Top Five Papers in Infectious

Disease Pharmacotherapy

Elizabeth Neuner, PharmD, BCPS (AQ-ID)

OSHP Spring Meeting

April 24th 2015

Learning Objectives

1. Review data from recent studies

assessing antimicrobial dosing strategies

and impact on clinical outcomes.

2. Discuss the impact of recent literature on

the selection of antimicrobials for various

health-care associated infections.

Methods

PubMed Search: Jan-Dec 2014

“Infectious Diseases”

N = 20,126

Houston ID Network: ID Pharmacotherapy

SIDP Survey

N = 27

Health-System

Pharmacists

SIDP = Society of Infectious Diseases Pharmacists

Other Excellent Papers

• Phe K, et al. AAC 2014;58(5):2740-6 (Polymixins Nephrotoxicity)

• Felton TW, et al. Clin Pharmacol Ther. 2014; 96(4): 438-48. (Pip-tazo)

• Spoorenberg V, et al. CID 2014; 58(2): 164-9. (UTI)

• DiazGranados CA, et al. NEJM 2014;371(7):635-45 (Influenza vaccine)

• Ahmed F, et al. CID 2014;58(1):50-57. (Influenza vaccine)

• Knoll GA, et al. JAMA 2014;312(20):2106-14. (BK virus)

• Afdhal N, et al. NEJM. 2014; 370(16): 1483-93. (Hepatitis C)

• Zeuzem S, et al. NEJM 2014;370:1604-1614. (Hepatitis C)

• Feld JJ, et al. NEJM 2014;370(17):1594-1603. (Hepatitis C)

• Corey GR, et al. NEJM 2014;370(23):2180-90. (Oritavancin)

• Moran GJ, et al. Lancet Infect Dis 2014;14(8):696-705. (Tedizolid)

• Boucher HW, et al. NEJM 2014;370(23):2169-79. (Dalbavancin)

• Ostrosky-Zeichner L, et al. CID 2014;58(9):1219-26. (Fungal infections)

• Beyda ND, et al. CID 2014;59(6):819-25. (Fungal infections)

β-Lactam PK in Sepsis: Background

• β-lactams commonly used in sepsis

• Dosing typically derived from healthy volunteers, less critically ill patients, and/or PK simulations

- PK-PD target: Time > MIC

• Critically ill patients have variable and often altered PK

- Larger volume of distribution

- Augmented renal clearance

- Low plasma albumin concentrations

• Design: Prospective, multicenter, PK point-prevalence study

Roberts JA, et al. CID 2014;58(8):1072-83.

Adult ICU Patient

+

Study Antibiotic

Amoxicillin, Ampicillin,

Cefazolin, Ceftriaxone,

Cefepime, Piperacillin,

Doripenem, Meropenem

HPLC

Sample A:

50% dosing interval

Sample B:

100% dosing interval

Determine PK/PD Targets 50% fT> MIC

100% fT > MIC

MIC=Minimum Inhibitory Concentration

• Estimated from epidemiological

data or highest possible

DALI: Results

Demographics Overall

N=361

Age 61 (48-73)

Weight, kg 75 (65-85)

APACHE II 18 (13-24)

CrCl, ml/min 80 (42-125)

Treatment of Infection 248 (68.7%)

Pathogen identified 72.9%

MIC determined 34.2%

Extended interval 67%

Combination therapy 62%

97 93.9

78.6 78.6 80.6

67

95

69.7

0

20

40

60

80

100

50% fT>MIC 100% fT>MIC

Achievement of PK-PD Target

Ceftriaxone Cefepime

Piperacillin Meropenem

Ceftriaxone (2g) Cefepime (6g)

Piperacillin (12g) Meropenem (3g)

Roberts JA, et al. CID 2014;58(8):1072-83.

DALI: Results

• Overall, 16% patients did not achieve 50% fT> MIC

- Less likely to have a positive clinical outcome

(OR 0.68 [95% CI 0.52-0.91]; p=0.009)

• Conclusions - Optimizing β-lactam dosing maybe needed in critically ill patients

- Should there be a more individualized approach to β-lactam dosing?

Roberts JA, et al. CID 2014;58(8):1072-83.

