Tuesday, November 28, 2023
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Editor's Note:
The toxicities associated with antiretroviral therapy for HIV infection have emerged as one of the most important clinical considerations for physicians and nurses involved in the management of this patient population. In particular, the metabolic and morphologic abnormalities associated with HIV or its treatment remain one of the more challenging areas of HIV care. The 8th International Workshop on Adverse Drug Reactions and Lipodystrophy in HIV, which was held September 24-26, 2006 in San Francisco, remains the most important annual workshop devoted to original research on this topic. One of the most widely recognized experts in this subspecialty of HIV medicine is Andrew Carr, MD, who is Associate Professor of Medicine at the University of New South Wales, Sydney, Australia, and Senior Staff Specialist, HIV, Immunology, and Infectious Diseases Unit at St. Vincent's Hospital in Sydney, Australia. Dr. Carr spoke with Scott Williams, Editorial Director of Medscape HIV/AIDS, about the highlights from this year's meeting.
Medscape: The evaluation of metabolic and morphologic changes in patients with HIV infection is obviously one of the central topics of this workshop. What do you think were some of the most important reports on this broad issue that you saw at the workshop?
Dr. Carr: There were a number of studies of interest. For example, one study aimed to define which patients do or don't have a label of Metabolic Syndrome in HIV; another aimed to define the clinical significance of Metabolic Syndrome in this patient population; and another examined what might be done about this syndrome from a clinical standpoint. The first of these 3 studies looked at 2 of the more common diagnostic tools for diagnosing Metabolic Syndrome.[1] Of course, as it's a syndrome with no known cause, different groups have come up with slightly different ways of looking at the same problem. Generally, it's a clustering of these criteria: abdominal obesity, hypertension, high triglycerides, low HDL cholesterol, and insulin resistance or diabetes.
The 2 commonly used variations of the diagnostic tool are from the US National Cholesterol Education Program, Adult Treatment Program III (ATP-3), and a more recent one from the International Diabetes Federation (IDF). ATP-3 requires 3 of the 5 criteria to be met. IDF absolutely requires abdominal obesity and 2 of the other 5. A group reported on the prevalence of Metabolic Syndrome in almost 800 adults with HIV infection and found that the prevalence of Metabolic Syndrome with one definition was 14% and with another was 18%.[1] That's, in fact, lower than the [prevalence in the] US population, which is about 25%.
This population was drawn from around the world, not just from the United States, and includes patients not currently treated and those who are heavily treated, as well as patients with and without lipodystrophy. What was quite interesting was that there was a substantial proportion of patients — about 50% — who were not labeled as having Metabolic Syndrome but in fact had all the metabolic components of it.
The reason they weren't labeled as having Metabolic Syndrome was because they weren't sufficiently obese. In other words, in the setting of HIV infection, a person doesn't have to be as obese as somebody in the general population in order to have the metabolic features of Metabolic Syndrome. To summarize, about 15% to 20% of people may be labeled as having Metabolic Syndrome, but looking at these criteria, the metabolic components of the syndrome were occurring in about 50% of the patients in this study, which is far higher than in the general population.
Medscape: Please tell us about the next study that looked at the clinical significance of Metabolic Syndrome in patients with HIV.
Dr. Carr: A subsequent study prospectively looked at this issue. They looked at the INITIO trial, which was a 900-patient, 3-year study that evaluated a protease inhibitor (nelfinavir), a nonnucleoside reverse transcriptase inhibitor (efavirenz), or both agents, combined with didanosine (ddI) and stavudine (d4T).[2] The measurements required to generate a label of Metabolic Syndrome were recorded in this study. At baseline, they found that the prevalence was about 10%, which is low. But, of course, these are patients who have some HIV wasting, so this was not surprising. However, if you exclude the 10% who did not have Metabolic Syndrome at baseline, about another 25% to 30% of patients developed Metabolic Syndrome during the study.
