Abstract
Objective: Many clinical microbiology laboratories procure antimicrobial susceptibility testing data using guidelines established by Clinical and Laboratory Standards Institute (CLSI). When necessary, CLSI revises interpretive breakpoints in efforts to improve clinical correlation, with two revisions relative to fluoroquinolone agents occurring in 2019. The purpose of this investigation was to determine the impact of fluoroquinolone breakpoint revisions on Wisconsin clinical isolates of Escherichia coli, Proteus mirabilis, and Pseudomonas aeruginosa.
Design: Multi-center laboratory surveillance, with testing at a single location utilizing standardized media and susceptibility testing protocols.
Methods: From the Surveillance of Wisconsin Organisms for Trends in Antimicrobial Resistance and Epidemiology (SWOTARE) program, levofloxacin and ciprofloxacin minimum inhibitory concentration (MIC) values for 1911, 1521, and 1463 Wisconsin isolates of E. coli, P. mirabilis, and P. aeruginosa, respectively, were determined by broth microdilution testing. In separate data analyses, all MIC data were interpreted using CLSI breakpoints published prior to 2019, then secondarily by using CLSI breakpoints published since 2019 (which reflect lower breakpoints for both levofloxacin and ciprofloxacin resistance). Findings were further stratified by Wisconsin Department of Health Services region.
Results: Up to 3.2% decreased statewide fluoroquinolone susceptibility was observed for E. coli isolates, while 5.1% and 6.3% decreases in levofloxacin susceptibility were noted for P. aeruginosa and P. mirabilis isolates, respectively, when revised breakpoints were applied. E. coli isolates from the Western region and P. mirabilis isolates from the Southeastern region demonstrated significant shifts toward decreased fluoroquinolone susceptibility upon application of revised breakpoints. Northern region P. mirabilis isolates exhibited consistently decreased fluoroquinolone susceptibility.
Conclusions: Fluoroquinolone resistance has been underreported in Wisconsin as a whole, yet geographic variability continues to exist. Targeted annual surveillance is important to identify and monitor resistance trending. Compilations of SWOTARE surveillance data can be utilized to predict the impact of future CLSI interpretive breakpoint revisions in Wisconsin.
Fluoroquinolone agents such as ciprofloxacin and levofloxacin are extensively prescribed for treatment of a variety of infections due to their broad spectrum of activity, favorable pharmacokinetic profiles, relative efficacy, and perceived safety in non-pregnant adult populations.1 In the United States, fluoroquinolones are the third most prescribed class of antimicrobial agents; an estimated average of 115 prescriptions per 1000 patients are written each year.2 An additional audit of prescribing patterns in the context of adult ambulatory care visits3 revealed that nearly 8 million fluoroquinolone prescriptions were written in 2014 for presentations such as sinusitis and uncomplicated cystitis in females that do not require the use of antimicrobial agents. Not only has the overuse of fluoroquinolone agents contributed to adverse events4 and secondary clinical scenarios such as Clostridioides difficile infection,5 but also the fear of antimicrobial resistance promulgation in both inpatient and outpatient settings.
Fluoroquinolone resistance within Gram-negative bacilli has been investigated in Wisconsin through antibiogram compilation6 and isolate surveillance7 approaches. The Surveillance of Wisconsin Organisms for Trends in Antimicrobial Resistance and Epidemiology (SWOTARE) program is a Wisconsin antimicrobial resistance surveillance initiative operated annually in collaboration with nearly two dozen clinical microbiology laboratories. Each laboratory provides isolates of clinically-significant species that are tested by standardized broth microdilution at a central laboratory. Data are analyzed via minimum inhibitory concentration (MIC) frequency distribution and by categorical interpretive criteria updated yearly by Clinical and Laboratory Standards Institute (CLSI). Data have additionally been analyzed on a geographic7-9 and epidemiologic10 basis.
