| Literature DB >> 17502001 |
Simone E Langford1, Jintanat Ananworanich, David A Cooper.
Abstract
During the extended clinically latent period associated with Human Immunodeficiency Virus (HIV) infection the virus itself is far from latent. This phase of infection generally comes to an end with the development of symptomatic illness. Understanding the factors affecting disease progression can aid treatment commencement and therapeutic monitoring decisions. An example of this is the clear utility of CD4+ T-cell count and HIV-RNA for disease stage and progression assessment. Elements of the immune response such as the diversity of HIV-specific cytotoxic lymphocyte responses and cell-surface CD38 expression correlate significantly with the control of viral replication. However, the relationship between soluble markers of immune activation and disease progression remains inconclusive. In patients on treatment, sustained virological rebound to >10,000 copies/mL is associated with poor clinical outcome. However, the same is not true of transient elevations of HIV RNA (blips). Another virological factor, drug resistance, is becoming a growing problem around the globe and monitoring must play a part in the surveillance and control of the epidemic worldwide. The links between chemokine receptor tropism and rate of disease progression remain uncertain and the clinical utility of monitoring viral strain is yet to be determined. The large number of confounding factors has made investigation of the roles of race and viral subtype difficult, and further research is needed to elucidate their significance. Host factors such as age, HLA and CYP polymorphisms and psychosocial factors remain important, though often unalterable, predictors of disease progression. Although gender and mode of transmission have a lesser role in disease progression, they may impact other markers such as viral load. Finally, readily measurable markers of disease such as total lymphocyte count, haemoglobin, body mass index and delayed type hypersensitivity may come into favour as ART becomes increasingly available in resource-limited parts of the world. The influence of these, and other factors, on the clinical progression of HIV infection are reviewed in detail, both preceding and following treatment initiation.Entities:
Year: 2007 PMID: 17502001 PMCID: PMC1887539 DOI: 10.1186/1742-6405-4-11
Source DB: PubMed Journal: AIDS Res Ther ISSN: 1742-6405 Impact factor: 2.250
Figure 1General pattern of the natural history of HIV-RNA levels and CD4 counts at three rates of disease progression [5] (Reproduced from Figure 1, HIV InSite Knowledge Base, with permission).
Predicted 6 month risk of AIDS according to age, current CD4+ cell count and viral load, based on a Poisson regression model
| 3000 | 1.6 | 1.1 | 0.8 | 0.6 | 0.5 | 0.4 | 0.3 | |||
| 10 000 | 1.6 | 1.2 | 0.9 | 0.7 | 0.5 | 0.4 | ||||
| 30 000 | 1.6 | 1.2 | 0.9 | 0.7 | 0.6 | |||||
| 100 000 | 1.8 | 1.4 | 1.1 | 0.8 | ||||||
| 300 000 | 1.9 | 1.5 | 1.2 | |||||||
| 3000 | 1.4 | 1.0 | 0.8 | 0.6 | 0.5 | 0.4 | ||||
| 10 000 | 1.5 | 1.1 | 0.9 | 0.7 | 0.5 | |||||
| 30 000 | 1.6 | 1.2 | 0.9 | 0.7 | ||||||
| 100 000 | 1.7 | 1.3 | 1.1 | |||||||
| 300 000 | 1.9 | 1.5 | ||||||||
| 3000 | 1.8 | 1.3 | 1.0 | 0.7 | 0.6 | 0.5 | ||||
| 10 000 | 1.9 | 1.4 | 1.1 | 0.8 | 0.7 | |||||
| 30 000 | 1.5 | 1.2 | 0.9 | |||||||
| 100 000 | 1.7 | 1.3 | ||||||||
| 300 000 | 1.9 | |||||||||
| 3000 | 1.7 | 1.2 | 0.9 | 0.7 | 0.6 | |||||
| 10 000 | 1.8 | 1.4 | 1.1 | 0.8 | ||||||
| 30 000 | 1.9 | 1.5 | 1.2 | |||||||
| 100 000 | 9.2 | 6.5 | 4.8 | 3.6 | 2.8 | 2.2 | 1.7 | |||
| 300 000 | ||||||||||
<2%, risk 2–9.9%, risk 10–19.9%,
This table is reproduced from Table 4 in [10]
Figure 2Kaplan Meier plots of the probability of progression to AIDS or death according to baseline CD4 count [20] (reproduced with permission).