It's important to remember that Metabolic Syndrome in the general population is a strong predictor for the development of diabetes and is also a predictor of the development of cardiovascular disease. In this study, Metabolic Syndrome at baseline and incident Metabolic Syndrome during the study were both strong predictors of the development of diabetes during the 3 years. Baseline Metabolic Syndrome, but not incident Metabolic Syndrome, was also predictive for the development of cardiovascular disease during the study.
These data suggest that Metabolic Syndrome does have clinical significance in patients with HIV and that treatment-induced Metabolic Syndrome has implications for diabetes, and possibly for cardiovascular disease. A patient was more likely to develop Metabolic Syndrome on nelfinavir than on efavirenz. But, of course, the contribution of the ddI-d4T backbone can't be determined because there's no comparative group for the nucleosides. Given what we know about their metabolic complications, it's quite possible that they contributed. These are regimens that are, by and large, not used anymore. So how applicable these data are to contemporary regimens is not clear. I would suspect that the incidence of Metabolic Syndrome might be a lot lower, but if you develop Metabolic Syndrome, the implications are probably going to be the same.
One important point from these data was that even though Metabolic Syndrome was highly predictive for diabetes and, quite possibly, for cardiovascular disease, the individual components of Metabolic Syndrome were not predictive. For example, just having high triglycerides doesn't predict diabetes, but high triglycerides with the other components of Metabolic Syndrome does. So if clinicians screen patients in order to avoid diabetes and cardiovascular disease, it's really important to screen for multiple risk factors, not just for one. So that begs the question of what to do about it.
Medscape: And the other study you mentioned earlier pertained to clinical management. What were the important points?
Dr. Carr: A group from Massachusetts General Hospital in Boston did a small, 6-month study in 34 patients with Metabolic Syndrome who were randomized to one counseling session or to an intensive lifestyle-modification program where the patients came in once a week to see a dietician and to have the various components of the program emphasized (intensive arm).[3] This included a reduced-fat diet, 2.5 to 3 hours of moderate-to-intensive exercise per week, and a high-fiber diet. The control group received a single phone counseling session at baseline to educate them about the benefits of a good diet and exercise.
Over a 6-month period, the adherence to the program among subjects in the intensive arm was about 75%. Clinical trial subjects are often highly motivated, so how well this would actually go in clinical practice is unknown. I'd be surprised if most patients would come in weekly for a 6-month period, or indeed if that were feasible. Nevertheless, this was a sort of proof-of-principle study.
The investigators found that this intervention decreased waist circumference and decreased systolic blood pressure significantly. The blood pressure difference was about 20 mm Hg for systolic blood pressure, which was really quite a substantial decline. It also decreased hemoglobin A1c levels, which is a measure of diabetes. However, it did not affect lipids at all. It did not affect fasting insulin levels, another diabetic measure.
So the results were mixed. Nevertheless, it's a very small study, and so it can tell us what can be affected and improved, but it doesn't tell us what can't be improved, because the study's too small. It may be that if the study were 100 times larger, they would find lipid differences.
Medscape: There have been previous studies on diet and lifestyle modifications in the setting of HIV. How does this one differ from other studies that have been done?
Dr. Carr: It's taken a long time, but this is the very first randomized study that evaluated both diet and exercise together in this population. They looked at a specific population with Metabolic Syndrome, whereas other studies have looked at diet or exercise for lipid disturbances. These patients were not selected on the basis of lipid disturbances. Most of them had some lipid abnormality, but certainly not all of them did.
I think it does say to us that these approaches to exercise and diet that are recommended for the non-HIV population make sense for persons with HIV who also have Metabolic Syndrome. The first study I referred to suggested that the specific metabolic components of this syndrome are really common, so this may well apply to a large proportion of HIV-infected adults.
Medscape: Lipoatrophy is a critical concern for many patients with HIV, and it has potential implications beyond cosmetic concerns. What new data did you see on this important topic?
