Effect of Algorithm-Based Therapy vs Usual Care on Clinical Success and Serious Adverse Events in Patients with Staphylococcal Bacteremia: A Randomized Clinical Trial.

Abstract

Importance

The appropriate duration of antibiotics for staphylococcal bacteremia is unknown.

Objective

To test whether an algorithm that defines treatment duration for staphylococcal bacteremia vs standard of care provides noninferior efficacy without increasing severe adverse events.

Design, setting, and participants

A randomized trial involving adults with staphylococcal bacteremia was conducted at 16 academic medical centers in the United States (n = 15) and Spain (n = 1) from April 2011 to March 2017. Patients were followed up for 42 days beyond end of therapy for those with Staphylococcus aureus and 28 days for those with coagulase-negative staphylococcal bacteremia. Eligible patients were 18 years or older and had 1 or more blood cultures positive for S aureus or coagulase-negative staphylococci. Patients were excluded if they had known or suspected complicated infection at the time of randomization.

Interventions

Patients were randomized to algorithm-based therapy (n = 255) or usual practice (n = 254). Diagnostic evaluation, antibiotic selection, and duration of therapy were predefined for the algorithm group, whereas clinicians caring for patients in the usual practice group had unrestricted choice of antibiotics, duration, and other aspects of clinical care.

Main outcomes and measures

Coprimary outcomes were (1) clinical success, as determined by a blinded adjudication committee and tested for noninferiority within a 15% margin; and (2) serious adverse event rates in the intention-to-treat population, tested for superiority. The prespecified secondary outcome measure, tested for superiority, was antibiotic days among per-protocol patients with simple or uncomplicated bacteremia.

Results

Among the 509 patients randomized (mean age, 56.6 [SD, 16.8] years; 226 [44.4%] women), 480 (94.3%) completed the trial. Clinical success was documented in 209 of 255 patients assigned to algorithm-based therapy and 207 of 254 randomized to usual practice (82.0% vs 81.5%; difference, 0.5% [1-sided 97.5% CI, -6.2% to ∞]). Serious adverse events were reported in 32.5% of algorithm-based therapy patients and 28.3% of usual practice patients (difference, 4.2% [95% CI, -3.8% to 12.2%]). Among per-protocol patients with simple or uncomplicated bacteremia, mean duration of therapy was 4.4 days for algorithm-based therapy vs 6.2 days for usual practice (difference, -1.8 days [95% CI, -3.1 to -0.6]).

Conclusions and relevance

Among patients with staphylococcal bacteremia, the use of an algorithm to guide testing and treatment compared with usual care resulted in a noninferior rate of clinical success. Rates of serious adverse events were not significantly different, but interpretation is limited by wide confidence intervals. Further research is needed to assess the utility of the algorithm.

Trial registration

ClinicalTrials.gov Identifier: NCT01191840.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1001/jama.2018.13155

Publication Info

Holland, Thomas L, Issam Raad, Helen W Boucher, Deverick J Anderson, Sara E Cosgrove, P Suzanne Aycock, John W Baddley, Anne-Marie Chaftari, et al. (2018). Effect of Algorithm-Based Therapy vs Usual Care on Clinical Success and Serious Adverse Events in Patients with Staphylococcal Bacteremia: A Randomized Clinical Trial. JAMA, 320(12). pp. 1249–1258. 10.1001/jama.2018.13155 Retrieved from https://hdl.handle.net/10161/29854.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Holland

Thomas Lawrence Holland

Professor of Medicine
Anderson

Deverick John Anderson

Professor of Medicine

Hospital epidemiology, infection control, antibiotic stewardship, multidrug-resistant organisms, device-related infections, surgical site infections, catheter-associated bloodstream infections, cost of infections, infections in community hospitals

Chow

Shein-Chung Chow

Professor of Biostatistics & Bioinformatics

My research interest includes statistical methodology development and application in the area of biopharmaceutical/clinical statistics such as bioavailability and bioequivalence, clinical trials, bridging studies, medical devices, and translational research/medicine. Most recently, I am interested in statistical methodology development for the use of adaptive design methods in clinical trials and methodology development for assessment of biosimilarity of follow-on biologics. In addition, I am also interested in methodology development for statistical evaluation of traditional Chinese medicine (TCM) clinical trials.

Chu

Vivian Hou Chu

Professor of Medicine

Dr. Chu's clinical research is focused on staphylococci and endocarditis (IE).  She is the director of the International Collaboration on Endocarditis (ICE), a group of investigators from 78 sites in 32 countries worldwide that is dedicated to further the understanding of infective endocarditis.  The ICE database comprises > 5000 cases of endocarditis and is designed to answer questions that could not be answered from a single-center study. The current focus of this group is surgical-decision making in the treatment of endocarditis. Another major focus of Dr. Chu's research is on the relationship between oral hygiene and risk for developing infective endocarditis.

Carugati

Manuela Carugati

Associate Professor of Medicine
Chamis

Anna Lisa Chamis

Professor of Medicine
Fowler

Vance Garrison Fowler

Florence McAlister Distinguished Professor of Medicine

Determinants of Outcome in Patients with Staphylococcus aureus Bacteremia
Antibacterial Resistance
Pathogenesis of Bacterial Infections
Tropical medicine/International Health


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