CLSI not infrequently adjusts interpretive breakpoints for selected antimicrobial agent/organism combinations, especially when new pharmacokinetic and pharmacodynamic parameters suggest roles in patient outcomes. In 2019, CLSI published revised ciprofloxacin and levofloxacin broth microdilution breakpoints for Enterobacterales and Pseudomonas aeruginosa11 in which resistance breakpoints were lowered for both organism groupings. To determine impact of these CLSI revisions on Wisconsin fluoroquinolone resistance within Gram-negative bacilli, we applied pre-201912 and revised (current)11 CLSI breakpoints for ciprofloxacin and levofloxacin to 5-year aggregate SWOTARE (2016-2020) collections of Escherichia coli, Proteus mirabilis, and P. aeruginosa clinical isolates. An additional analysis determined geographic regions of Wisconsin that were impacted by these breakpoint revisions to a greater extent.
Materials and Methods
Study Site Recruitment
Five demarcated regions (Figure 1) of the Wisconsin Department of Health Services (DHS) that are typically utilized for communication and data analysis within the agency served as the basis for geographic comparison within this study. Basis for study site recruitment within the SWOTARE initiative has previously been discussed.7-10 In general, SWOTARE attempts to focus recruitment efforts toward non-tertiary care facilities in order to provide a representative profile of Wisconsin antimicrobial resistance patterns. Past efforts have indicated that more than one-half of participating microbiology laboratories are found in municipalities with populations of < 30,000 inhabitants.8 Past limitations to this approach have included certain Wisconsin DHS regions possessing less population density and those possessing fewer hospital microbiology laboratories due to laboratory consolidation.
Study locations that contributed isolates to this aggregate 5-year analysis included microbiology laboratories in Ashland, Marshfield, Spooner, Stevens Point, and Weston (Northern region); Appleton, Fond du Lac, Green Bay, Manitowoc, Neenah, and Sturgeon Bay (Northeastern region); Janesville, Madison, Monroe, Platteville, Prairie du Chien, and Viroqua (Southern region); Fort Atkinson, Milwaukee, West Allis, West Bend (Southeastern region); and, Amery, Cumberland, Eau Claire, Grantsburg, La Crosse, and St. Croix Falls (Western region).
Distribution of five Wisconsin Department of Health Services geographic regions.
Selection of Isolates
On an annual basis, study sites were requested to forward clinically-significant isolates of E. coli, P. mirabilis, and P. aeruginosa on Amies transport swabs containing charcoal (Hardy Diagnostics, Santa Maria, California) to a centralized testing laboratory. To limit potential of bias during the collection process, isolates were collected in consecutive fashion and any duplicate or nonviable isolates were excluded from the study. In addition, study sites were asked to provide limited demographic information related to age, gender, specimen source of isolate, and location of healthcare encounter. Moreover, efforts were made to exclude academic medical centers to avoid biases in antimicrobial resistance. Access to protected health information for the purpose of surveillance was granted by the Marquette University Institutional Review Board. Because of the lack of direct involvement in the collection of specimens and because of the utilization of de-identified isolates from routine clinical care, the SWOTARE program was not considered to be actively engaged in human subjects research by the Marquette University Institutional Review Board.
Test Performance and Data Analysis
Following cultivation of isolates from transport swabs and subculture onto trypticase soy agar with 5% sheep erythrocytes (ThermoFisher Remel, Lenexa, Kansas), broth microdilution antimicrobial susceptibility testing was executed using standards published by CLSI.13 Endpoint levofloxacin and ciprofloxacin MIC values were recorded for all testing performed. CLSI levofloxacin and ciprofloxacin interpretive breakpoints published prior to 201912 were retrospectively applied to the entire MIC dataset for a sub-analysis heretofore referred to as “previous”. In analogous fashion, CLSI fluoroquinolone interpretive breakpoint revisions published in 201911 were retrospectively applied to the same MIC dataset for a “current” interpretation sub-analysis.