Dr. Carr: Two studies addressed the question of whether lipoatrophy could be predicted. We know that some drugs are more likely to cause this adverse effect, but these investigators looked more at pathogenesis. The first was a genetic study that's a collaboration between the ACTG and some genetics investigators at Bristol-Myers Squibb.[4] They looked at the ACTG body composition substudy that was published in AIDS last year.[5]
They genotyped the adults who enrolled in this study for 135 genes and 285 single nucleotide polymorphisms (SNPs). They looked at 135 genes that they thought might have a bearing on metabolic abnormalities that are seen, such as those related to lipid and insulin metabolism, and at ones related to body fat function or body mass index. They identified one, an SNP in the gene for resistin, a protein involved in insulin sensitivity that is made (in part) by fat. High levels of resistin can generate insulin resistance.
This polymorphism was strongly associated with a clustering of abnormalities such that patients who, with one genotype of this polymorphism, had much higher lipid changes in the response to antiretroviral therapy, and had greater limb fat loss over the course of the study, regardless of what treatment they were on.
So that begs the question of whether this test may be useful in predicting who might get lipoatrophy. It wasn't a very large sample, and it's based on a lot of patients who received ddI-d4T, so it may not have any applicability today. Clearly it needs to be validated in a larger and separate cohort receiving contemporary treatments to know whether it could be used as a screening test.
Medscape: Certainly some patients are still starting or continue to take thymidine analogs, despite the adverse effects that are associated with these drugs.
Dr. Carr: Yes, they are. There are a lot of patients who started AZT and are still on it, and there are a lot of patients now who are starting AZT as a second-line nucleoside. There are also a smaller number of patients who are using ddI in various settings. Looking at those patient populations with this test may well be a useful exercise.
The second study looked at another group (about 60 adults) of naive patients who had body composition assessed every 6 months for between 2 and 3 years.[6] The authors looked at both baseline parameters and other measures over the first 6 months of treatment to get a sense of who was most likely to get either lipoatrophy or visceral fat accumulations. Lipoatrophy was measured with a DEXA scan and visceral fat accumulation with abdominal CT scan. Apart from the clinical and metabolic parameters (lipids and glucose), other fat proteins were measured such as adiponectin, leptin (an adipocytokine involved in insulin sensitivity), C-reactive protein, and tumor necrosis factor-alpha (TNF-alpha), which have been associated with lipoatrophy.
There were 2 main findings. First, as an end-of-the-bed test, body mass index was strongly related to fat loss. But it was completely the opposite from what cross-sectional studies had shown. Cross-sectional studies have shown that lipoatrophy is more likely in patients who were wasted, who had less fat. But, in fact, this study showed that the more fat you had at the beginning, the more fat you lost. So the notion of starting early and somehow protecting against lipoatrophy is probably completely wrong. They also found that the greater the changes in plasma levels of leptin in the first 6 months of treatment, the greater the body fat loss. In fact, leptin levels at baseline also had some predictive value in regard to the development of lipoatrophy.
These data suggest that a protein could be measured to help predict lipoatrophy risk in a person starting a regimen. And clearly the body mass index at the start of treatment is also going to give you a sense of how much fat the patient might lose.
Again, a sizeable proportion of this population was on ddI-d4T, so it will be helpful to have this validated in another population. In fact, both the resistin polymorphism and leptin levels are likely to be tested in the ACTG-5142 population. Everybody in that study had DEXAs performed and serum stored, so it's likely that that much larger population will be looked at in the coming months.
In the present study, the investigators also looked at visceral fat accumulation and they found very different associations. The only metabolic parameter that predicted the degree of fat accumulation was the level of TNF-alpha. TNF-alpha is a pro-inflammatory cytokine and the levels at baseline were high, which is quite consistent with HIV replication, and the levels fell very dramatically and stayed down following treatment initiation. The magnitude of that change was associated with how much visceral fat the patients gained. But the baseline BMI and the leptin had no bearing on this. That implies, as some other data do, that peripheral fat loss and central fat gain are separate processes — that, at least in part, the amount of abdominal fat you gain is just a function of recovery from wasting, rather than a specific drug effect.
