Cigarette smoking may undermine benefits of potent antiretroviral therapy

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Cigarette smokers are more likely to be diagnosed with an AIDS-defining condition or to die, negating some of the benefits of potent antiretroviral therapy, according to a large prospective observational study of HIV-positive women from the United States. The study, published in the June issue of the American Journal of Public Health, is the first to find a relationship between smoking and HIV disease progression in women.

Until recently, there had been no studies on the effects of cigarette smoking in the era of potent antiretroviral therapy. Data from Galia and colleagues from the gay men's Multicenter AIDS Cohort Study had previously found no association between smoking and the risk of developing AIDS or dying, but since this was conducted prior to the availability of potent anti-HIV therapy, it was possible that the effects of smoking were masked by HIV's virulence.

Last year, Crothers and colleagues published data from a large prospective observational cohort of 867 HIV-positive male veterans which found that smokers on potent antiretroviral therapy were twice as likely to die than non-smokers, and more likely to suffer from increased respiratory symptoms, chronic obstructive pulmonary disease (COPD), and bacterial pneumonia.

Glossary

AIDS defining condition

Any HIV-related illness included in the list of diagnostic criteria for AIDS, which in the presence of HIV infection result in an AIDS diagnosis. They include opportunistic infections and cancers that are life-threatening in a person with HIV.

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. 

observational study

A study design in which patients receive routine clinical care and researchers record the outcome. Observational studies can provide useful information but are considered less reliable than experimental studies such as randomised controlled trials. Some examples of observational studies are cohort studies and case-control studies.

bias

When the estimate from a study differs systematically from the true state of affairs because of a feature of the design or conduct of the study.

confounding

Confounding exists if the true association between one factor (Factor A) and an outcome is obscured because there is a second factor (Factor B) which is associated with both Factor A and the outcome. Confounding is often a problem in observational studies when the characteristics of people in one group differ from the characteristics of people in another group. When confounding factors are known they can be measured and controlled for (see ‘multivariable analysis’), but some confounding factors are likely to be unknown or unmeasured. This can lead to biased results. Confounding is not usually a problem in randomised controlled trials. 

Recent studies have found that HIV-positive women who smoke are twice as likely to acquire bacterial pneumonia, and three times more likely to acquire human papilloma virus (HPV) , which can lead to cervical cancer, an AIDS-defining condition.

In order to investigate whether smoking affects disease progression and death in women on potent antiretroviral therapy, investigators from the Women's Interagency HIV Study (WIHS) analysed data from their longitudinal cohort study of HIV infection among women enrolled at six urban sites in the United States.

Of the 2,059 women in the cohort, 56% were current smokers and 16% were former smokers. At enrolment, the typical WIHS smoker had smoked a pack of cigarettes a day for a median of 12.4 years - about a third of her lifetime.

A total of 924 women were eligible for this analysis. To be eligible, an HIV-positive woman must have initiated potent antiretroviral therapy, and have CD4 count, viral load and smoking data available.

During the median 5.2 years of follow-up, around 524 women (57%) reported being current smokers. The investigators found that there were significant differences between smokers and non-smokers at baseline. Smokers were more likely to be African American; more likely to have used illicit drugs; had a lifetime history of illicit injection drug use; were more likely to be infected with hepatitis C virus; and were more likely to have previously been diagnosed with AIDS (all p=0.001).

In addition, they found that mean CD4 counts were significantly higher among smokers than non-smokers (539 vs. 517 cells/mm3; p=0.005), although this difference was not seen with viral load levels. However, over time, smokers' CD4 counts became lower than those of non-smokers (p=.01 for trend). The investigators attempt to explain this by saying that this may "reflect a selection bias in which healthier patients are more likely to smoke at any point in time." However it is known that HIV-negative smokers have higher CD4 lymphocyte levels, suggesting that selection bias may not explain this observation.

There were a total of 164 deaths during the observation period, and the investigators found that smokers had a 53% increased risk of dying compared with non-smokers (p=0.018), after adjusting for age, race, CD4 count, viral load, illicit drug use, previous AIDS, previous antiretroviral use, baseline hepatitis C infection, and baseline exposure category.

Smokers also had a 36% increased risk of of developing an AIDS-defining illness (p=0.01). However, the risk of AIDS-related deaths did not differ between smokers and non-smokers.

Since the investigators found that adherence to antiretroviral therapy was significantly lower among smokers than among non-smokers, in order minimise the potentially confounding effects of adherence they further limited their analysis only to women who reported greater than 95% adherence during the observational period. Nevertheless, differences between smokers and non-smokers in the risk of death and AIDS-defining conditions remained statistically significant.

The investigators say that their data "clearly demonstrated that HIV-positive women who smoke have a higher risk of acquiring [AIDS-defining illnesses] or dying." They add that potent antiretroviral therapy "is not as beneficial in smokers as it is in non-smokers."

Whilst this may be related in part to adherence, they argue, "even after adjustment for reported compliance and illicit drug use, [potent antiretroviral therapy] was still less effective in smokers as measured by AIDS incidence and death. These data indicate a negative impact of smoking even while [potent antiretroviral therapy] may be effective in reducing AIDS-related deaths in smokers."

However the investigators are not sure why there was a lack of an association between smoking and AIDS-related deaths. It may be due to an "inability to determine the true cause of death in this cohort setting or because competing causes of death result in smokers dying more rapidly (i.e. smokers die from acute causes such as drug overdoses, homicides/suicides/accidents before dying from AIDS-related causes)". It may also be the case that whilst smoking has an impact on AIDS-defining illnesses - such as cervical cancer and recurrent bacterial pneumonia - they did not result in death during the observation period.

Although the investigators controlled for important confounding factors like adherence and for illicit drug use, they concede that there "may still be some residual confounding factors not yet identified...We cannot exclude potential bias among patients in poor health who may be more or less likely to smoke. For example, a patient in poor health who feels that she has nothing to lose might choose to smoke anyway, in spite of the known health risks."

Nevertheless, they conclude by saying that their "data suggest that the treatment of HIV-positive women with [potent antiretroviral therapy] may be less effective in those who smoke cigarettes and point to a need to promote smoking cessation."

References

Feldman JG et al. Association of cigarette smoking with HIV prognosis among women in the HAART era. Am J Public Health 96(6): 1060-1065, 2006.

Crothers K et al. The impact of cigarette smoking on mortality, quality of life, and comorbid illness among HIV-positive veterans. Journal of General Internal Medicine 20 (12), 1142-1145, 2005.

Galai N et al. Effect of smoking on the clinical progression of HIV-1 infection. J Acquir Immune Defic Syndr Hum Retrovirol 14: 451-458, 1997.