Use of Hematopoietic Growth Factors as Adjuvant Therapy for Anemia and Neutropenia in the Treatment of Hepatitis C
Bibliographic record
Abstract
OBJECTIVE: To review the hematologic adverse effects of hepatitis C virus (HCV) therapy and adjuvant treatment with epoetin alfa and granulocyte colony-stimulating factor (ie, filgrastim). DATA SOURCES: Medical literature indexed in MEDLINE (1966-January 2007) and EMBASE (1980-January 2007) was searched, and published conference abstracts were reviewed. STUDY SELECTION AND DATA EXTRACTION: Peer-reviewed articles and relevant conference abstracts regarding the use of epoetin alfa and granulocyte colony-stimulating factor were reviewed. DATA SYNTHESIS: Ribavirin induces a dose-dependent hemolytic anemia. Studies using epoetin alfa 40 000 units subcutaneously once weekly have demonstrated efficacy in maintaining hemoglobin, ribavirin dose, and quality of life scores, but clear benefit shown with sustained virologic response (SVR) is lacking. The hemoglobin threshold for initiation of epoetin alfa used in studies may not adequately reflect values used in clinical practice. Treatment-related neutropenia is caused primarily by interferon or peginterferon. Few studies have investigated the impact of granulocyte or granulocyte-macrophage colony-stimulating factor derivatives on neutropenia. Results of dose maintenance evaluation vary, and studies reporting data on SVR showed no effect from growth factor therapy. The frequency of bacterial infections was not reported. CONCLUSIONS: The role and benefit of hematopoietic growth factors in HCV therapy have not been conclusively determined to date. However, the possibility of a benefit to individual patients seen on an outpatient basis remains, and an individualized treatment approach is recommended.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".