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Strategies for Drug Selection: Growing Insight into Resistance Mutations

This report is based on medical evidence presented at sanctioned medical congress, from peer reviewed literature or opinion provided by a qualified healthcare practitioner. The consumption of the information contained within this report is intended for qualified Canadian healthcare practitioners only.

Congrès Synergie et Résistances

Aix-en-Provence, France / October 26-27, 2006

The goal of antiretroviral therapy (ART) in all patients, whether they are receiving the first or fifth regimen, is to reduce the viral load (VL) <50 HIV RNA copies/mL. This level of suppression is associated with a low risk of resistance mutations that lead to regimen failure. Although a VL <400 copies/mL was once considered acceptable, new data suggest that the threshold for a risk of resistance mutations from continuing HIV replication may begin as low as 100 copies/mL. Due to fear of resistance, a more aggressive approach is being applied to failing regimens. Indeed, it is now being suggested that a switch should be considered even within the first months of a new regimen if VLs are not falling with sufficient speed.

Predictions at Six Months

According to Dr. Isabelle Pellegrin, Laboratoire de virologie, Centre hospitalier universitaire, Bordeaux, France, who is citing a study by Smith et al (J Acquir Immune Defic Syndr 2004;1155-9), “Response at the end of the first month correlates very closely with the likelihood of reaching a VL of <50 copies/mL at the end of six months.” She observed that 84% of patients have a VL <50 copies/mL at six months if a new regimen had achieved a VL <1000 copies/mL by one month, but the proportion fell to 61% if the load at one month was between 1000 and 10,000 copies/mL, 37% if the VL was between 10,000 and 100,000 copies/mL, and 24% for those with a VL >100,000 copies/mL at one month. In determining why regimens fail, the key resistance mutations are now well established for most ARTs, but new progress is being made to better understand how these mutations affect other agents in the current or future regimens, including risk of cross-resistance. For example, abacavir (ABC) and tenofovir (TDF) are among the two most potent nucleoside reverse transcriptase inhibitors (NRTIs), but their resistance profiles are very different. For ABC, thymidine analog mutations (TAMs) play a major role in conferring resistance, while K65R is the key mutation for TDF. Findings suggesting an antagonism between these mutations at the genomic level have important implications for drug selection. Much of the data regarding cross-resistance from one NRTI to another was derived from a series of trials evaluating NRTI regimens, which were found insufficiently potent for most patients.

In one such study of a NRTI regimen consisting of ABC, TDF, and lamivudine, as cited by Dr. Réjean Thomas, President, Clinique l’Actuel, Montreal, Quebec (Delaunay et al. J Virol 2005;79:9572-8), the most rapid resistance mutation was selection for K65R. By week 4, 10% of isolates had acquired K65R, 65% by week 12. Although a mutation that is driven by TDF, it conferred cross-resistance to the other NRTIs. Conversely, TAMs associated with ABC are not only associated with little resistance to TDF. Genomic antagonism between TAMs and K65R reduce the risk of this mutation from developing. In another study cited by Dr. Thomas, K65R was found to develop rapidly and was present in more than half of patients, in the absence of TAM. In patients infected with HIV who already had a TAM, only 4% developed K65R. Similar antagonism was reported by Parikh et al. (J Infect Dis 2006;194:651-60) in a database of 59,262 patient genotypes,where less than 1% of isolates had both TAMs and a K65R mutation.

Relative Risk of K65R Differs by HIV Type

However, recent data suggest that the relative risk of specific mutations, including K65R, differs for the type of HIV. According to Dr. Thomas, K65R is substantially less common for type B infections than for type C. In some parts of Africa, such as Botswana, where a large proportion of patients have type C infection, he suggested that TDF is likely to be at a substantial disadvantage. In his own clinic, Dr. Thomas reported that TDF is rarely used first-line because of concerns about cross-resistance to other NRTIs, including ABC, 3TC, didanosine, emtricitabine and stavudine.

Interpatient differences in pharmacokinetics have long been an area of controversy, particularly because of the risk of low drug levels that permit sufficient viral replication to lead to resistance. Some experts advocate routine therapeutic drug monitoring (TDM) to verify that drug exposure remains above established minimum drug concentrations (Cmin).This is an attractive approach to ensure drug efficacy, particularly in high-risk subgroups, such as those with a high VL or those with a slow response to therapy. However, it may be important to consider TDM in the context of body parts. This issue is important for patients who are pregnant, have central nervous system (CNS) symptoms of HIV infection, such as cognitive impairment, or whose semen level of HIV poses a high risk in the event of unsafe sex. Although it has never been proven that patients with these symptoms will do better with drugs that have a relatively high degree of penetration into these parts, this has been a reasonable assumption.

“When the CNS:plasma ratios are calculated, there are very different rates of exposure. Of the protease inhibitors, indinavir provides one of the best ratios and among NRTIs, lamivudine has a particularly high penetration,” reported Dr. Gianni di Perri, University of Turin, Italy. He acknowledged that measuring blood levels in parts of the body, such as the CNS, male and female genitals, placenta and breasts are difficult to perform on a routine basis, but this may deserve further study. He noted, for example, that drug levels of lopinavir/ritonavir fall sufficiently in the third trimester that dose adjustments may be appropriate.

Discordant Resistance Patterns by Body Parts

He also reported that there are cases in which HIV isolated from semen has demonstrated a resistance pattern that is different from HIV isolated from the plasma. Similar observations were made by Dr. Jade Ghosn, Laboratoire de virologie, Centre hospitalier universitaire de Bicêtre et Hôpital Necker, Kremlin-Bicêtre, France.

“We have found discordant resistance patterns in the CNS and blood as well as in the semen and blood,” Dr. Ghosn told the audience. Although he reported that most patients who have a low VL in the blood also have a low VL in the semen, he observed that the exceptions might be significant. For example, the presence of sexually transmitted diseases other than HIV is associated with higher replication rates in the genitals.

Importantly, resistance is relative and not wholly predictable in the presence or absence of specific mutations. Dr. Victor de Grutolla, Harvard University, Boston, Massachusetts, is working on developing algorithms to translate genotypic resistance into a predictor of phenotypic resistance. He noted that several very different methodologies have been developed, including those at his own institution, but accuracy differs very little even though different variables are being used. He suggested that the methodologies so far seem to be limited by missing information, such as specifics of drug metabolism among different types of patients.

Concurred Dr. Dominique Costagliola, Epidemiology Clinic, Université Pierre et Marie Curie, Paris, “The genotype profile of HIV is just one element to consider when changing therapy. We must constantly re-evaluate the rules of resistance testing because we are still defining what variables affect results.”

Summary

The therapeutic goal in treatment-experienced HIV-infected patients, as in HIV patients who are treatment-naïve, is a VL <50 HIV RNA copies/mL. Although resistance testing is becoming a standard of care, the presence of resistance mutations do not provide a definitive answer for drug selection in the absence of other considerations. While progress is being made, the rules of optimal drug selection remain in a state of evolution.

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