Association of TNF-α and CCL5 with response to interferon-based therapy in patients with HCV 1 genotype
Bibliographic record
Abstract
AIM OF THE STUDY: To evaluate the role of potential genetic predictors -308G/A TNF-α and -403G/A CCL5 in treatment for HCV 1 genotype. MATERIAL AND METHODS: Treatment results of 130 patients with chronic hepatitis C 1 genotype according to different genotypes of IL28B, CCL5, and TNF-α were analysed using multiple logistic regression. RESULTS: IL28B genotypes CC/CT/TT were found in 27 (20.8%), 74 (56.9%), and 29 (22.3%) patients. Genotypes GG/GA/AA of -308G/A TNF-α were revealed in 98 (75.4%), 30 (23.1%), and 2 (1.5%) patients. Genotypes GG/GA/AA of -403G/A CCL5 were revealed in 86 (66.2%), 39 (30%), and 5 (3.8%) patients, respectively. The previously known effect of IL28B was observed. IL28B TT genotype decreased end of treatment response (EOTR) rates by a factor of 29.0 (95% CI: 6.4-183). The combination of CCL5 GG and IL28B CT genotypes increased the risk of failure to achieve EOTR by a factor of 28.5 (95% CI: 7.2-160). Genotypes GA and AA of TNF-α (-308) G/A SNP increased the risk of relapse in patients who achieved EOTR (OR = 9.4; 95% CI: 2.4-48). CONCLUSIONS: Practitioners may benefit from using these predictors when considering indications for the antiviral therapy and deciding on the treatment regimen.
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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) | 0.000 | 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) | 0.000 | 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".