Daptomycin Dosing in Obesity:

Background

• Clinical controversy

• Pharmacokinetic studies in obese subjects - ↑ Cmax and AUC by 30-60%

• PK-PD studies - AUC/MIC target parameter

• Toxicodynamic study - Cmin levels ≥ 24.3 mg/L associated with CPK elevations

- Significant relationship between obesity & CPK elevation

- Monte Carlo simulation predicted similar Cmin levels if obese subjects dosed on lean body weight

• Clinical safety data - Multicenter retrospective cohort obese patients dosed based on

total body weight

- CPK elevations >500 units/L: 13.7%

Dvorchik BH, et al. J Clin Pharmacol 2005;45:48-56.

Pai MP, et al. AAC 2007;51(8):2741-7.

Bhavnani SM, et al. CID 2010;50(12):1568-74.

Bookstaver PB, et al. Pharmacotherapy 2013;33(12):1322-30.

Organism Target AUC/MIC

S. aureus 250-500

Enterococci 500-700

• Retrospective, before-after analysis

Ng JK, et al. AAC 2014;58(1):88-93.

July 1 2009-2011

Daptomycin > 72 hrs

Positive cultures

N = 308

Excluded N=191

No positive cultures

Prior to admission

Endocarditis

Prosthetic device

Renal impairment

ABW < IBW

ABW Dosing

N = 69

IBW Dosing

N = 48

• Primary outcome: Clinical success

- Cure = Resolution of s/sx and/or no additional G+ coverage

- Improvement = additional antibiotics but condition allowed

for de-escalation

Daptomycin: Demographics

Demographics ABW

N = 69

IBW

N = 48

P value

Weight (kg) 91.0 (24.8) 91.4 (21.9) 0.61

4 mg/kg

6 mg/kg

39 (56.5)

30 (43.5)

27 (56.2)

21 (43.8)

0.98

Duration 21.8 (26.1) 20.6 (19.5) 0.89

Combination G+ 7 (10.3) 8 (16.7) 0.31

Concomitant statin 34 (49.3) 11 (22.9) <0.01

Bacteremia

SSTI

IAI

UTI

OM

21 (30.4)

26 (37.7)

17 (24.6)

7 (10.1)

7 (10.1)

18 (37.5)

14 (29.2)

15 (31.2)

12 (25.0)

1 (2.1)

0.43

0.34

0.43

0.03

0.09

Enterococcus

MRSA

39 (56.5)

13 (18.8)

36 (75)

9 (18.8)

0.04

0.23

Ng JK, et al. AAC 2014;58(1):88-93.

Daptomycin: Results

• No difference in microbiological cure, mortality, or LOS

• No difference in CPK elevation

• Conclusions - First study to present clinical outcomes for IBW dosing

- In this cohort, no difference in clinical and microbiological outcomes

Ng JK, et al. AAC 2014;58(1):88-93.

Cefepime for Enterobacter:

Background

• Enterobacter spp. can be MDR due to presence of AmpC-type β-lactamases

• Cefepime is a poor inducer and stable to AmpC-type β-lactamases

- Zwitteronic structure

• In vitro data demonstrate cefepime activity

• Limited clinical data to support

Nikaido H, et al. AAC 1990;34:337-42.

Lagace-Wiens, et al. AAC 2011;55(5):2434-7.

Tamma PD, et al. CID 2013;57:781-8.

AmpC Hyperproducing (n=94) MIC 50 MIC 90

Ceftriaxone 16 32

Ceftazidime 16 64

Cefepime 0.25 0.5

• Retrospective review of all Enterobacter spp. bacteremias from 2005-2011

• Methods - Multivariable logistic regression models

adjusted for demographics and clinical characteristics

- Propensity-matched analysis

- Single or combination antimicrobial therapy

• Primary outcomes - Persistent bacteremia (≥ 1 day)

- In-hospital mortality

Siedner MJ, et al. CID 2014;58(11):1554-63.

Cefepime for Enterobacter: Results

12 12

0

13

10 11

21

17

0

8

21

15

25

16

26

24

0

5

10

15

20

25

30

Category 1 Category 2 Category 3 Category 4

Pro

port

ion

of pa

tien

ts

Chart Title

Quinolone Ceftazidime Cefepime Carbapenem

Single-agent

persistent bacteremia

Overall persistent

bacteremia

Single-agent mortality Overall mortality

Siedner MJ, et al. CID 2014;58(11):1554-63.