Medscape: In terms of the thymidine analog issue you noted, we also saw some longer-term data from studies of stavudine vs tenofovir, which has been one of the nucleosides, along with abacavir, that many patients have initiated or switched to in order to avoid development of or worsening of lipoatrophy. What are the longer-term data now showing in terms of lipoatrophy or other adverse events?
Dr. Carr: There is no doubt that the only effective way of managing lipoatrophy is to prevent it from occurring in the first place. Randomized trials evaluating switches from protease inhibitors have not shown benefit. Studies in which patients switched from stavudine or zidovudine to abacavir or tenofovir found that lipoatrophy did improve significantly over 12 to 24 months, but that the magnitude of change was fairly modest. A patient improving at the average rate (about 300-400 g of limb fat per year) would not expect lipoatrophy to resolve within 5 or maybe even 10 years, and of course it is possible that lipoatrophy may never resolve. Data from Gilead 903 presented at the workshop[7] were consistent with this, with about a 0.9kg improvement in limb fat mass over 2 years.
Antiretroviral initiation studies with tenofovir or abacavir show fairly compelling data that these drugs do not cause lipoatrophy, and so the safety focus with both drugs has moved to hypersensitivity for abacavir and to renal and bone safety for tenofovir. With tenofovir, the 3-year randomized data from the Gilead 903 trial[7] and the subset of South American patients with 5 years of follow-up[8] showed minimal evidence of renal dysfunction and stable and probably normal limb fat mass.
Medscape: Could you tell us about new data in regard to the clinical equations that clinicians are now using to monitor renal function in antiretroviral-treated persons with HIV? There were a few studies at the workshop that addressed this important issue.
Dr. Carr: It's been known for a long time that just measuring serum creatinine is a very poor estimate of renal dysfunction. You essentially need to lose more than half of your renal function before your creatinine starts to increase significantly above the "noise" of the test.
There are 2 equations that nephrologists use to improve this evaluation. One is the Cockcroft-Gault equation, which gives an estimate of what's called creatinine clearance from the kidneys. That's been recently replaced somewhat by another equation, called the modification of diet in renal disease, or MDRD equation. The nephrology guidelines for managing patients with chronic renal disease now recommend that the MDRD equation be used because it's probably a more sensitive measure of renal dysfunction.
One caveat here is that all drug dosing in most countries is based on the Cockcroft-Gault equation. For example, when the FDA says that you should dose-reduce or use a drug every second day, that's based on the Cockcroft-Gault equation. So you dose based on one equation but you monitor with the other, which is a little confusing.
Dr. Donald Kotler evaluated some older data from his site on creatinine clearance, serum creatinine, the MDRD equations, and body composition data in order to determine how well these 2 equations performed in people of various body mass indexes.[9] He looked at people who were healthy, people who were extremely wasted, and people who were obese, because serum creatinine is affected not only by renal function, but also by how much creatinine is produced, which is a product of a person's muscle mass.
Effectively what he found is that at either extreme — for obese or for wasted persons — these equations perform quite poorly. These data don't affect most people, but these data do suggest that any single point estimate that you derive from these equations should be repeated, particularly in patients at either body composition extreme.
Of course, the general recommendation is that when an MDRD equation is used, a glomerular filtration rate (GFR) is given an absolute value, if the value is less than 60 mL/min per 1.73 m2 (a normal value is 100 or more.) If it's above 60, the results should be expressed as "greater than 60", and that's because the higher the number, the less reliable the result. One problem is that many pathologists aren't now doing this; they're actually giving values of 75, for example. That's because the test has noise in it. If body composition introduces further noise into that, I think that that's a further impetus for physicians to ignore those numbers above 60 and to ignore single values. What we really need are trends in results over time.
The other implication of these sorts of data is how we interpret clinical trial results. Treatment-naive patients who start drugs will have changes in their body composition, such as weight gain. Therefore, what's going to be very important in interpreting data such as these are control groups. If you've got a drug that affects renal function and a drug that doesn't, then the differences observed between the 2 groups is what matters, not the absolute changes from baseline.
