The information provided by genotypic resistance assays may be difficult to interpret. Current knowledge on the correlation between the genotypic and phenotypic characteristics of an HIV-1 isolate is mainly based on in vitro studies of laboratory and clinical HIV-1 strains. The clinical relevance of mutations is also determined from linking mutation patterns with previous therapy history or from linking them with subsequent therapy response. A decade ago, when monotherapy was the standard-of-care, the direct linkage between mutations, therapy experience, and subsequently therapy response was more clear-cut than in the current HAART situation. The potency of new drugs is now investigated in ''add-on'' studies, where the new drug is added to the failing regimen. More recently, this strategy has encountered ethical problems because of the possibility that it could lead into fast resistance development against the new drug. An increasing number of efficiency studies are performed with combinations of the new drug and at least one other suspected active compound. This hampers the understanding of the impact of preexisting resistance and the subsequent viral response to the new drug.

Patients are currently treated with combination therapies that change in time and that result in complex patterns of mutations. The phenotypic effects of mutations and their interactions often cannot be reliably predicted. Some mutations that are developed under the selective pressure of a particular drug can cause resistance toward other drugs from the same class without any previous experience (cross-resistance), and others might reverse the phenotypic resistance level of certain resistance mutations. Phenotypic resistance assays give a direct measurement of susceptibility toward the tested inhibitors that includes the effect of all mutations and their interactions. However, the clinical relevance of pheno-typic results can also be difficult to interpret because the threshold at which a specific inhibitor becomes ineffective in vivo has not been determined yet for all available drugs.

The investigation of the correlation between genotype and phenotype has resulted into the development of genotypic-phenotypic relational databases and rule-based algorithms.[5] These systems can be helpful in the interpretation of in vivo resistance. Large datasets containing matched genotypes and phenotypes are already used to predict phenotype from genotype. Rule-based algorithms contain lists of mutations that are: 1) known to confer phenotypic resistance toward a particular drug; 2) known to be part of a mutation pathway toward highlevel resistance; 3) and, most importantly, responsible for a reduced clinical response.[6]

At the moment, several interpretation algorithms are available. They give concordant results in most cases. The observed discordances reflect the uncertainty that is still associated with particular set of mutations.[7]

These algorithms should be subject to regular updates as soon as new correlations between genotype and phenotype are established and the clinical relevance of certain genotypes and phenotypes become evident.

From the time antiretroviral drugs were first used in the treatment of HIV-1 infection, it was observed that in many cases therapy failure was associated with the development of resistance mutations at the genetic level and decreases in drug susceptibility at the phenotypic level. Only a few years ago, after the effect of resistance on subsequent therapy failure was investigated in retrospective studies, the idea to prospectively use the results from genotypic and phenotypic resistance assays in the management of HIV-1 infection was incorporated into the design of clinical trials. In these trials, viral response on therapy guided by genotypic and/or phenotypic resistance results was compared to that during standard-of-care. In some of these prospective trials, access to genotypic or phenotypic drug resistance results led into a short-term, modest viral benefit. In other studies, the effect of resistance testing was attenuated as a consequence of many factors.

The absence of resistance does not always result into therapy response because success is a result of many factors besides antiviral resistance, such as adherence, potency, and pharmacological reasons. It has also been shown that the interpretation of the raw resistance data plays an important role in the successful implementation of resistance testing.[8] It is recommended that the interpretation should be left to experts. These experts can translate the data into recommendations that are useful for clinicians. Another limitation of the use of drug resistance assays in the clinical management of HIV-1 infection is the limited choice of drugs in the treatment of HIV-1 patients who have undergone extensive therapy with multiple failures.[9] Because of the existing cross-resistance within drug classes, a badly managed combination therapy could result into broad cross-resistance toward all available drugs, even if these respective drugs had not been previously used. Whether or not the choice of subsequent therapy is then guided by resistance testing has no longer any relevance, because there remains only limited or no option at all.

Nevertheless, resistance testing has demonstrated its advantages and has been implemented into guidelines.[10-12] It is recommended for primary and recent HIV-1 infection, before initiation of therapy in chronically infected patients if infected within the past 2 years, or in areas with high resistance prevalence, first or multiple therapy failure, and pregnancy.

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Getting Started With Dumbbells

Getting Started With Dumbbells

The use of dumbbells gives you a much more comprehensive strengthening effect because the workout engages your stabilizer muscles, in addition to the muscle you may be pin-pointing. Without all of the belts and artificial stabilizers of a machine, you also engage your core muscles, which are your body's natural stabilizers.

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