Virological characteristics of hepatitis C virus infection in HIV-infected individuals with chronic hepatitis C: implications for treatment
Bibliographic record
Abstract
The treatment of chronic hepatitis C virus (HCV) infection is vital in patients co-infected with HIV, because end-stage liver disease is a leading cause of mortality in this population. The response to HCV therapy depends on the viral load and genotype. Patients with HCV genotypes 2/3 and low HCV-RNA titres show greater response rates, and may be treated for just 6 months, which is useful in HIV-co-infected patients, in whom anti-HCV drugs are toxic and may interact with antiretroviral agents. More than a third of HIV-infected individuals are estimated to be co-infected with HCV in the United States and Europe [1–3]. As the incidence of the classic opportunistic infections have declined dramatically since the introduction of highly active antiretroviral therapies, new entities have emerged as the leading causes of morbidity and mortality among HIV-infected individuals. Liver disease caused by HCV is one, if not the main, cause of morbidity and mortality in these patients [4–7]. The treatment of chronic hepatitis C with α-IFN was associated with high toxicity and low response rates in the past [8], but the chances of cure have improved significantly since the introduction of dual combination therapy with IFN plus ribavirin [9,10]. Moreover, the prospects are now even better after the approval of the new pegylated forms of IFN, which are more potent and less toxic [11–13]. Therefore, a reluctance to treat HCV infection in HIV-positive individuals is no longer justified. The response to HCV therapy is greatly dependent on two HCV virological variables, the viral load and the genotype [14], whose distribution is not well known in HIV/HCV co-infected individuals. Former studies showed that HCV genotype 3 was particularly prevalent among intravenous drug users [15], who represent the largest group of HIV-infected individuals with chronic hepatitis C. As HCV-3 tends to show the greater response to treatment [14,16], this was good news. Besides, treatment may be limited to just 6 months (instead of the standard 12 months) in patients carrying HCV genotypes 2/3 [17], which is of great interest in HIV-co-infected individuals because anti-HCV drugs are relatively toxic, and may interact with antiretroviral compounds [18,19]. Unfortunately, however, circulating HCV viraemia seems to be increased in immunosuppressed patients, including those with HIV infection [19,20], precluding the possibility of shortening the treatment period to 6 months [17]. However, a reduction in HCV viraemia has been noted in co-infected individuals treated with potent antiretroviral regimens [21,22], although much controversy exists on this matter [22–24]. Consequently, the knowledge of both the prevalence of HCV genotypes and the amount of HCV RNA in the current population of HIV/HCV-co-infected individuals is of great interest, in order to establish specific HIV/HCV treatment guidelines. HCV genotypes and plasma HCV-RNA titres were analysed in samples collected since 1998 from 917 HIV/HCV-co-infected individuals (69.4% male, 89% intravenous drug users) living in Madrid, Spain. HCV genotyping was carried out using a commercial hybridization system (LiPA HCV, Innogenetics, Barcelona, Spain) [25] and the HCV viral load was measured using the Cobas HCV Monitor (Roche Diagnostics, Barcelona, Spain) [26]. The distribution of HCV genotypes was as follows: HCV-1, 65.5%; HCV-3, 22.2%; HCV-4, 8.5%; HCV-2, 2.3%; HCV-5, 0.2%; and HCV-6, 0.1%. Only seven individuals (0.7%) harboured co-infections with distinct HCV genotypes: HCV-1 plus -4 (three patients), HCV-2 plus -3 (two patients), and HCV-1 plus -2 or -4 (one of each). The mean HCV viraemia was 982 308 IU/ml, being significantly higher in men than in women (1 017 837 versus 881 353;P < 0.05). Overall, up to 65.8% of patients harboured HCV-RNA loads above 800 000 IU/ml, a threshold that predicts a lower response to HCV treatment [14,17]. Overall, no differences in HCV-RNA levels were seen among different HCV genotypes (Table 1). However, sex differences in circulating HCV viraemia seemed to be restricted to genotypes 1 and 4: men infected with those HCV types harboured a greater HCV load than women. In contrast, women infected with HCV-3 tended to show greater amounts of HCV RNA than men (Table 2).Table 1: Distribution of hepatitis C virus genotypes and corresponding mean HCV-RNA values in the study population. Table 2: Hepatitis C virus load (IU/ml) according to sex and hepatitis C virus genotype. A review of recent reports [9,11,12,14,27,28] on the distribution of HCV genotypes and levels of HCV viraemia in large populations of HCV-mono-infected patients showed results that did not differ significantly from our figures in HIV/HCV co-infected patients. In contrast with previous findings [15,19,20], we did not find a higher rate of HCV-3 nor a greater HCV load in our population. This last observation might be related to the favourable impact of highly active antiretroviral therapy, limiting HCV replication [21,22]. The reason why HCV-3 has declined (it represented up to 63% of HCV infections among intravenous drug users until 1995 [15]) is not clear. Moreover, HCV-4 is currently more prevalent than expected, whereas HCV-2 is now very uncommon. HCV-4 might have been introduced into Spain in recent years from north Africa, where it is highly prevalent [29]. Needle sharing may have been the main route of transmission of this HCV variant, which otherwise is very rare in Spain among individuals who acquired HCV through other routes. Unfortunately, HCV-4 shows less susceptibility to IFN than HCV-2/3 [30]. In conclusion, only a minority (∼ 20%) of HIV/HCV-co-infected patients show a favourable virological profile for responding to HCV therapy (genotypes 2/3 in 25% and HCV viraemia < 800 000 IU/ml in 33%). Therefore, dual IFN/ribavirin therapy should be extended to one year in the majority of HIV/HCV-co-infected patients in order to optimize the treatment response rate. Mayte Pérez-Olmeda Pilar Ríos Marina Núñez Javier García-Samaniego Miriam Romero Vincent Soriano
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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) | 0.001 | 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".