Impact of Ceftolozane–Tazobactam vs. Best Alternative Therapy on Clinical Outcomes in Patients with Multidrug-Resistant and Extensively Drug-Resistant <i>Pseudomonas aeruginosa</i> Lower Respiratory Tract Infections

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Abstract

Introduction

Infections caused by multidrug-resistant (MDR), extensively drug-resistant (XDR), and difficult-to-treat (DTR) Pseudomonas aeruginosa are increasingly challenging to combat. Ceftolozane–tazobactam (C/T) is a novel β-lactam–β-lactamase inhibitor combination now commonly used to treat MDR and XDR P. aeruginosa. Lower respiratory tract infections (LRTIs) remain the most common source of infection caused by MDR/XDR P. aeruginosa. Comparative effectiveness studies to date have been limited by the type of comparator agents (i.e., aminoglycosides and polymyxins) and the inclusion of multiple infection sources (i.e., urinary tract, abdominal, skin and soft tissue, etc.).

Methods

We performed a multicenter, retrospective analysis of adults with LRTI caused by MDR or XDR P. aeruginosa admitted from January 2014 to December 2019. We aimed to compare clinical outcomes between patients who received C/T ( n = 118) versus best alternative therapy ( n = 88). The primary outcome was clinical failure, defined as 30-day mortality and/or an adverse drug reaction on antibiotic therapy.

Results

Two hundred and six patients met inclusion criteria. The C/T group had a significantly higher proportion of XDR P. aeruginosa and ventilator-associated bacterial pneumonia (VABP). After multivariable logistic regression, C/T treatment was independently associated with a 73.3% reduction in clinical failure compared to those who received best alternative therapy ( P < 0.001). The number needed to harm with best alternative therapy was 3.

Conclusion

Our results suggest that C/T is a safe and effective therapeutic regimen for patients with MDR and XDR P. aeruginosa LRTI.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40121-022-00687-9.

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Most cited references 20

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Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.

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Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.

A-P Magiorakos, A. Srinivasan, R.B. Carey … (2012)

Many different definitions for multidrug-resistant (MDR), extensively drug-resistant (XDR) and pandrug-resistant (PDR) bacteria are being used in the medical literature to characterize the different patterns of resistance found in healthcare-associated, antimicrobial-resistant bacteria. A group of international experts came together through a joint initiative by the European Centre for Disease Prevention and Control (ECDC) and the Centers for Disease Control and Prevention (CDC), to create a standardized international terminology with which to describe acquired resistance profiles in Staphylococcus aureus, Enterococcus spp., Enterobacteriaceae (other than Salmonella and Shigella), Pseudomonas aeruginosa and Acinetobacter spp., all bacteria often responsible for healthcare-associated infections and prone to multidrug resistance. Epidemiologically significant antimicrobial categories were constructed for each bacterium. Lists of antimicrobial categories proposed for antimicrobial susceptibility testing were created using documents and breakpoints from the Clinical Laboratory Standards Institute (CLSI), the European Committee on Antimicrobial Susceptibility Testing (EUCAST) and the United States Food and Drug Administration (FDA). MDR was defined as acquired non-susceptibility to at least one agent in three or more antimicrobial categories, XDR was defined as non-susceptibility to at least one agent in all but two or fewer antimicrobial categories (i.e. bacterial isolates remain susceptible to only one or two categories) and PDR was defined as non-susceptibility to all agents in all antimicrobial categories. To ensure correct application of these definitions, bacterial isolates should be tested against all or nearly all of the antimicrobial agents within the antimicrobial categories and selective reporting and suppression of results should be avoided. © 2011 European Society of Clinical Microbiology and Infectious Diseases. No claim to original US government works.

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Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis

(2022)

