0 mg/L, DFO +0.37 mg/L, p<.001). Conclusions: These results demonstrated a correlation of iron burden with elevated biomarkers of oxidant-stress and inflammation. Iron chelation therapy with DFO or with deferasirox showed equal effectiveness in decreasing MDA. In contrast, only therapy with deferasirox produced a significant decline in hsCRP.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".