Tenofovir is a focus of attention in terms of renal function. There were 2 cohort studies that looked at factors associated with renal dysfunction. One was from the Vancouver cohort of almost 1200 adults who commenced tenofovir between 2003 and 2005[10]; the second cohort was the Women's Interagency HIV study (WIHS) cohort, which looked at 645 tenofovir-naive women who started treatment with that drug.[11]
These are real-world cohorts. They weren't prospectively studying tenofovir toxicity, so the data aren't perfect, and antiretroviral regimens are, of course, very heterogeneous. Furthermore, there aren't any data on hypertension, diabetes, race, or nephrotoxic drugs, so we will mostly see the "big signals," if they're there. The potential risk factors found in the 2 different studies were different, although the general impression of how nephrotoxic tenofovir might be was pretty similar.
Approximately 2% to 4% of patients were experiencing what would be regarded as significant declines in renal function while on tenofovir-containing regimens. In the Vancouver cohort, they also found an association with ddI, perhaps because tenofovir-ddI was a pretty popular combination a few years ago. We might expect, therefore, the nephrotoxicity rate to be a bit lower now that ddI and tenofovir are no longer used together.
One theoretical concern in regard to tenofovir safety is that it is boosted by some protease inhibitors, and the mechanism is not understood. These investigators looked to see whether the use of a protease inhibitor affected tenofovir toxicity, and they found no strong evidence for that. There was a very weak association on a univariate analysis, but when it was all adjusted, they found no association at all. That's not proof, but at least it's something that encourages us that it's not a major clinical problem in the absence of relevant data from randomized clinical trials.
Investigators from the WIHS cohort found that estimated GFR declined by approximately 10% to 15% in these women over a 3.5-year period. Only about 2% of women developed what clinicians might regard as a significant problem, with 10% to 15% showing a mild-to-moderate problem. There was no association in this study with either ddI or with tenofovir coadministered with protease inhibitors. Rather, the associations were with injection-drug use and concomitantly administered nephrotoxic drugs.
Medscape: HLA testing, particularly to try to predict abacavir hypersensitivity reactions, is a topic that is gaining increasing attention among researchers and clinicians in the field of HIV/AIDS. There were some data presented here at the workshop on the pre- versus posttesting experience. Could you tell us about that?
Dr. Carr: A group from Brighton in the United Kingdom reported on their experience in 561 treatment-naive and -experienced patients who started abacavir for the first time.[12] They had introduced the test after just over 300 patients had been exposed to abacavir. In the pretesting cohort, the prevalence of abacavir hypersensitivity was 6.2%. After the introduction of the test and the avoidance of abacavir in patients who were HLA B*5701-positive, the prevalence of hypersensitivity was 0.5%,which is a highly significant reduction.
There were 2 advantages of this cohort, which has generated very similar results to those from the Perth group in Western Australia. First, it's a larger sample — about twice the size. Second, it's a more ethnically diverse sample — about 20% non-white patients, which is a larger percentage than in the Perth cohort. Despite that greater diversity, the tests continued to perform well. This was not a randomized trial, but we now have 2 highly consistent results from cohorts with close to 1000 patients that show that the prevalence of abacavir hypersensitivity can, by and large, disappear with the use of this test.
Medscape: There have been pharmacogenomic differences observed between different ethnicities. Did they notice anything in this regard in this particular study?
Dr. Carr: They did find a few black patients who were positive on their test. Then, when they went to do more sophisticated genetic testing, they actually found that they didn't have B*5701; they had B*5703, which does not predispose to hypersensitivity. These were all variants of B*57, and that's important. So it will be important, if a provider chooses to use this test, to understand its nuances. If it's a broad, PCR-based test, for example, that just looks at HLA-B*57, then it will include B*5701 and it will probably include some other B*57 types. Some laboratories will take it a step further and they will sequence and be certain that it's B*5701 or not. In my mind, that's a preferable test, but it does add some cost and time to the test.
This test from Brighton didn't use sequencing, and so one would anticipate, based on what they found in a retrospective fashion, that if they had done sequencing, the test may have performed slightly better.