Summary Background Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen–drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date. Methods We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen–drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drug-resistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level. Findings On the basis of our predictive statistical models, there were an estimated 4·95 million (3·62–6·57) deaths associated with bacterial AMR in 2019, including 1·27 million (95% UI 0·911–1·71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27·3 deaths per 100 000 (20·9–35·3), and lowest in Australasia, at 6·5 deaths (4·3–9·4) per 100 000. Lower respiratory infections accounted for more than 1·5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000–1 270 000) deaths attributable to AMR and 3·57 million (2·62–4·78) deaths associated with AMR in 2019. One pathogen–drug combination, meticillin-resistant S aureus, caused more than 100 000 deaths attributable to AMR in 2019, while six more each caused 50 000–100 000 deaths: multidrug-resistant excluding extensively drug-resistant tuberculosis, third-generation cephalosporin-resistant E coli, carbapenem-resistant A baumannii, fluoroquinolone-resistant E coli, carbapenem-resistant K pneumoniae, and third-generation cephalosporin-resistant K pneumoniae. Interpretation To our knowledge, this study provides the first comprehensive assessment of the global burden of AMR, as well as an evaluation of the availability of data. AMR is a leading cause of death around the world, with the highest burdens in low-resource settings. Understanding the burden of AMR and the leading pathogen–drug combinations contributing to it is crucial to making informed and location-specific policy decisions, particularly about infection prevention and control programmes, access to essential antibiotics, and research and development of new vaccines and antibiotics. There are serious data gaps in many low-income settings, emphasising the need to expand microbiology laboratory capacity and data collection systems to improve our understanding of this important human health threat. Funding Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.

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Author and article information

Contributors

Dana J. Holger: dholger@wayne.edu

Michael J. Rybak:

ORCID: http://orcid.org/0000-0002-1094-043X

m.rybak@wayne.edu

Journal

Journal ID (nlm-ta): Infect Dis Ther

Journal ID (iso-abbrev): Infect Dis Ther

Title: Infectious Diseases and Therapy

Publisher: Springer Healthcare (Cheshire )

ISSN (Print): 2193-8229

ISSN (Electronic): 2193-6382

Publication date (Electronic): 1 September 2022

Publication date PMC-release: 1 September 2022

Publication date (Print): October 2022

Volume: 11

Issue: 5

Pages: 1965-1980

Affiliations

[1 ]GRID grid.254444.7, ISNI 0000 0001 1456 7807, Wayne State University, ; Detroit, MI USA

[2 ]GRID grid.254444.7, ISNI 0000 0001 1456 7807, Anti-Infective Research Laboratory, Department of Pharmacy Practice, Eugene Applebaum College of Pharmacy and Health Sciences, , Wayne State University, ; 259 Mack Avenue, Detroit, MI 48201 USA

[3 ]GRID grid.413103.4, ISNI 0000 0001 2160 8953, Department of Pharmacy, , Henry Ford Hospital, ; Detroit, MI USA

[4 ]GRID grid.412014.2, ISNI 0000 0004 0440 9591, Department of Pharmacy Services, , Detroit Receiving Hospital, Detroit Medical Center, ; Detroit, MI USA

[5 ]GRID grid.254444.7, ISNI 0000 0001 1456 7807, School of Medicine, , Wayne State University, ; Detroit, MI USA

[6 ]GRID grid.511699.3, ISNI 0000 0004 6487 6327, Present Address: Seres Therapeutics, ; Cambridge, MA 02139 USA

[7 ]GRID grid.259828.c, ISNI 0000 0001 2189 3475, Present Address: Department of Clinical Pharmacy and Outcomes Sciences, College of Pharmacy, , Medical University of South Carolina, ; Charleston, SC USA

[8 ]GRID grid.259828.c, ISNI 0000 0001 2189 3475, Present Address: Department of Pharmacy Services, , Medical University of South Carolina Shawn Jenkins Children’s Hospital, ; Charleston, SC USA

Author information

Michael J. Rybak http://orcid.org/0000-0002-1094-043X

Article

Publisher ID: 687

DOI: 10.1007/s40121-022-00687-9

PMC ID: 9617978

PubMed ID: 36048335

SO-VID: ee03b07a-ab9c-4af3-919b-6cb9da5b1e3e

License:

Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.

History

Date received : 11 July 2022

Date accepted : 5 August 2022

Custom metadata

Keywords: ceftolozane–tazobactam,habp/vabp,multidrug resistance,pneumonia,pseudomonas aeruginosa

Data availability:

Keywords: ceftolozane–tazobactam, habp/vabp, multidrug resistance, pneumonia, pseudomonas aeruginosa

Impact of Ceftolozane–Tazobactam vs. Best Alternative Therapy on Clinical Outcomes in Patients with Multidrug-Resistant and Extensively Drug-Resistant Pseudomonas aeruginosa Lower Respiratory Tract Infections

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Abstract

Introduction

Methods

Results

Conclusion

Supplementary Information

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European Respiratory Society: COVID-19

Most cited references 20

Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.

Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis

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