Percentage susceptible, intermediate, and resistant values, as well as median MIC (MIC50) and 90th percentile MIC (MIC90) determinations were made on a statewide and geographic basis using both sets of breakpoints. As an additional means of characterizing geographic variation, the statewide mean susceptibility percentage for a given organism/antimicrobial combination established a baseline value. An interval of 5% on either side of that mean represented normal distribution. Region-specific values ≥ 5% less than the state mean indicated areas with increased resistance. Region-specific values ≥ 5% greater than the state mean indicated less resistance potential. These intervals were utilized in previous SWOTARE reports.7-10
Results
Effect of Revised Fluoroquinolone Breakpoints on Wisconsin Statewide Isolates of E. coli, P. mirabilis, and P. aeruginosa
Standardized reference ciprofloxacin and levofloxacin broth microdilution assayed each isolate using a concentration range of 0.25 μg/mL through 32 μg/mL. MIC50 and MIC90 frequency distribution data for 1911 E. coli isolates (Table 1) revealed a broad distribution of MIC values across the testing range, particularly for ciprofloxacin. When compared to pre-2019 practice, small decreases in percentage susceptibility were observed when updated CLSI breakpoints were applied (1.5% for levofloxacin; 3.2% for ciprofloxacin).
Fluoroquinolone MIC50 and MIC90 distribution of Wisconsin surveillance isolates of Escherichia coli, Proteus mirabilis, and Pseudomonas aeruginosa collected from 2016-2020. Categorical interpretive data (S, susceptible; I, intermediate; R, resistant) are based on application of either previous (prior to 2019) or current (established in 2019) Clinical and Laboratory Standards Institute (CLSI) Enterobacterales (formerly Enterobacteriaceae) and Pseudomonas aeruginosa breakpoints.
A similar broad MIC frequency distribution was observed for 1521 isolates of P. mirabilis. Application of revised CLSI breakpoints to this dataset resulted in up to 6.3% decreases in susceptibility (levofloxacin) when compared to previous breakpoints (Table 1).
For P. aeruginosa, MIC50 and MIC90 data for ciprofloxacin (≤ 0.25 μg/mL; 2 μg/mL) and levofloxacin (0.5 μg/mL; 4 μg/mL) demonstrated a narrower MIC frequency distribution than the aforementioned Enterobacterales (Table 1).
Application of revised CLSI breakpoints to the 1463-isolate dataset resulted in 4.5% − 5.1% decreases in fluoroquinolone susceptibility than what were realized with the previous breakpoints.
Geographic Variation of Fluoroquinolone Resistance within Wisconsin E. coli Isolates and Impact of CLSI Breakpoint Revisions
When E. coli isolates were analyzed on a geographic basis using previous CLSI breakpoints, fluoroquinolone susceptibility rates differed by up to 9.4% (levofloxacin; Table 2), with Western region isolates demonstrating greatest susceptibility and Southeastern region isolates demonstrating the lowest susceptibility rate. Similar observations were made when revised CLSI breakpoints were applied to the dataset. However, the maximum susceptibility difference between regions decreased to 6.8% (levofloxacin).
Fluoroquinolone MIC50 and MIC90 distribution of Wisconsin surveillance isolates of Escherichia coli collected from 2016-2020, stratified by Wisconsin Department of Health Services (DHS) region. Categorical interpretive data (S, susceptible; I, intermediate; R, resistant) are based on application of either previous (prior to 2019) or current (established in 2019) Clinical and Laboratory Standards Institute (CLSI) Enterobacterales (formerly Enterobacteriaceae) breakpoints.
Despite the Western region appearing to exhibit the highest fluoroquinolone susceptibility rates for E. coli, CLSI breakpoint revisions appeared to have had the greatest impact in this region of Wisconsin. As an example, ciprofloxacin susceptibility rates in the Western region decreased 4.9% when revised CLSI breakpoints were applied to this dataset. In the context of an MIC90 value of 8 μg/mL (Table 2), these data suggest that Western region isolates generally exhibited a narrower MIC frequency distribution than other regions of Wisconsin, allowing a greater proportion of isolates to shift into an intermediate or resistant interpretive category following the two doubling dilution revision in CLSI breakpoint. Only modest changes in fluoroquinolone susceptibility rates following breakpoint revision were noted in other Wisconsin DHS regions.
