ViResiST was a project that contributed to understanding the relationship between antimicrobial use and resistance. It confirmed this relationship using new methodology with routine laboratory and pharmacy data from multiple hospitals. ViResiST collected longitudinal electronic data from several European hospitals, validating models showing the relationship in these settings. The project established an accepted methodology for examining this issue but did not fully transition from research to guiding prescriptions in real-time to prevent resistance increases.

1. ViResiST:
its contribution to our knowledge
of the relationship between
antimicrobial use and resistance
Dominique L. Monnet

2. About antibiotics...
• ”As soon as we use it, we loose it”
• ”The more we use it, the more we
loose it”

3. The Antimicrobial Resistance Spiral
ANTIMICROBIAL RESISTANCE New antimicrobials
(promotion)
1 - Concern
4 - Cross-transmission 2 - Broad-spectrum
3 - Selection empiric therapy
Antimicrobial resistance Dose
Duration

4. Genetic Diversity and Adaptation
2010
approx. 15,000 generations humans
Tautavel (France), approx. 1010 generations of 109 E. coli
approx. 450,000 years ago
Adapted from: Geberding JL, CDC/NCID/HIP, 1999.
Picture from: URL: http://www.culture.fr/culture/arcnat/tautavel/en/homme-fr.htm

5. Illustration: Prittie EJ. Philadeplphia, PA: JC Winston, 1930.

10. The Antimicrobial Resistance Spiral
ANTIMICROBIAL RESISTANCE
1 - Concern
New antimicrobials
(promotion) ?
4 - Cross-transmission 2 - Broad-spectrum
3 - Selection empiric therapy
Antimicrobial resistance Dose
Duration

11. Study designs for
the relationship between
antimicrobial use and resistance

12. Pharyngeal Carriage of Macrolide-Resistant Streptococci
Following Exposure to Azithromycin and Clarithromycin
Source: Malhotra-Kumar S, et al. Lancet 2007;369:482-490.

13. Cumulative Hazard Estimates for
Emergence of Fluoroquinolone Resistance
Following Fluoroquinolone Exposure
0.20
Probability of resistance
0.15
Fluoroquinone exposed
0.10
0.05
No fluoroquinolone
0.00
0 20 40 60 80
Days
Source: Harbarth S, et al. Clin Infect Dis 2001;33:1462-1468.

14. Fluoroquinolone Use and Ciprofloxacin-Resistant
P. aeruginosa, SCOPE-MMIT Hospitals, 1999-2000
50
y = 0.0832x + 18.461
Pseudomonas aeruginosa
R2 = 0.29
% Ciprofloxacin-Resistant
40 p = 0.01
30
(%)
20
10
0
0 50 100 150 200 250
Total Fluoroquinolone Use
(Daily Doses per 1,000 patient-days)
Source: Polk RE, et al. 41st ICAAC, Chicago (IL), 2001, late-breaker abstr. UL-1.

15. Retrospective Information to Guide
Empiric Prescription of Antimicrobials
Source: Snyder JW, Beam L. University of Louisville Hospital, Louisville (Kentucky), 1994.

16. Before ViResiST…
Bzzzz...

17. 5-Month Moving Average Percent Imipenem-
Resistant/Intermediate P. aeruginosa and Hospital
Imipenem Use, Hospital Vega Baja, Spain, 1991-2002
Average delay = 1 month
1 DDD/1,000 pat-days  +0.40 %R
% Imipenem-resistant/intermediate
25 30
(DDD/1,000 patient-days)
Hospital imipenem use
Pseudomonas aeruginosa
25
20
20
15
15
10
10
5
5
0 0
91
92
93
94
95
96
97
98
1
2
3
4
5
6
7
8
l-9
l-9
l-9
l-9
l-9
l-9
l-9
l-9
n-
n-
n-
n-
n-
n-
n-
n-
Ju
Ju
Ju
Ju
Ju
Ju
Ju
Ju
Ja
Ja
Ja
Ja
Ja
Ja
Ja
Ja
Updated from: López-Lozano JM, et al. Int J Antimicrob Agents 2000;14:21-30. ViResiST

18. Applications of ViResiST
in other hospitals

19. %Carbapenem-Resistant Pseudomonas aeruginosa
and Carbapenem Use in 4 Hospitals, 1996-2003
Univ. Hospital, Ulm (D) Univ. Hospital, Utah (USA)
Lepper et al. AAC 2002;46:2920-5. Samore MH, et al. Unpublished data.
40 2
(DDD/100 pt-days)
Carbapenem-resistant
Carbapenem use
P.aeruginosa(%)
30 1.5
Average Average
20 1
delay delay
= 10 0.5
=
0-1 month 0 0 0-1 month
96
97
98
99
00
01
n-
n-
n-
n-
n-
n-
Ja
Ja
Ja
Ja
Ja
Ja
Univ. Hospital, Antwerp (B) Centre Hosp. Mulhouse (F)
Goossens H, et al. Unpublished data. Aujoulat O, Delarbre JM. ViResiST.
40 5 40 0.5
(DDD/100 pt-days)
(DDD/100 pt-days)
Carbapenem-resistant
Carbapenem use
Carbapenem use
Imipenem-resistant
Average
P.aeruginosa(%)
P.aeruginosa (%)
4 0.4
30 30
Average
3 0.3 delay
20
delay 20
2 0.2 =
10 = 10
1 0.1 n.a.
0 0 0-2 months 0 0
7
8
9
0
1
2
99
00
01
02
03
04
-9
-9
-9
-0
-0
-0
n-
n-
n-
n-
n-
n-
n
n
n
n
n
n
Ja
Ja
Ja
Ja
Ja
Ja
Ja
Ja
Ja
Ja
Ja
Ja

20. %MRSA and Monthly Use of Macrolides,
Third-Generation Cephalosporins and Fluoroquinolones,
Aberdeen Royal Infirmary, 01/1996-12/2001
Explaining variable Lag (months) Estimated
for monthly %MRSA coefficient
%M RSA 1 0.420
Macrolide use 1,2,3 0.165
Third-generation
4,5,6,7 0.290
cephalosporin use
Fluoroquinolone use 4,5 0.255
Constant - - 36.7
R2=0.902
Source: Monnet DL, et al. Emerg Infect Dis 2004;10:1432-1441.

21. Multivariate time series models to explain hospital MRSA
University of Geneva Hospitals, 2000-2006
Antrim Area Hospital, Northern Ireland, 2000-2004
Source: Vernaz N, et al. JAC 2008;62:601-607; Aldeyab MA, et al. JAC 2008;62:593-600.

22. What did ViResiST achieve?
Confirmation of the relationship between antimicrobial use
 and resistance with new methodology using routine
laboratory and pharmacy data
Collection of longitudinal, electronic data from several
 hospitals in Europe
Confirm the models with data from these European
 hospitals (generalisation)
 Acceptance of the methodology
 Transition from research to routine practice
Use models in real time to guide prescriptions in order to
 beat resistance before it increases

23. With ViResiST!
Beat the Bug Before it Bites
B... B... B... B...

24. 10
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25. http://antibiotic.ecdc.europa.eu