Systematic Review of Antimicrobial Combination Options for Pandrug-Resistant Acinetobacter baumannii
Abstract
:1. Introduction
2. Methods
2.1. Search Strategy
2.2. Eligibility Criteria
2.3. Data Extraction
2.4. Definition of Eligible Strains
2.5. Evaluation of In Vivo Feasibility of the Identified Combinations
2.6. Data Synthesis and Analysis
3. Results
3.1. Summary and Characteristics of Reviewed Studies
3.2. Overview of Methods for Assessment of Antimicrobial Combinations
3.3. Overview of Antimicrobial Combinations That have been Evaluated
3.4. Overview of Polymyxin-Based Combinations
3.5. Overview of Non-Polymyxin Based Combinations
3.6. Evaluation of Clinical Relevance of Reported Synergy
3.7. Clinical Studies
4. Discussion
4.1. Summary of Main Findings
4.2. Polymyxin-Based Combinations
4.3. Non-Polymyxin Combinations
4.4. Limitations of the Review and of the Available Evidence
4.5. Strengths of the Review
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
Year of Publication | Number of Studies (%) |
---|---|
2017–2021 | 29 (35%) |
2021 | 5 (6%) |
2020 | 6 (7%) |
2019 | 10 (12%) |
2018 | 3 (4%) |
2017 | 5 (6%) |
2012–2016 | 32 (38%) |
2016 | 10 (12%) |
2015 | 6 (7%) |
2014 | 7 (8%) |
2013 | 6 (7%) |
2012 | 3 (4%) |
2007–2011 | 15 (18%) |
2011 | 3 (4%) |
2010 | 6 (7%) |
2009 | 3 (4%) |
2008 | 2 (2%) |
2007 | 1 (1%) |
2002–2006 | 7 (8%) |
2005 | 2 (2%) |
2004 | 4 (5%) |
2003 | 1 (1%) |
1995–2001 | 1 (1%) |
1996 | 1 (1%) |
WHO Regions | Number of Studies Per Region (%) |
---|---|
Americas | 24 (29%) |
Brazil | 6 (7%) |
USA | 12 (14%) |
Argentina | 3 (4%) |
Colombia | 1 (1%) |
Southeast Asia Region | 7 (8%) |
India | 1 (1%) |
Thailand | 6 (7%) |
European Region | 28 (33%) |
France | 3 (4%) |
Germany | 1 (1%) |
Greece | 3 (4%) |
Italy | 3 (4%) |
Spain | 7 (8%) |
Turkey | 7 (8%) |
Switzerland | 1 (1%) |
United Kingdom | 1 (1%) |
Eastern Mediterranean Region | 5 (6%) |
Iran | 1 (1%) |
Saudi Arabia | 4 (5%) |
United Arab Emirates | 2 (2%) |
Oman | 2 (2%) |
Kuwait | 2 (2%) |
Qatar | 2 (2%) |
Bahrain | 3 (4%) |
Western Pacific Region | 20 (24%) |
China | 9 (11%) |
South Korea | 6 (7%) |
Taiwan | 3 (3%) |
Antimicrobial Combinations | CHBD | CHBD: Concentration at which Synergy Was Present | TKA | TKA: Concentration at which Synergy Was Present | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Studies n | Isolates n | Synergy n (% *) | ≤Breakpoints n (% *) | >Breakpoints n (% *) | Unclear n (% *) | Studies n | Isolates n | Synergy n (% *) | ≤Breakpoints n (% *) | >Breakpoints n (% *) | Unclear n (% *) | |
SUL-based | ||||||||||||
SUL/CAZ | 1 | 10 | 7 (70%) | 1 (10%) | 6 (60%) | 0 (0%) | ||||||
SUL/CIP | 1 | 10 | 8 (80%) | 2 (20%) | 6 (60%) | 0 (0%) | ||||||
SUL/MEM | 6 | 173 | 72 (42%) | 2 (1%) | 2 (1%) | 68 (39%) | 3 | 54 | 32 (59%) | 0 (0%) | 7 (22%) | 25 (78%) |
SUL/DOR | 1 | 17 | 4 (24%) | 4 (100%) | 0 (0%) | 0 (0%) | ||||||
