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September 20, 2022 08:05pm
By Erin Hunter, Assistant Editor
Although many retail clinicians treat their patientsâ€™ infections by prescribing them the highest tolerable dose of antibiotics, this may not be the best practice for preventing the evolution of drug-resistant diseases.
Although many retail clinicians treat their patients’ infections by prescribing them the highest tolerable dose of antibiotics, this may not be the best practice for preventing the evolution of drug-resistant diseases.
Researchers recently developed a mathematical model intended to quantify the primary factors that contribute to the evolution of drug resistance in disease-causing microbes. In designing the model, they identified 2 evolutionary forces in particular: the frequency at which drug resistance arises in the microbes through genetic mutation, and the ability of microbes carrying those mutations to survive and multiply.
The researchers found that high doses of medications often succeeded at combating the first of these evolutionary processes by killing microbes before they could reproduce; however, this approach was not always effective and could potentially exacerbate a disease’s drug resistance.
“There is nothing in evolutionary theory that says that the dogma of hitting infections hard with high doses of medication should be the best rule of thumb to prevent drug resistance,” said researcher Andrew Read, PhD, in a press release. “Our analysis demonstrates that although the traditional 'hit hard' approach often works, in some cases, it also can be the very worst thing to do.”
Dr. Read elaborated that high doses of medications can allow even a small amount of drug-resistant microbes to thrive and multiply by killing the drug-sensitive microbes with which they compete.
“One of the main reasons drug-resistant microbes are rare is that they are in direct competition for resources with their drug-sensitive neighbors,” Dr. Read explained. “High doses of medication can quickly eliminate this competition for resources, allowing drug-resistant microbes to thrive.”
Given his team’s findings, Dr. Read suggested that the best way for clinicians to prevent the evolution of drug-resistant microbes may be to prescribe either a medication’s highest safe dose or its lowest effective dose based on a careful consideration of each patient’s individual condition.
“Determining which is the best approach for a given infectious agent will need to be done on a case-by-case basis in clinical trials,” Dr. Read stated. “By definition, both will make the patient better in the short term, but we don't know ahead of time which course of action will be best for preventing the evolution of resistance, which leads to more problems in the long term.”
While further research may be needed to establish best practices for preventing drug resistance, retail clinicians can still play a role in slowing this evolution.
For example, one particularly noteworthy source of drug resistance is the overprescribing of antibiotics. According to data from the US Centers for Disease Control and Prevention (CDC), up to 50% of antibiotic prescriptions areunnecessary or inappropriatein the outpatient setting.
In response to this trend, the CDC and American College of Physicians (ACP) recently publishedrecommendationson appropriate antibiotic use for clinicians to consider when treating patients with acute upper respiratory tract infections. Emphasizing the importance ofantibiotic stewardship, the ACP and CDC encouraged clinicians to use their best judgment when prescribing these medications.
“Although it is everyone's responsibility to use antibiotics appropriately, providers have the power to control prescriptions,” the organizations wrote. “Reducing inappropriate antibiotic prescribing will improve quality of care, decrease health care costs, and preserve the effectiveness of antibiotics.”
The fight against drug-resistant diseases has even reached the White House. In September 2014, President signed a 5-yearexecutive action, the National Action Plan for Combating Antibiotic-Resistance Bacteria, in an attempt to better understand and ultimately curb the evolution ofantibiotic resistance.
The research on which Dr. Read and his colleagues’ model was based was published inPLOS Computational Biology, while the CDC and ACP’s recommendations appeared in theAnnals of Internal Medicine.