DEATH DESPITE APPROPRIATE ANTIBIOTICS 7... · Marin H. Kollef, MD Professor of Medicine Virginia E....

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DEATH DESPITE APPROPRIATE

ANTIBIOTICS

Marin H. Kollef, MD

Professor of Medicine

Virginia E. and Sam J. Golman Chair in

Respiratory Intensive Care Medicine

Washington University School of Medicine

St. Louis, Missouri

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Conflicts of Interest 1.Merck

2.Actavis

3.Arsanis

4.Cardeas

5.Cubist

6.Medimmune

7.Astrazeneca

8.Accelerate

9.Academy for Infection Management

10.Barnes-Jewish Hospital Foundation

3 The Review on Antimicrobial Resistance Chaired by Jim O’Neill December 2014

Commissioned Report By

UK Government and

the Wellcome Trust

> Ten Million Deaths

Yearly By 2050 A global problem!

4

DEATH DESPITE APPROPRIATE ANTIBIOTICS

• Host factors

• Pathogen virulence

• Antibiotic concentrations

• Source control

• Other complications

5


• Host factors



• Source control


6 Tang J and Chan P. N Engl J Med 2007;357:1855

7

Immunologic Response to Critical illness

Hyp

eri

mm

un

e

No

rmal

Hyp

oim

mu

ne

Imm

un

e S

tatu

s

Days

Healthy Person

Elderly patient with malnutrition & alcoholism

Patient w/ diabetes, chronic renal failure, &

pneumonia

Hotchkiss R and Karl I. N Engl J Med 2003;348:138-150.

Recovery

Death

8 Limaye, A. P. et al. JAMA 2008;300:413-422.

ICU Patients – Continued

hospitalization or death

9 Boomer JS, et al. JAMA 2011; 306: 2594–2605.

Apoptosis of CD4, CD8, and HLA-DR cells

(dendritic cells, macrophages, and B cells)

10 PD-1 = Programmed Cell Death Protein 1

Hotchkiss RS, et al. Lancet Infect Dis. 2013; 13: 260–268

Interleukin 7 and anti-PD-1 immunotherapy in sepsis

PD-1 = Programmed

Cell Death Receptor-1

11

Antigen Presenting Cell (APC) and T cell Interactions

- inhibitory pathways PD-1 and CTLA-4

Apoptotic cell death

12

Topalian et al. NEJM online June 2nd 2012.

Brahmer et al. NEJM online June 2nd 2012.

13

• 87% response rate among heavily pretreated patients with

Hodgkin’s lymphoma receiving nivolumab (anti-PD-1)

• 40% response rate for patients with malignant melanoma

treated with anti-PD-1

January 22nd , 2015

14

• Apoptosis-induced immunosuppression

(immune effector cells / tumor cells)

• Chronic Ag stimulation (DAMPs/PAMPs) leading to T cell exhaustion

• Expression of neg co-stimulatory molecules (PD-1, PD-L1, CTLA4)

• Increased anti-inflammatory cytokine production

• Decreased expression of HLA-DR class I and class II

• Increased myeloid suppressor cells

• Increased T regulatory cells.

Given common immunosuppressive mechanisms, it is likely that the

immunotherapeutic drugs that work in cancer may work in sepsis as well.

15 Hotchkiss RS, Moldawer LL. N Engl J Med 2014;371:380-383.

Immune Phenotypes of Cancer & Protracted Infection

16 Chang K, et al. Crit Care 2014, 18:R3.

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• Host factors



• Source control


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Toxic protein exoproducts of P. aeruginosa

Exoproduct Gene symbol

Pseudomonas

genome database

locus tag

Secretory type Activity Effect on host

Alkaline protease aprA PA1249 I Proteolysis

Blocks

complement

activation

Elastase (LasA

and LasB) lasA and lasB PA1871 and PA3724 II Elastolytic activity Tissue destruction

Exotoxin A toxA PA1148 II ADP-

ribosyltransferase Cytotoxin

Phospholipase C plcH and plcN PA0844 and PA3319 II Phospholipase C Heat-labile

hemolysis

ExoS (exoenzyme

S, 49-kDa) exoS PA3841 III

ADP-

ribosyltransferase,

GAP

Anti-phagocytosis

ExoT (exoenzyme

S, 54-kDa exoT PA0044 III GAP activity

Blocks wound

healing

ExoU exoU - III Phospholipase A2 Cytotoxin, anti-

phagocytosis

ExoY exoY PA2191 III Adenylate cyclase Edema formation

Sawa et al. Critical Care 2014 18:668.

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Alveolar epithelial injury caused by the ExoU

cytotoxin of Pseudomonas aeruginosa

Sawa et al. Critical Care 2014 18:668.

Pseudomonas aeruginosa type III secretion system

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Probability estimate for 5-day mortality of P. aeruginosa bacteremia

according to type III secretion system exoU genotype and MDR status

Peña C, et al. Clin Infect Dis 2015;60:539-548.