Geographic Variation of Fluoroquinolone Resistance within Wisconsin P. mirabilis Isolates and Impact of CLSI Breakpoint Revisions
When the P. mirabilis dataset was analyzed on a geographic basis using previous CLSI breakpoints, fluoroquinolone susceptibility rates differed by rates greater than those exhibited by E. coli. As an example, 91.7% of Southeastern region isolates were susceptible to levofloxacin, while 74.9% of Northern region isolates were susceptible to the agent, a 16.8% difference (Table 3). The analogous disparity for ciprofloxacin was 12.6%. When revised (current) CLSI breakpoints were applied to the P. mirabilis dataset, geographic differences in susceptibility decreased to a maximum of 13.6% for levofloxacin and 11.1% for ciprofloxacin, with the Southern region demonstrating highest fluoroquinolone susceptibility rates.
Fluoroquinolone MIC50 and MIC90 distribution of Wisconsin surveillance isolates of Proteus mirabilis collected from 2016-2020, stratified by Wisconsin Department of Health Services (DHS) region. Categorical interpretive data (S, susceptible; I, intermediate; R, resistant) are based on application of either previous (prior to 2019) or current (established in 2019) Clinical and Laboratory Standards Institute (CLSI) Enterobacterales (formerly Enterobacteriaceae) breakpoints.
On a DHS regional basis, analysis of the P. mirabilis dataset indicated that revised CLSI breakpoints had little effect on organism susceptibility to ciprofloxacin, with changes in percentage susceptibility ranging from 0.7% (Northern region) to 3.8% (Southeastern region). In contrast, regionspecific reductions in levofloxacin susceptibility included 5.6%, 8.1%, and 9.5% values in the Northern, Northeastern, and Southeastern regions, respectively, upon application of revised breakpoints (Table 3). Regardless of breakpoints used, the Northern region exhibited the lowest rates of fluoroquinolone susceptibility within P. mirabilis isolates. The noteworthy change in Southeastern region isolate susceptibility to levofloxacin (also observed in tempered fashion for ciprofloxacin) was likely linked to a narrower MIC frequency distribution (MIC90 2 μg/mL), signifying a significant proportion of previously-susceptible isolates within this region with elevated MIC values within the susceptible range.
Geographic Variation of Fluoroquinolone Resistance within Wisconsin P. aeruginosa Isolates and Impact of CLSI Breakpoint Revisions
When the P. aeruginosa MIC dataset was analyzed on a geographic basis using previous CLSI breakpoints, fluoroquinolone susceptibility rates differed by up to 4.3% (levofloxacin; Table 4). When revised CLSI breakpoints were applied to the dataset, the maximum susceptibility difference increased to 5.8% (levofloxacin). Higher rates of P. aeruginosa susceptibility to fluoroquinolone agents were consistently observed in Southern region isolates.
Fluoroquinolone MIC50 and MIC90 distribution of Wisconsin surveillance isolates of Pseudomonas aeruginosa collected from 2016-2020, stratified by Wisconsin Department of Health Services (DHS) region. Categorical interpretive data (S, susceptible; I, intermediate; R, resistant) are based on application of either previous (prior to 2019) or current (established in 2019) Clinical and Laboratory Standards Institute (CLSI) Pseudomonas aeruginosa breakpoints.
Impact of the CLSI P. aeruginosa levofloxacin breakpoint revision was greatest in the Northeastern (6.1% reduction in susceptibility), Southeastern (6.4%), and Western (5.9%) regions of Wisconsin (Table 4). The Southeastern region also exhibited a 5.9% reduction in susceptibility upon implementation of the ciprofloxacin breakpoint revision. General fluoroquinolone MIC frequency distributions within Wisconsin P. aeruginosa isolates differed less by geographic region when compared to E. coli and P. mirabilis isolates.
