The path of least resistance: aggressive or moderate treatment?

Kouyos, Roger D.; Metcalf, C. Jessica E.; Birger, Ruthie; Klein, Eili Y.; Wiesch, Pia Abel zur; Ankomah, Pierre; Arinaminpathy, Nimalan; Bogich, Tiffany L.; Bonhoeffer, Sebastian; Brower, Charles; Chi-Johnston, Geoffrey; Cohen, Ted; Day, Troy; Greenhouse, Bryan; Huijben, Silvie; Metlay, Joshua P.; Mideo, Nicole; Pollitt, Laura C.; Read, Andrew F.; Smith, David L.; Standley, Claire J.; Wale, Nina; Grenfell, Bryan T.

doi:10.1098/rspb.2014.0566

Cited by 87 publications

(127 citation statements)

References 64 publications

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“…These include the overall prevalence of single-resistant strains before multidrug resistance emerges and the relative order in which different singleresistant strains appear. Previous work has questioned the orthodoxy that "aggressive" antimicrobial chemotherapy is optimal for preventing resistance (43,50). If we consider that one aspect of treatment aggressiveness is the extent of drug penetration, then our model demonstrates the complexities involved in answering this question and motivates further work aimed at estimating the size of drug-protected compartments for relevant combination therapies.…”

Section: Discussionmentioning

confidence: 87%

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Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multidrug resistance

Moreno-Gámez

Hill

Rosenbloom

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

134

149

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Infections with rapidly evolving pathogens are often treated using combinations of drugs with different mechanisms of action. One of the major goal of combination therapy is to reduce the risk of drug resistance emerging during a patient’s treatment. Although this strategy generally has significant benefits over monotherapy, it may also select for multidrug-resistant strains, particularly during long-term treatment for chronic infections. Infections with these strains present an important clinical and public health problem. Complicating this issue, for many antimicrobial treatment regimes, individual drugs have imperfect penetration throughout the body, so there may be regions where only one drug reaches an effective concentration. Here we propose that mismatched drug coverage can greatly speed up the evolution of multidrug resistance by allowing mutations to accumulate in a stepwise fashion. We develop a mathematical model of within-host pathogen evolution under spatially heterogeneous drug coverage and demonstrate that even very small single-drug compartments lead to dramatically higher resistance risk. We find that it is often better to use drug combinations with matched penetration profiles, although there may be a trade-off between preventing eventual treatment failure due to resistance in this way and temporarily reducing pathogen levels systemically. Our results show that drugs with the most extensive distribution are likely to be the most vulnerable to resistance. We conclude that optimal combination treatments should be designed to prevent this spatial effective monotherapy. These results are widely applicable to diverse microbial infections including viruses, bacteria, and parasites.

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Section: Discussionmentioning

confidence: 87%

“…The choice of antimicrobial therapy generally presents a tradeoff between maximizing clinical efficacy and minimizing the chance that drug resistance emerges (43). The spatial setting introduces new dimensions to this trade-off.…”

Section: Trade-off Between Halting Pathogen Growth and Preventing Resmentioning

confidence: 99%

Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multidrug resistance

Moreno-Gámez

Hill

Rosenbloom

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

134

149

View full text Add to dashboard Cite

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“…Different chemotherapeutic protocols (e.g., combination versus mono therapy (1), synergistic versus antagonistic drug combinations (2–4), and high versus low drug concentration (5–9)) result in different likelihoods of resistance emergence. This is because such protocols affect the likelihood of resistant genotypes appearing through mutation, as well as the fitness of resistant and wild type genotypes once they have appeared.…”

Section: Evolutionary Emergence Of Resistancementioning

confidence: 99%

Is selection relevant in the evolutionary emergence of drug resistance?

Day

Huijben

Read

2015

Trends in Microbiology

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113

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The emergence of drug resistant pathogens is often considered a canonical case of evolution by ‘natural’ selection. Here we argue that the strength of selection can be a poor predictor of the rate of resistance emergence. It is possible for a resistant strain to be under negative selection and still emerge in an infection or spread in a population. Measuring the right parameters is a necessary first step towards the development of evidence-based resistance management strategies. We argue that it is the absolute fitness of the resistant strains that matters most, and that a primary determinant of the absolute fitness of a resistant strain when it arises is the ecological context in which it finds itself.

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“…Although there is considerable empirical work on how drug dosing potentially affects treatment outcome (for literature survey, see [37]), it does not provide a clear signal as to whether "hit hard" approaches are superior to alternative dosing schedules [39]. For example, Negri and coworkers [39,40] demonstrated how strains of E. coli with different levels of resistance to the antibiotic cefotaxime persisted at different drug doses.…”

Section: Dosingmentioning

confidence: 99%

“…For example, Negri and coworkers [39,40] demonstrated how strains of E. coli with different levels of resistance to the antibiotic cefotaxime persisted at different drug doses. They identified the "selective window": doses that eliminate sensitive strains and favor relatively resistant ones.…”

Section: Dosingmentioning

confidence: 99%

Six wedges to curing disease

Hochberg

2017

Preprint

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Abstract.One of the great challenges in ecology and evolutionary biology is to explain disease, whether caused by infectious agents such as parasites and pathogens, or by the deterioration or transformation of cellular behavior and function, a prime example of the latter being cancer. Decades of observation and research suggest that successfully treating disease requires insights into how the environment mediates the interactions between disease causing agents (DCAs) and diseased individuals. A major finding is that single factor, targeted therapies are not only likely to fail in controlling or eradicating many DCAs, but are also likely to select for resistance, reducing options for subsequent treatment attempts, and in cases of infectious DCAs, rendering therapeutic agents (e.g., antibiotics) obsolete.I argue that meeting the growing challenge of treating disease in agriculture and animal husbandry, in protected and domesticated species, wildlife, and in the human population will require a fundamental understanding of ecological interactions at sites of infection or disease. I discuss different ways in which components of such disease ecosystems mediate DCA and therapeutic dynamics and resistance evolution, and derive a very simple mathematical criterion for therapeutic success. I then touch on how fundamental insights as revealed by the processes of evolutionary rescue and competitive release can help understand why therapies succeed or fail. Finally, I present six "wedges" that can each contribute alone, or as part of multi-pronged approaches to successfully treating disease. The Magic BulletDespite remarkable progress in prevention and treatment, the impacts of diseases in agriculture and animal husbandry, and on protected and domesticated species, wildlife, and human health are likely to intensify into the 21 st century. Humans in particular are increasingly in contact with each other and with wildlife, treated with drug regimens that select for resistance, and adopt life-styles or are exposed to environments that render them more susceptible to infectious diseases and more likely to get cellular diseases such as cancers.For many clinicians the Holy Grail is to discover the Ehrlichian "Magic Bullet"-a drug that will target the disease-causing agents (DCAs) and cure disease. Intuitively, the most effective way to reduce DCAs is to "hit hard and fast". That is, more drug means more kill within the tolerance limits of the patient. Rapid administration of the drug means forestalling further DCA growth and associated symptoms, but also reducing the probability of the appearance of resistant mutant strains. Despite decades of research on pest and disease control (much of it with an ecological basis) this approach and the many alternatives described below remain highly controversial (e.g., [1]).The Magic Bullet may be shortsighted for another reason. What will cure most patients may not be optimal for the general population in which resistant variants may emerge and spread 1 . This problem is in many ways similar...

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The path of least resistance: aggressive or moderate treatment?

Cited by 87 publications

References 64 publications

Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multidrug resistance

Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multidrug resistance

Is selection relevant in the evolutionary emergence of drug resistance?

Six wedges to curing disease

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