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Expert Analysis
Expert Analysis: Insights for International Clinicians on New Data From HIV Glasgow 2020

Released: November 06, 2020

Expiration: November 05, 2021

Marina Klein
Marina Klein, MD, MSc, FRCP(C)
Jean-Michel Molina
Jean-Michel Molina, MD, PhD
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Fat Distribution and Density in PWH

Marina Klein, MD, MSc, FRCP(C):
We conclude this discussion by focusing on key data informing our understanding of comorbidities in PWH. In recent years, there has been a renewed focus on understanding more about weight gain in patients receiving contemporary ART regimens. In this observational cohort study, investigators determined the amount and density or “quality” of fat accumulating among patients who gained ≥ 5% weight after switching to INSTIs (n = 57) or remaining INSTI naive (n = 51).39 It is important to consider the way in which patients were selected and whether that may affect interpretation of the results. These treatment-experienced patients attended the Modena HIV Metabolic Clinic during a wide time frame, 2007 to 2019. Furthermore, multiple baseline characteristics significantly differed between groups, with a longer HIV duration as well as lower nadir and current CD4+ cell counts among switch patients.

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Fat Quantity and Quality at Last Contact in Patients With Weight Gain

Marina Klein, MD, MSc, FRCP(C):
The change in mean BMI was significantly higher in the INSTI switch group, at 2.47 vs 1.9 in the INSTI-naive group (P = .006). However, the groups experienced similar mean lean and fat gains during the approximately 4-year follow-up, as measured by dual-energy X-ray absorptiometry. This mimics an emerging theme wherein a certain level of background weight gain is occurring over time in everyone, as people age. Furthermore, once PWH are healthy, they tend to eat more like the general population and so, we must somehow subtract any expected gain from what may be caused directly by effective drugs, and that is where it becomes challenging. By CT, visceral adipose tissue was also comparable between groups, but there was a trend toward increased subcutaneous adipose tissue among patients who switched to INSTI-based ART (P = .06).

One caveat is the relatively small number of patients. Although this is quite a detailed exploratory study, it is more hypothesis generating than anything definitive.

Their final set of analyses elucidate the fat types that are being laid down in the setting of INSTI exposure. They found a statistically significant reduction in visceral adipose tissue density with INSTI switch and similar subcutaneous adipose tissue density reductions between groups.

Jean-Michel Molina, MD, PhD:
So, they are suggesting that this is good fat, right?

Marina Klein, MD, MSc, FRCP(C):
Yes. Their hypothesis is that this may signal improved fat “quality.”

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NAFLD and Cardiovascular Risk in PWH

Marina Klein, MD, MSc, FRCP(C):
This next study expanded our understanding of why we are concerned about fat at all, and it has to do with its potential to be associated with major comorbidities—specifically nonalcoholic fatty liver disease (NAFLD) and cardiovascular disease (CVD).40

Like the previous examination of fat quantity and quality, this cross-sectional study included PWH attending the Modena HIV Metabolic Clinic—in this case between June 2018 and October 2019. In total, 616 ART-experienced patients were surveyed to understand how transient elastography measuring NAFLD compared with an atherosclerotic cardiovascular disease (ASCVD) risk score for prediction of major adverse cardiac events and subclinical CVD.

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NAFLD as a Predictor for Cardiovascular Risk in PWH

Marina Klein, MD, MSc, FRCP(C):
There was a high prevalence of NAFLD with significant fibrosis (8.2%) or without significant fibrosis (39.7%) in this population, which is something that is a growing concern. The investigators showed a relationship between this prevalence and CVD risk. Being “low risk” for CVD was associated with the lowest prevalence of NAFLD, and the trend went upward from there. Having an ASCVD score ≥ 7.5% was associated with more NAFLD. If subclinical CVD was present, there was even more NAFLD. And, finally, patients experiencing a major adverse cardiac event exhibited the highest prevalence of NAFLD.

I think the results of this analysis provide 2 important insights. First, NAFLD could serve as a marker that warrants increased concern about someone’s cardiovascular risk. Thus, if you have a patient in front of you who is diagnosed with NAFLD, you also have to be thinking about them as someone with potential for CVD. But it also raises a question about the pathogenesis and how these 2 issues are linked. I do not know that we would use NAFLD instead of ASCVD score, for example, to predict cardiovascular risk, but I think it is more a question of maybe stepping up our suspicion of subclinical CVD among people with known NAFLD.

Jean-Michel Molina, MD, PhD:
Indeed, the take-home here is: When you see NAFLD, you need to worry about CVD.

Marina Klein, MD, MSc, FRCP(C):
Yes. NAFLD and CVD are clearly associated with one another whether they are causally associated or they share a common pathway. In the event a patient has one, you should be looking for the other and trying to manage them accordingly.

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RESPOND: Study Design

Marina Klein, MD, MSc, FRCP(C):
RESPOND is a multicohort effort originating in Australia and Europe and encompassing 29,432 PWH. A subset of this population was examined to determine if smoking differentially influenced the development of cancer based on the degree of virologic suppression or immune dysfunction.41

Among 507 PWH with 73,868 person-years of follow-up, 513 cancer events were recorded. Investigators first stratified cancer incidence by a single factor—either smoking status or, separately, HIV status. In general, crude incidence rates of cancer were lowest for never smokers and those with HIV-1 RNA < 200 copies/mL and CD4+ cell count ≥ 500 cells/mm3.

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RESPOND: Interaction Among Smoking, Viral Suppression, and Cancer Incidence in PWH

Jean-Michel Molina, MD, PhD:
The effect of CD4+ cell count and HIV-1 RNA level were most evident for AIDS-defining and infection-related cancers. By contrast, for BMI-related and non-AIDS–defining cancers, virologic control and immune status did not seem to matter as much.

Marina Klein, MD, MSc, FRCP(C):
When they looked for an interaction between smoking and HIV-1 RNA level/CD4+ cell count, they did not observe one. In essence, these parameters exert independent effects on the development of cancer.

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Assessment of Outcomes in Hospitalized Adults With COVID-19, With and Without HIV

Jean-Michel Molina, MD, PhD:
The last dataset we will discuss examines something on everybody’s mind: COVID-19. This prospective, observational study determined COVID-19 outcomes in hospitalized adults with and without HIV at 207 centers in the United Kingdom (N = 47,573).42 Despite the overall large cohort size, only 123 patients had HIV, and key information regarding their clinical trajectories were lacking. For instance, data on baseline HIV-1 RNA levels and CD4+ cell counts were not available. The absence of that information complicates interpretation of the data. Among the PWH, 90.2% had recorded ART use.

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COVID-19 Outcomes in Hospitalized Individuals With HIV: Results

Jean-Michel Molina, MD, PhD:
The results suggested that there was an increased risk of 28-day mortality among those with vs without HIV infection after controlling for factors such as age, sex, and so on. However, not having information on immune status or level of virologic control is a substantial limitation.

Marina Klein, MD, MSc, FRCP(C):
Yes, these could well be different types of individuals getting hospitalized. Patients could be admitted more readily if they are sicker from HIV at baseline, which could then naturally affect outcomes. I agree that we need more information. As clinicians, we continue to tell our patients that unless they have poorly controlled HIV, a low CD4+ cell count, multiple comorbidities, or are older, they are not at higher risk for poor COVID-19 outcomes than the average person. It is difficult to generalize these data without additional context.

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