Cefepime for Enterobacter: Results

• No statistically significant difference between cefepime or carbapenem for rates of persistent bacteremia or mortality

- Propensity score analysis

- Subset resistant to ceftriaxone or cephamycins

• Conclusion

- Cefepime has similar clinical and microbiological efficacy to carbapenems for Enterobacter spp. bacteremia

Siedner MJ, et al. CID 2014;58(11):1554-63.

HCAP Treatment: Background

• Controversial concept

• Geographic variation

in MDR pathogens

• Overuse of broad

spectrum agents?

- Toxicity

- Resistance

- Collateral damage

ATS/IDSA Am J Respir Crit Care Med 2005;171:388-416.

Kollef MH, et al. Chest 2005;128:3854-62.

Healthcare Associated Pneumonia

Hospitalization ≥ 2 days in prior 90

Residence in NH or LTCF

Home infusion therapy / wound care

Chronic dialysis within 30 days

Family members with MDR pathogen

MRSA

Pseudomonas aeruginosa

Acinetobacter spp.

ESBL producing Enterobacteriaceae

Antipseudomonal β-lactam plus

Antipseudomonal FQ or AG plus

Linezolid or vancomycin

Ris

k F

acto

rs

Path

ogens

Tre

atm

ent

• Methods: - 1980-January 2013

published articles

- HCAP vs. CAP comparison

• Primary outcome - Frequency of

potential resistant organisms in HCAP group

Chalmers JD, et al. CID 2014;58(3):330-9.

HCAP Treatment: Results

PLR (95%CI) NLR (95%CI) AUC (95%CI)

All resistant 1.94 (1.67-2.24) 0.57 (0.50-0.66) 0.70 (0.69-0.71)

MRSA 1.97 (1.74-2.22) 0.44 (0.35-0.55) 0.74 (0.72-0.76)

Enterobacteriaceae 1.37 (1.26-1.49) 0.76 (0.69-0.84) 0.60 (0.58-0.62)

P. aeruginosa 1.68 (1.53-1.84) 0.62 (0.52-0.74) 0.68 (0.66-0.70)

Clinically Useful >10 <0.10 <0.75

• No significant increase in mortality associated with HCAP (OR 1.20; 95%CI 0.85-1.70; p=0.3)

• Conclusions - Current HCAP criteria do not accurately identify resistant

pathogens

- MDR risk factors may need to be pathogen specific

- Emphasize importance of local microbiology/epidemiology

Chalmers JD, et al. CID 2014;58(3):330-9.

PLR = positive likelihood ratio

NLR = negative likelihood ratio

AUC = area under the curve

Azithromycin & Cardiovascular

Events: Background

Ray WA, et al. NEJM 2012;366(20):1881-90.

Svanstrom H, et al. NEJM 2013;368(18):1704-12.

Rao GA, et al. Ann Fam Med 2014;12(2):121-7.

2012 2013 2014

• Retrospective population-based cohort

• Veterans Administration database

• Propensity score matching

Design

•Age ≥ 65 and diagnosis of pneumonia •Hospitalized October 2001 – September 2012 •IDSA/ATS recommended antibiotic for CAP within 48 hrs

Inclusion

• 30-day and 90-day all cause mortality

• Cardiovascular events within 90 days of admission

Outcomes

Mortensen EM, et al. JAMA 2014;311(21):2199-2208.

Azithromycin & CV Events: Results

Azithromycin

N=38787

No

Azithromycin

N=34903

P value

Any CV event 43% 42.7% 0.38

Heart Failure 26.3% 26.2% 0.73

MI 5.1% 4.4% <0.001

Arrhythmia 25.8% 26.0% 0.52

Survival Curve

90 day mortality: 17.4% azithromycin vs.

22.3% no azithromycin; p<0.001

• Conclusions

- Among older hospitalized patients with pneumonia, azithromycin was associated with an overall net benefit

Mortensen EM, et al. JAMA 2014;311(21):2199-2208.