SUL/AVI | 1 | 1 | 1 (100%) | 1 (100%) | 0 (0%) | 0 (0%) | ||||||
SUL/GEN | 1 | 10 | 8 (80%) | 2 (25%) | 6 (75%) | 0 (0%) | ||||||
SUL/CST | 1 | 6 | 2 (33%) | 2 (100%) | 0 (0%) | 0 (0%) | ||||||
SUL/PMB | 1 | 3 | 2 (67%) | 2 (100%) | 0 (0%) | 0 (0%) | ||||||
SUL/FOF | 2 | 56 | 41 (73%) | 3 (7%) | 37 (90%) | 1 (2%) | 2 | 10 | 7 (70%) | 0 (0%) | 7 (100%) | 0 (0%) |
SAM-based | ||||||||||||
SAM/FEP | 1 | 2 | 2 (100%) | 1 (50%) | 1 (50%) | 0 (0%) | ||||||
SAM/LVX | 1 | 7 | 7 (100%) | 5 (71%) | 2 (29%) | 0 (0%) | ||||||
SAM/MEM | 2 | 10 | 2 (20%) | 2 (100%) | 0 (0%) | 0 (0%) | 1 | 2 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) |
SAM/RIF | 1 | 7 | 7 (100%) | 4 (57%) | 1 (14%) | 2 (29%) | ||||||
IMP-based | ||||||||||||
IMP/CFS | 1 | 16 | 11 (69%) | 9 (82%) | 2 (18%) | 0 (0%) | ||||||
IMP/CST | 2 | 10 | 9 (90%) | 2 (20%) | 7 (70%) | 0 (0%) | 1 | 2 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) |
IMP/RIF | 2 | 28 | 16 (57%) | 11 (39%) | 3 (11%) | 2 (7%) | 5 | 13 | 6 (46%) | 0 (0%) | 6 (46%) | 0 (0%) |
IMP/FOF | 3 | 45 | 26 (58%) | 9 (20%) | 10 (22%) | 7 (16%) | 1 | 9 | 8 (89%) | 0 (0%) | 8 (89%) | 0 (0%) |
MEM-based | ||||||||||||
MEM/SUL | 6 | 173 | 72 (42%) | 2 (1%) | 2 (1%) | 68 (39%) | 3 | 54 | 32 (59%) | 0 (0%) | 7 (13%) | 25 (46%) |
MEM/SAM | 2 | 10 | 2 (20%) | 2 (20%) | 0 (0%) | 0 (0%) | 1 | 2 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) |
MEM/AMK | 4 | 47 | 16 34%) | 1 (2%) | 2 (4%) | 13 (28%) | ||||||
MEM/CST | 6 | 29 | 21 (72%) | 5 (17%) | 11 (3%) | 5 (17%) | 3 | 4 | 4 (100%) | 0 (0%) | 4 (100%) | 0 (0%) |
MEM/PMB | 1 | 3 | 3 (100%) | 3 (100%) | 0 (0%) | 0 (0%) | 1 | 2 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) |
MEM/FOF | 4 | 79 | 15 (19%) | 1 (1%) | 14 (18%) | 0 (0%) | ||||||
MEM/VAN | 1 | 5 | 3 (60%) | 1 (20%) | 0 (0%) | 2 (40%) | ||||||
DOR-based | ||||||||||||
DOR/SUL | 1 | 17 | 4 (24%) | 4 (24%) | 0 (0%) | 0 (0%) | ||||||
DOR/CST | 3 | 6 | 2 (33%) | 1 (17%) | 1 (17%) | 0 (0%) | 5 | 33 | 23 (70%) | 19 (58%) | 4 (12%) | 0 (0%) |
DOR/TGC | 1 | 3 | 3 (100%) | 1 (33%) | 0 (0%) | 2 (67%) | 1 | 45 | 5 (11%) | 5 (11%) | 0 (0%) | 0 (0%) |
DOR/RIF | 1 | 1 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 | 5 | 2 (40%) | 1 (20%) | 1 (20%) | 0 (0%) |
CZA- or AVI-based | ||||||||||||
AVI/SUL | 1 | 1 | 1 (100%) | 1 (100%) | 0 (0%) | 0 (0%) | ||||||
CST-based | ||||||||||||
CST/SUL | 1 | 6 | 2 (33%) | 2 (33%) | 0 (0%) | 0 (0%) | ||||||
CST/LVX | 2 | 2 | 1 (50%) | 1 (50%) | 0 (0%) | 0 (0%) | 2 | 2 | 1 (50%) | 0 (0%) | 1 (50%) | 0 (0%) |
CST/IMP | 2 | 10 | 9 (90%) | 2 (20%) | 7 (70%) | 0 (0%) | 1 | 2 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) |
CST/MEM | 6 | 29 | 21 (72%) | 5 (17%) | 11 (38%) | 5 (17%) | 3 | 4 | 4 (100%) | 0 (0%) | 4 (100%) | 0 (0%) |
CST/DOR | 3 | 6 | 2 (33%) | 1 (17%) | 1 (17%) | 0 (0%) | 5 | 33 | 23 (70%) | 19 (58%) | 4 (12%) | 0 (0%) |
CST/TGC | 2 | 10 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 | 12 | 7 (100%) | 7 (100%) | 0 (0%) | 0 (0%) |