Geographic Variation of Fluoroquinolone Resistance in Wisconsin Relative to State Mean
Finally, fluoroquinolone susceptibility values within each DHS region were compared to the Wisconsin mean for each agent relative to previous and current CLSI breakpoints. Ciprofloxacin data are illustrated in Figure 2 as a class example. While geographic variation was evident for all organism/antimicrobial combinations (Tables 2-4), such variation was normalized when data were compared to the state mean for each combination. One major exception was exemplified by decreased fluoroquinolone susceptibility in Northern region P. mirabilis isolates (Figure 2B), a paradigm that was unchanged following CLSI breakpoint revision (Figure 2E).
Geographic variation with respect to Escherichia coli (A, D), Proteus mirabilis (B, E), Pseudomonas aeruginosa (C, F) susceptibility to ciprofloxacin, relative to statewide mean, Wisconsin 2016-2020. Panels A-C reflect analysis of datasets with previous (prior to 2019) CLSI ciprofloxacin breakpoints; panels D-F reflect analysis of datasets with current (established in 2019) CLSI ciprofloxacin breakpoints. Regions colored orange represent percentage susceptible rates ± 5% of the Wisconsin mean for ciprofloxacin. Regions colored red represent percentage susceptible rates ≥ 5% less than the state mean for ciprofloxacin. Regions colored green represent percentage susceptible rates ≥ 5% greater than the state rate for ciprofloxacin..
Additional normalization occurred when current CLSI breakpoints were applied to the E. coli dataset, particularly in the Western region (Figure 2D). Previous ciprofloxacin profiling of the Western region E. coli dataset had indicated increased susceptibility (Figure 2A), again indicating a region in which fluoroquinolone resistance had been underreported due to suboptimal breakpoints. In similar fashion, characterization of the P. mirabilis dataset from the Southeastern region using the previous CLSI ciprofloxacin breakpoint (Figure 2B) indicated a susceptibility rate >5% higher than the state mean. Upon CLSI breakpoint revision, susceptibility values mirrored the state mean, again indicating previous underreporting of ciprofloxacin resistance in Southeastern Wisconsin. Analysis of levofloxacin data revealed the same illustrations depicted in Figure 2.
Discussion
CLSI publications serve as the reference for antimicrobial susceptibility testing efforts within most United States clinical microbiology laboratories. These guidelines and standards are revised as needed to attempt to better meet the needs of clinical partners. In particular, Humphries et al14 commented that interpretive breakpoint modifications may be prompted by factors including (but not limited to) discovery of novel resistance mechanisms, new antimicrobial formulations, dosing regimens in widespread clinical practice differing substantially from regimens that were used to establish previous breakpoints, differences between CLSI breakpoints and those from other regulatory agencies, specific public health needs not being addressed, and refinements in scientific experimentation used to determine pharmacokinetics and pharmacodynamics of an antimicrobial agent. Important CLSI revisions within the past 10 years have included establishment of a susceptible-dose dependent interpretive category for the Enterobacteriacae/cefepime15 and Staphylococcus spp/ceftaroline11 combinations, as well as the creation of uncomplicated cystitis breakpoints for the Enterobacteriaceae/cefazolin16 combination.
Impetus for the fluoroquinolone breakpoint revisions focused upon in our report centered around multi-disciplinary CLSI investigations17 which determined that area under the curve (AUC):MIC ratios for fluoroquinolone agents that corresponded to previously-published CLSI breakpoints failed to correlate with in vivo AUC:MIC ratio targets derived from clinical therapeutic studies of bacterial pneumonia.18,19 As a result, for both fluoroquinolone agents, P. aeruginosa-specific breakpoints were reduced by one doubling dilution for susceptible, intermediate, and resistant interpretive criteria. Similarly, a two doubling-dilution reduction in breakpoint values was established for both agents within Enterobacterales.
When fluoroquinolone susceptibility data were analyzed on a statewide basis and by individual DHS region, decreases in levofloxacin and ciprofloxacin susceptibility rates were noted in each region for each organism following application of revised CLSI breakpoints. These data suggest in vitro fluoroquinolone resistance was generally underreported in Wisconsin for several years prior to the institution of revised CLSI breakpoints. In addition, organism-specific geographic variability relative to fluoroquinolone susceptibility does exist within Wisconsin. With respect to P. mirabilis in particular, these variances showed evidence of shifting as a result of CLSI breakpoint revision. Factors contributing to general geographic variation within Wisconsin antimicrobial resistance patterns, including local provider prescription practices as well as potential veterinary and agricultural influences,20,21 warrant additional study.
