Antiretroviral therapy and liver disease progression in HIV and hepatitis C co-infected patients: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: HIV co-infection exacerbates hepatitis C disease, increasing the risk of cirrhosis and hepatitis C-related mortality. Combination antiretroviral therapy (cART) is the current standard treatment for co-infected individuals, but the impact of cART and antiretroviral (ARV) monotherapy on liver disease in this population is unclear. We aimed to assess the effect of cART and ARV monotherapy on liver disease progression and liver-related mortality in individuals co-infected with HIV and chronic hepatitis C. METHODS: A systematic review with meta-analyses was conducted. MEDLINE and EMBASE bibliographic databases were searched up to September 2015. Study quality was assessed using a modified Newcastle-Ottawa scale. Results were synthesised narratively and by meta-analysis. RESULTS: Fourteen observational studies were included. In analyses that adjusted for potential confounders, risk of liver-related mortality was significantly lower in patients receiving cART (hazard ratio/odds ratio 0.31, 95 % CI 0.14 to 0.70). Results were similar in unadjusted analyses (relative risk 0.40, 95 % CI 0.29 to 0.55). For outcomes where meta-analysis could not be performed, results were less consistent. Some studies found cART was associated with lower incidence of, or slower progression of liver disease, fibrosis and cirrhosis, while others showed no evidence of benefit. We found no evidence of liver-related harm from cART or ARV monotherapy compared with no HIV therapy. CONCLUSIONS: cART was associated with significantly lower liver-related mortality in patients co-infected with HIV and HCV. Evidence of a positive association between cART and/or ARV monotherapy and liver-disease progression was less clear, but there was no evidence to suggest that the absence of antiretroviral therapy was preferable.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.029 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".