CST/RIF | 5 | 40 | 31 (78%) | 10 (25%) | 10 (25%) | 11 (28%) | 3 | 7 | 7 (100%) | 0 (0%) | 6 (86%) | 1 (14%) |
CST/SXT | 2 | 8 | 2 (25%) | 1 (13%) | 0 (0%) | 1 (13%) | 1 | 1 | 1 (100%) | 0 (0%) | 1 (100%) | 0 (0%) |
CST/CHL | 1 | 2 | 2 (100%) | 1 (50%) | 1 (50%) | 0 (0%) | 1 | 2 | 2 (100%) | 0 (0%) | 2 (100%) | 0 (0%) |
CST/FA | 2 | 6 | 6 (100%) | 1 (17%) | 2 (33%) | 3 (50%) | 2 | 4 | 3 (75%) | 0 (0%) | 3 (75%) | 0 (0%) |
CST/VAN | 7 | 33 | 29 (88%) | 2 (6%) | 2 (6%) | 25 (67%) | 6 | 20 | 16 (80%) | 13 (65%) | 3 (15%) | 0 (0%) |
PMB-based | ||||||||||||
PMB/SUL | 1 | 3 | 2 (67%) | 2 (67%) | 0 (0%) | 0 (0%) | ||||||
PMB/MEM | 1 | 3 | 3 (100%) | 3 (100%) | 0 (0%) | 0 (0%) | 1 | 2 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) |
PMB/RIF | 1 | 3 | 3 (100%) | 1 (33%) | 1 (33%) | 1 (33%) | 1 | 3 | 1 (33%) | 1 (33%) | 0 (0%) | 0 (0%) |
PMB/VAN | 1 | 3 | 3 (100%) | 3 (100%) | 0 (0%) | 0 (0%) | 1 | 3 | 2 (67%) | 0 (0%) | 2 (67%) | 0 (0%) |
TGC-based | ||||||||||||
TGC/DOR | 1 | 3 | 3 (100%) | 1 (33%) | 0 (0%) | 2 (67%) | 1 | 45 | 5 (11%) | 5 (11%) | 0 (0%) | 0 (0%) |
TGC/AMK | 1 | 14 | 2 (14%) | 1 (7%) | 1 (7%) | 0 (0%) | 1 | 1 | 1 (100%) | 1 (100%) | 0 (0%) | 0 (0%) |
TGC/CST | 2 | 10 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 | 12 | 7 (58%) | 7 (58%) | 0 (0%) | 0 (0%) |
TGC/RIF | 2 | 16 | 1 (6%) | 0 (0%) | 1 (6%) | 0 (0%) | 2 | 4 | 1 (25%) | 1 (25%) | 0 (0%) | 0 (0%) |
TGC/FOF | 1 | 4 | 3 (75%) | 1 (25%) | 2 (50%) | 0 (0%) | 1 | 1 | 1 (100%) | 0 (0%) | 1 (100%) | 0 (0%) |
RIF-based | ||||||||||||
RIF/SAM | 1 | 7 | 7 (100%) | 4 (57%) | 1 (14%) | 2 (29%) | ||||||
RIF/CFS | 1 | 7 | 2 (29%) | 1 (14% | 0 (0%) | 1 (14%) | ||||||
RIF/IMP | 2 | 28 | 16 (57%) | 11 (39%) | 3 (11%) | 2 (7%) | 5 | 13 | 6 (46%) | 0 (0%) | 6 (46%) | 0 (0%) |
RIF/DOR | 1 | 1 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 | 5 | 2 (40%) | 1 (20%) | 1 (20%) | 0 (0%) |
RIF/CST | 5 | 40 | 31 (78%) | 10 (25%) | 10 (25%) | 11 (28%) | 3 | 7 | 7 (100%) | 0 (0%) | 6 (85%) | 1 (14%) |
RIF/PMB | 1 | 3 | 3 (100%) | 1 (33%) | 1 (33%) | 1 (33%) | 1 | 3 | 1 (33%) | 1 (33%) | 0 (0%) | 0 (0%) |
RIF/TGC | 2 | 16 | 1 (100%) | 0 (0%) | 1 (100%) | 0 (0%) | 2 | 4 | 1 (25%) | 1 (25%) | 0 (0%) | 0 (0%) |
FOF-based | ||||||||||||
FOF/SUL | 2 | 56 | 41 (73%) | 3 (5%) | 37 (66%) | 1 (2%) | 2 | 10 | 7 (70%) | 0 (0%) | 7 (70%) | 0 (0%) |
FOF/IMP | 3 | 45 | 26 (58%) | 9 (20%) | 10 (22%) | 7 (16%0 | 1 | 9 | 8 (89%) | 0 (0%) | 8 (89%) | 0 (0%) |
FOF/MEM | 4 | 79 | 15 (19%) | 1 (1%) | 14 (18%) | 0 (0%) | ||||||
FOF/AMK | 2 | 29 | 26 (90%) | 11 (38%) | 15 (52%) | 0 (0%) | ||||||
FOF/GEN | 2 | 13 | 12 (92%) | 3 (32%) | 9 (69%) | 0 (0%) | ||||||
FOF/TGC | 1 | 4 | 3 (75%) | 1 (25%) | 2 (50%) | 0 (0%) | 1 | 1 | 1 (100%) | 0 (0%) | 1 (100%) | 0 (0%) |
Triple combinations | ||||||||||||
PMB/FOF/MEM | 1 | 3 | 3 (100%) | 3 (100%) | 0 (0%) | 0 (0%) | ||||||