Taken together, these data demonstrate the importance not only of knowledge of local antimicrobial susceptibility patterns but also routine surveillance of antimicrobial resistance profiles at the local and regional level, with dissemination of such findings. Moreover, through collection of raw MIC data, the SWOTARE program can facilitate statewide and geographic-specific predictive exercises relative to the impact of future CLSI interpretive breakpoint revisions on antimicrobial resistance profiles in Wisconsin.
From both a clinical patient care perspective and antimicrobial stewardship perspective, changes in susceptibility may affect clinicians’ choices of empiric antimicrobial agents (eg, kidney infections in the community caused by E. coli or hospital-associated infections caused by P. aeruginosa). While the finding of reduced susceptibility of E. coli, P. mirabilis, and P. aeruginosa to fluoroquinolone agents is disturbing in terms of antimicrobial resistance trending, the magnitude of these changes at this time is not likely to affect empiric decision making. More importantly, in the past few years, fluoroquinolone agents have been discouraged for clinical use as first-line agents for uncomplicated urinary tract infections and bacterial sinusitis.22 However, continued statewide and regional surveillance of the magnitude of resistance trends will remain important for future treatment considerations.
Acknowledgments
The research received support from the Wisconsin Department of Health Services, Division of Public Health (ELC Project K2: HAI Coordinated Prevention and Stewardship).
The authors thank Zorangel Amezquita-Torres, Lauren Crudo, Maegan Guevarra, Morgan Hays, Erin Hueppchen, Manjeet Khubbar, Madeline Leafblad, Jennifer Lentz, Rebecca Martin, Morena Pass, Alyssa Reynoso, Rebecca Schulte, Laura Sienkiewicz, Yazmine Thomas, and Heather Zeman for expert technical assistance.
The authors further recognize the efforts of clinical microbiologists across Wisconsin for sustained contributions to the SWOTARE program, including:
Kathy Lang (Ashland)
Thomas R. Fritsche, MD, PhD, Brooke Olson (Marshfield)
Ashley Gargulak, Mattie Pitts (Spooner)
Becky Brooks (Stevens Point)
Joshua Kropp, Jennifer Meyer (Weston)
Benjamin Kaetterhenry (Appleton)
Ellen Wirtz (Fond du Lac)
Sherry Barta, Kellie Diedrick, Tyler Radke, Andrea Roder (Green Bay)
Debbie Maedke, Lynn Prellwitz (Manitowoc)
Heidi Graves, Karen Siebers (Neenah)
Cara Tolliver (Sturgeon Bay)
Tracy Felland (Janesville)
Erin Bowles, Raymond P. Podzorski, PhD (Madison)
Sonja Alt, Nyssa Sheridan, Madeline Zuber (Monroe)
Debra Kieler (Platteville)
Betsy Hudson, Brian Simmons (Prairie du Chien)
Jorn Bansberg, Linda Morrison (Viroqua)
Frances Spray-Larson, PhD (Fort Atkinson)
Kayla Bonert, David Klebenow, Timothy Kramme (Milwaukee)
Eric T. Beck, PhD (West Allis)
Timothy Block (West Bend)
Lori Reed (Amery)
Bryna Melichar (Cumberland)
Janelle Stearns, Tyler Tschanz (Eau Claire)
Robin Larson (Grantsburg)
Sarah Stoner (La Crosse)
Ashley Hoveland, Mary A. Smith (St. Croix Falls)
Footnotes
Financial Disclosure: Dr. Munson received financial support from the Wisconsin Department of Health Services, Division of Public Health (ELC Project K2: HAI Coordinated Prevention and Stewardship).
- Received September 6, 2021.
- Accepted December 24, 2021.
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