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Minimum inhibitory concentration (MIC) results can play an important role in fighting antimicrobial resistance (AMR) and in guiding optimal clinical decisions. It’s too important to fail, but there is still some uncertainty about the best way to generate results.

While some approaches extrapolate from minimal data points, Thermo Fisher Scientific firmly believes a more “definitive” MIC is the only way to be sure. The phrase “true MIC” has been used to describe each of these methods at various times, but it is worth noting that the term has no grounding in the literature.

So, when does true mean true, what is a “definitive” MIC, and how does it provide the best path to right-first-time decisions?

MIC, AMR, and patient care

An MIC, defined as the lowest concentration of an antimicrobial that will inhibit the visible growth of a microorganism after incubation, is a quantitative method of antimicrobial susceptibility testing (AST). It is important for two reasons.

Firstly, it is a key weapon in the war against AMR. While some degree of antimicrobial resistance is inevitable, the misuse and overuse of some agents is contributing to the global emergency that threatens to cause 10 million deaths a year by 2050.1

As much as new medicines are needed, tackling this crisis also relies on stewardship, or ensuring existing antimicrobials are used only when necessary, and in the smallest possible volumes, said Cindy Knapp, director of R&D, AST and pharma, Microbiology at Thermo Fisher Scientific.

On the individual patient level, antibiotics come with side effects. These can include vomiting and diarrhea, and some agents can cause skin photosensitivity, muscle or joint pain, heart palpitations or even severe liver damage. Importantly, depending on the antimicrobial, the risk of this occurring may increase with higher doses.2

Jeroen Bursens, Thermo Fisher Scientific Microbiology’s EU clinical equipment manager, said: “This is why MIC calculations are vital for protecting individual patients and society alike. Inaccurate results negatively affect antimicrobial stewardship programs and the ability to guide optimal clinical decisions.”

Gold standard

The medical community, including the Clinical and Laboratory Standards Institute (CLSI) and International Organization for Standardization (ISO) are united on the importance of an MIC result in fighting AMR and guiding patient care.

The reference standard is clear; Using a 96- or 384-well wet or frozen panel, technicians prepare multiple two-fold broth dilutions of the antimicrobial. The wells are incubated with the target organism at appropriate colony forming units (CFU) levels, and then incubated for 16 to 24 hours, depending on the isolate. The level of growth in each well is then read manually, and this information used to determine the MIC.

There remains, however, some ambiguity in the best way to obtain a gold standard-equivalent result from a commercial system.

Extrapolate or observe?

The currently available approaches can be broadly divided by the way in which they calculate post-incubation growth levels. Some use algorithms to extrapolate results from an incomplete dataset, whereas others streamline microbiological processes to arrive at observed, definitive results efficiently.

In extrapolation method systems, algorithms are trained to understand the growth patterns of target microorganisms under appropriate conditions. Growth is then measured at a set point during incubation, and the results fed through a statistical model which calculates the likely continued growth at endpoint. It is extremely accurate in many scenarios, but it has its limitations and, like any algorithm-based technology, is only as good as the data it holds.

The models are based on a subset of isolates that may not be relevant to the clinical case in hand and have no way of recognizing new kinetic models of growth, such as those influenced by resistance mechanisms. It means laboratories are unable to identify or track signs of emerging resistance and places a certain degree of uncertainty on the guidance of clinical decisions, said Bursens.

“The problem with non-definitive devices is you don't know how the kinetic model becomes influenced by different resistance mechanisms. Resistance mechanisms occur continuously and there is also a lot of synergy between different resistance mechanisms,” he added.

“The curves may have been a good fit for the organisms that were used in the development of the algorithm. But new resistance mechanisms come with new methods for those resistance mechanisms to interact, and this will have a creep on the accuracy of the result.”

Definitive detection, such as that utilized by the Thermo Scientific™ Sensititre™ System, uses microbroth dilution to closely align to the reference method. This generates observable, quantitative, endpoint results even if the isolate behaves unpredictably in the presence of antibiotics, said Knapp.

“This broth dilution, observable growth approach is a very similar process and procedure to the reference method, making it a lot more robust,” she added.

When is a true MIC not a true MIC?

We don’t know what we don’t know, meaning the only true MIC result is one that gives us the full picture.

It is one that utilizes an approach that mirrors the reference standard, using a minimum of four two-fold, sequential dilutions. It is, in essence, one that arrives at robust, observable results.

Unlike extrapolated MIC results, definitive MIC results deal only with the facts related to each unique sample and situation, providing all the information laboratories and medical teams need to support stewardship efforts and guide quality patient care.


References

  1. No time to wait: Securing the future from drug-resistant infections. (2019). The Interagency Coordination Group (IACG) on Antimicrobial Resistance. https://www.who.int/antimicrobial-resistance/interagency-coordination-group/IACG_final_summary_EN.pdf?ua=1 
  2. Tamma, P. D., Avdic, E., Li, D. X., Dzintars, K., & Cosgrove, S. E. (2017). Association of adverse events with antibiotic use in hospitalized patients. JAMA internal medicine, 177(9), 1308-1315.

 

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