PMB/SUL/MEM | 1 | 3 | 3 (100%) | 3 (100%) | 0 (0%) | 0 (0%) | ||||||
CST/DOR/SUL | 1 | 6 | 6 (100%) | 6 (100%) | 0 (0%) | 0 (0%) | ||||||
CST/VAN/DOR | 1 | 3 | 3 (100%) | 3 (100%) | 0 (0%) | 0 (0%) |
Study-Combinations | Method | Synergy % (n/N) | Comments |
---|---|---|---|
Lenhard, J.R., 2017 [61,62] | |||
PMB/MEM | HFIM | 0 (0/1) | Doses simulating human regimens were used (PMB 3.33 mg/kg then 1.43 mg/kg every 12 h, MEM 2 gr every 8 h as 3 h infusions, SAM 8/4 g every 8 h as 3 h infusions). |
PMB/SAM | 0 (0/1) | ||
MEM/SAM | 0 (0/1) | ||
PMB/MEM/SAM | 100 (1/1) | ||
Yuan, Z., 2010 [102] and Lim, T.P., 2008 [107] | |||
AMK/LVX | HFIM | 0 (0/1) | Regrowth despite initial killing at 4 h. |
AMK/FEP | 0 (0/1) | Regrowth despite initial killing at 4 h. | |
Córdoba, J., 2015 [73] | |||
CST/IMP | Other dynamic in vitro PK/PD model | 0 (0/1) | Simulation of human treatment regimens |
CST/DAP | 100 (1/1) | ||
IMP/ETP | 0 (0/3) | ||
RIF/CFS | 0 (0/7) | ||
Housman, S.T., 2013 [87] | Simulated regimens: SAM 9 g q8 h (3 h inf), DOR 2 gr q8 h (4 h inf), TGC 200 mg q12 h (0.5 h inf). | ||
TGC/DOR | Other dynamic in vitro PK/PD model | 0 (0/2) | |
SAM/DOR | 0 (0/3) | Increased killing with SAM/DOR vs. monotherapies against all 3 strains but with regrowth by 24 h. | |
SAM/TGC | 0 (0/1) | ||
Lee, H.J., 2013 [88] | |||
CST/RIF | Other dynamic in vitro PK/PD model | 100 (1/1) | Regimens mimicking human serum concentration after usual doses in critically-ill patients. |
Study-Combinations | Method | Synergy % (n/N) | Comments |
---|---|---|---|
Cebrero-Cangueiro, T., 2021 [38] | |||
MEM/IMP | Intraperitoneal infection mouse model | 0 (0/2) | Decreased bacterial loads with combination vs. monotherapy, but similar mortality and bacterial clearance comparing meropenem monotherapy to combination therapy. |
Poulakou, G., 2019 [55] | |||
CST/DAP | Intraperitoneal infection mouse model | 100 (1/1) | The combination significantly improved survival and reduced bacterial loads in tissues compared to monotherapies. |
Wei, W., 2017 [64] | |||
CST/LVX | G. mellonella model | 0 (0/1) | Same survival comparing combination therapy to monotherapy |
Yang, H., 2016 [70] | |||
CST/VAN | G. mellonella model | 100 (1/1) | Survival rate in G. mellonella model higher with combination, but high survival even with monotherapies. |
O’Hara, J.A., 2013 [35] | |||
CST/DOR | G. mellonella model | 0 (0/3) | No synergy |
CST/VAN | 0 (0/3) | ||
DOR/VAN | 100 (3/3) | The clinical relevance of the G. mellonella model is unclear because of mechanisms of action likely not relevant to humans; high survival even with DOR and VAN monotherapies, and high survival with DOR/VAN despite lack of in vitro synergy | |
CST/VAN/DOR | 100 (3/3) | ||
Queenan, A.M., 2013 [90] | |||
DOR/CIP | intraperitoneal infection mouse model | 0 (0/1) | No synergy |
DOR/LVX | 100 (1/1) | Improved survival in the mouse model (the isolate had relatively low MICs: DOR 16 mg/L and LVX 8 mg/L). | |
