Review of Boceprevir and Telaprevir for the Treatment of Chronic Hepatitis C
Bibliographic record
Abstract
OBJECTIVE: To summarize and evaluate the published literature pertaining to boceprevir and telaprevir, and to provide clinicians with suggestions for use in patients with chronic hepatitis C infection. METHODS: A standardized search strategy was performed using the MEDLINE, EMBASE, Google Scholar and International Pharmaceuticals Abstracts databases using the search terms "boceprevir", "telaprevir", "boceprevir and hepatitis C", and "telaprevir and hepatitis C". A manual search of references was performed to identify articles missed by the electronic search. Studies were included in the review if they assessed either boceprevir or telaprevir in comparison with standard of care in chronic hepatitis C patients. RESULTS: The studies identified assessed boceprevir and telaprevir in genotype-1 hepatitis C patients. In both treatment-naive and treatment-experienced patients, sustained virological response rates were achieved more often with boceprevir or telaprevir in combination with pegylated interferon and ribavirin compared with pegylated interferon and ribavirin alone. Both medications were well tolerated, with anemia presenting as the most treatment-limiting adverse effect. CONCLUSIONS: Boceprevir and telaprevir will revolutionize the management of hepatitis C genotype 1 patients and will most likely decrease the burden of end-stage disease worldwide. However, current clinical limitations include establishing appropriate and cost-effective treatment durations, and use in special populations such as transplant patients and patients coinfected with HIV. Future research will need to clarify these clinical obstacles to clearly define the role of these agents in hepatitis C management.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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".