Active Ingredients: Azithromycin
Overall, apart from cryptococcal infections, combined antifungal therapy is not significantly better than monotherapy in terms of clinical efficacy.
It is questionable whether combination therapy should be used in most cases as there is a lack of evidence from well-designed clinical trials. However, combination therapy could be an alternative to monotherapy for patients with invasive infections that are difficult to treat, such as those due to multi-resistant species and for those who fail to respond to standard treatment.
The antifungal therapies that are currently available exhibit limited effectiveness and a complete response depends mainly on correction of the underlying disease.
The increase in available antifungal compounds has prompted the search for better therapeutic strategies, such as using the newer antifungal agents in combination.
Antifungal compounds used in combination might promote the effectiveness of each drug, with efficacy being achieved using a lower dose of each drug.
Pharmacological benefits would accrue, with one drug clearing infection from one body system while the other clears it from a different site. In addition, combination therapy could be utilized in an attempt to prevent or delay the emergence in vivo of resistant populations of the pathogenic fungus.
There are no data from clinical trials regarding the safety and efficacy of combination therapy.
In fact, large and expensive clinical trials are required to show significant differences between adverse events and the efficacy of a given combination compared with those of the monotherapy, but these are unlikely to take place in the current climate of budgetary restraints.
The review is divided into three sections, in which combinations of various antifungal agents are discussed. Combination studies in vitro Susceptibility testing of combinations of antifungal agents has yielded conflicting results due mainly to the different methodologies used, such as agar dilution, agar diffusion and broth dilution.
The chequerboard method and the killing curves technique are most frequently used to assess antimicrobial combinations in vitro.
The term chequerboard refers to the pattern, tubes or microtitration trays, formed by testing two antifungal agents, in concentrations several dilutions above and below the MICs for the fungi being tested.
The method has been used almost exclusively for determining the inhibitory concentration Figure 1. This technique has been used for testing fungicidal agents such as amphotericin B, but the repetitive counting of colony-forming units that the technique entails is labour intensive, tedious and seriously limits the number of antifungal concentrations and combinations that can be tested at any one time.
In vitro techniques Chequerboard dilutions can be readily performed in clinical laboratories using microdilution or macrodilution systems, are easier to standardize and thus are more commonly reported.
Although the dilutions used in the chequerboard are exponential, typically two-fold dilutions, the results are interpreted by the pattern they form on an isobologram, which displays fractional inhibitory concentration indices FICI on an arithmetic scale.
A single FICI is the most common way in medical mycology to report the results of studies with chequerboard dilutions, and is the lowest concentration of each drug that inhibits growth. To begin with, controversial results can be obtained depending on the criteria used to evaluate the antifungal interaction, such as MIC endpoint definition, assay medium, reading method and analysis of results.
A second flaw to consider is that the FICI calculation assumes incorrectly that all antimicrobial compounds have linear dose-response curves, providing a static, all-or-none view of antimicrobial interaction, creating artificial FICs.Uses Azithromycin is used to treat a wide variety of bacterial infections.
They rely on the response surface approaches generated by the three-dimensional nature of antimicrobial interactions, in contrast to the one-dimensional FICI. The drug effect is measured by the proportion of growth with respect to a drug-free control and is related to any drug combination, generating a surface when this relationship is plotted three dimensionally.
Response surface models incorporate interaction parameters, as well as the uncertainty of the estimates, by taking into account the variation of the data.