Albumin levels can predict HIV disease severity and indicate success of antiretroviral therapy

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Serum albumin levels are a good predictor of the severity of HIV disease in individuals who are not taking antiretroviral therapy and can also indicate the extent of a patient’s response to HIV treatment, according to a study conducted in Nigeria and published in the September edition of HIV Medicine. The investigators believe testing serum albumin could be a particularly useful means of monitoring HIV disease progression, and the success of antiretroviral therapy, in poorer countries where many patients with access to HIV drugs cannot afford CD4 cell counts or viral load tests.

Although albumin levels are not a marker of HIV infection status, they have been found to be a strong predictor of mortality in HIV-positive adults and children. Tests to monitor serum albumin are cheap, and could therefore be a useful investigative tool in resource limited settings. Investigators from the university of Ilorin in Nigeria looked at the ability of serum albumin levels to predict the severity of HIV disease in 185 antiretroviral naive patients and their subsequent response to HIV therapy. CD4 cell count, and body weight were also measured in these patients to see how using serum albumin compared to the use of traditional measures of HIV disease progression and response to HIV therapy.

All the patients received an antiretroviral regimen consisting of lamivudine, stavudine and nevirapine and had a mean age of 37 years, with equal numbers being men and women. The patients had tests at baseline and then after three months of anti-HIV therapy.

Glossary

serum

Clear, non-cellular portion of the blood, containing antibodies and other proteins and chemicals.

 

disease progression

The worsening of a disease.

statistical significance

Statistical tests are used to judge whether the results of a study could be due to chance and would not be confirmed if the study was repeated. If result is probably not due to chance, the results are ‘statistically significant’. 

p-value

The result of a statistical test which tells us whether the results of a study are likely to be due to chance and would not be confirmed if the study was repeated. All p-values are between 0 and 1; the most reliable studies have p-values very close to 0. A p-value of 0.001 means that there is a 1 in 1000 probability that the results are due to chance and do not reflect a real difference. A p-value of 0.05 means there is a 1 in 20 probability that the results are due to chance. When a p-value is 0.05 or below, the result is considered to be ‘statistically significant’. Confidence intervals give similar information to p-values but are easier to interpret. 

sensitivity

When using a diagnostic test, the probability that a person who does have a medical condition will receive the correct test result (i.e. positive). 

Mean serum albumin level prior to the initiation of HIV therapy was 32mg/l, a level associated with an increased risk of mortality in earlier studies, but increased significantly to 37.7mg/l (p = 0.004).

Body weight was only a mean of 51kg prior to HIV treatment being provided, but it increased by a significant amount to a mean of 59kg after the initiation of HIV therapy (p < 0.001).

CD4 cell count before antiretroviral therapy was 215 cells/mm3, indicating that the patients had a very real risk of developing AIDS-defining illness. As would be expected, the provision of potent HIV therapy lead to a significant increase in CD4 cell count, to a mean of 372 cells/mm3, high enough to protect patients from life-threatening infections.

A significant correlation was found by the investigators between pre-treatment serum albumin levels and pre-treatment CD4 cell count (r = 0.231; p = 0.006) and pre-treatment serum albumin levels and pre-treatment weight (r = 0.354; p < 0.001).

What’s more, there was also a significant positive correlation between post-treatment serum albumin and CD4 cell count up to 700 cells/mm3 (r = 0.07; no p value provided), and between post-therapy serum albumin levels and weight (r = 0.278; p = 0.006).

Attention was then turned by the investigators to the relationship between increases in serum albumin levels and increases in weight and CD4 cell count. A significant positive correlation was found between increases in serum albumin and increases in weight (r = 0.505; p = 0.001), but the relationship between increases in albumin and post-treatment gains in CD4 cell count were just below the threshold for statistical significance (r = 0.20; p = 0.057).

“With a sensitivity of 91.5% and a positive predictive value of 96.15%, it is valid to use serum albumin in place of CD4 cell counts”, write the investigators.

They conclude, “in developing countries where many people are living below the poverty line, serum albumin would be a very useful surrogate test for predicting the severity of HIV infection and also for the clinical monitoring of response to antiretroviral therapy.”

References

Olawuni HO et al. The value of serum albumin in pretreatment assessment and monitoring of therapy in HIV/AIDS patients. HIV Med 7: 351 - 355, 2006.