Pachón-Ibáñez, M.E., 2011 [94] | |||
RIF/IMP | Pneumonia mouse model | 0 (0/2) | In the animal model survival with RIF/IMP (80 and 33%) and RIF/SUL (60 and 53%) did not differ significantly compared to RIF monotherapy (73 and 40%). Lung clearance and blood culture sterilization was higher against one of the two strains with RIF/SUL. |
RIF/SUL | 50 (1/2) | ||
Pachón-Ibáñez, M.E., 2010 [98] | |||
SUL/IMP | Pneumonia (mouse) and meningitis (rabbit) models | 100 (1/1) | Higher survival and bacterial clearance in animal model compared to monotherapies. |
RIF/IMP | 0 (0/1) | Survival not improved comparing RIF monotherapy (71%) to combination therapy (60%), despite improved bacterial clearance. | |
RIF/SUL | 0 (0/1) | Survival not improved comparing RIF monotherapy (71%) to combination therapy (47%), despite improved bacterial clearance. | |
Yuan, Z., 2010 [102] | |||
AMK/LVX | Pneumonia mouse model | 0 (0/1) | Similar survival with AMK monotherapy. |
AMK/FEP | 1 (1/1) | Improved survival and reduction of tissue bacterial burden in the mouse model. | |
FEP/LVX | 0 (0/1) | Similar survival with FEP monotherapy. | |
Song, Y.C., 2009 [105] | |||
IMP/RIF | Pneumonia mouse model | 100 (3/3) | Synergistic (≥2Δlog reduction in lung baterial loads compared to RIF monotherapy) against all 3 strains, but 100% survival with both monotherapy and combination. |
RIF/AMK | 0 (0/1) | Not better than monotherapy | |
IMP/AMK | 0 (0/1) | Not better than monotherapy | |
Montero, A., 2004 [113] | |||
IMP/RIF | Pneumonia mouse model | 50 (1/2) | Strain D: no differences compared to monotherapy in the mouse model. Strain E: significantly reduced lung bacterial counts, no significant reduction of bacteremia, similar survival (100% with the combination, 100% with RIF monotherapy). |
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Karakonstantis, S.; Ioannou, P.; Samonis, G.; Kofteridis, D.P. Systematic Review of Antimicrobial Combination Options for Pandrug-Resistant Acinetobacter baumannii. Antibiotics 2021, 10, 1344. https://doi.org/10.3390/antibiotics10111344
Karakonstantis S, Ioannou P, Samonis G, Kofteridis DP. Systematic Review of Antimicrobial Combination Options for Pandrug-Resistant Acinetobacter baumannii. Antibiotics. 2021; 10(11):1344. https://doi.org/10.3390/antibiotics10111344
Chicago/Turabian StyleKarakonstantis, Stamatis, Petros Ioannou, George Samonis, and Diamantis P. Kofteridis. 2021. "Systematic Review of Antimicrobial Combination Options for Pandrug-Resistant Acinetobacter baumannii" Antibiotics 10, no. 11: 1344. https://doi.org/10.3390/antibiotics10111344
APA StyleKarakonstantis, S., Ioannou, P., Samonis, G., & Kofteridis, D. P. (2021). Systematic Review of Antimicrobial Combination Options for Pandrug-Resistant Acinetobacter baumannii. Antibiotics, 10(11), 1344. https://doi.org/10.3390/antibiotics10111344