P < 0.002 P < 0.28

Early Mortality

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Probability estimate for 30-day mortality of P. aeruginosa bacteremia

according to type III secretion system exoU genotype and MDR status


P < 0.58 P < 0.02

Late Mortality

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Variables

Crude Analysis Adjusted Analysis

HR (95% CI) P Value HR (95% CI) P Value

Non-MDR P. aeruginosa susceptibility

No

Yes 1.23 (.79–1.90) .34

TTSS exoU

No

Yes 1.81 (1.24–3.16) .004 1.90 (1.15–3.14) .01

Adequate empiric antibiotic

No

Yes 0.89 (.57–1.39) .62

Cox Regression Analysis of Predictors for Early

Mortality of P. aeruginosa Bloodstream Infection


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Variables

Crude Analysis Adjusted Analysis

HR (95% CI) P Value HR (95% CI) P Value

MDR P. aeruginosa susceptibility

No

Yes 1.42 (1.04–1.93) .026 1.40 (1.01–1.94) .04

TTSS exoU

No

Yes 0.90 (.62–1.30) .58

Adequate definitive antibiotic

No

Yes 1.33 (.71–2.49) .44

Cox Regression Analysis of Predictors for 30-Day

Mortality of P. aeruginosa Bloodstream Infection


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Determinants of Outcome in P. aeruginosa Infections

Early Late

Virulence Antibiotic Resistance

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Panobacumab treatment in immunosuppressed P.

aeruginosa-infected mice (Pneumonia)

Secher T, et al. PLoS ONE 2013;8(9): e73396. doi:10.1371/journal.pone.0073396.

IgM/κ monoclonal

antibody directed

against the LPS O-

polysaccharide moiety

of P. aeruginosa

serotype IATS O11

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(A) Patients with nosocomial

Pseudomonas aeruginosa O11

pneumonia receiving ≥1 dose of

panobacumab (blue: intent-to-treat

group; n = 17) versus untreated

patients (red: n = 14). p-Value (log-rank

test): 0.3008.

(B) Patients with nosocomial P.

aeruginosa O11 pneumonia receiving

the full treatment (three doses) of

panobacumab (blue: per-protocol

group; n = 13) versus untreated

patients (red: n = 14). p-Value (log-rank

test): 0.0045.

Que YA, et al. Eur J Clin Microbiol Infect Dis 2014;33:1861-1867.

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• Host factors



• Source control


29 Kollef, MH, et al. Crit Care 2012;16(6):R218.

CPIS for Pseudomonas aeruginosa MITT

0

1

2

3

4

5

6

7

8

1 2 3 4 5 6 7 8 9 10 11

To

tal

CP

IS s

co

re

Study Day

Doripenam

Imipenam

EOT Doripenem

30

0

20

40

60

80

100

120

1 3 5 7 9 11 13 15 17 19 21 23 25 27

Pro

bab

ilit

y o

f S

urv

ival

Doripenam

Imipenam

28-Day All Cause Mortality: P. aeruginosa

P=0.040, Log-Rank Test

Kollef, MH, et al. Crit Care 2012;16(6):R218.

EOT

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Doripenem Mean Concentration by CrCl

Time (Hours)

0 1 2 3 4 5 6

Do

rip

enem

Pla

sma

Co

nce

ntr

atio

n (

µg

/mL

)

0

5

10

15

20

25Super Normal Renal Function (n=10)

Normal Renal Function (n=12)

Mild Renal Impairment (n=15)

Moderate Renal Impairment (n=4)

Severe Renal Impairment (n=2)

Supra Normal Renal Function n=10 10.7 (33.5) ug/mL

Normal Renal Function n=12 18.1 (30.8) ug/mL

Mild Renal Impairment n=15 15.1 (46.6) ug/mL

Moderate Renal Impairment * n=4 10.5 (10.6) ug/mL

Severe Renal Impairment* n=2 16.3 (10.4) ug/mL

Mean Cmax (%CV)

Note that full

dose interval is

8 hours*

* Subjects with moderate renal impairment

Rx with 500mg q8h; severe with 500mg q12h

PK similar in males and females

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β-lactam Underdosing in Patients with

Augmented Renal Clearance (ARC)?

ARC = supranormal

glomerular filtration

ClCr > 130 ml/min/1.73m2

Cockcroft Gault ClCr =

(140-age) x Wt x 1.73

(Scr x 72 x BSA) x 0.85 (female)

Most common in critically

ill patients with:

– SIRS/Sepsis

– Trauma

Tro

ugh c

once

ntr

ation:M

IC

1

10

100

50 100 150 200 250 300 350

ClCr (ml/min/1.73m2)

Udy AA et al. Chest 2012;142:30-39. Baptista JP et al. Crit Care 2011;15:R139.

33 Basilea (On File)

Ceftobiprole 500 mg q 8 hours as a 120-minute infusion

Linezolid 600 mg q 12 hours as a 60-minute infusion & Ceftazidime 2 g q 8 hours

as a 120-minute infusion

VERSUS

Dosing in VAP Matters!

Infection

type

Treatment group Predicted

mortality*

(%)

Actual mortality

(%)

Non-VAP Ceftobiprole 18.5 18.8

Non-VAP Linezolid/Ceftazidime 19.0 21.2

VAP Ceftobiprole 24.2 33.7

VAP Linezolid/Ceftazidime 24.2 22.6

*Based on Knaus et al. Crit Care Med 1985;13:818

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Mortality/Noncure Rates: Tigecycline vs Comparators

Prasad P et al. Clin Infect Dis. 2012;54:1699-1709.

100 mg IV initial dose, followed by 50 mg IV every 12 hours.

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PK/PD RATIOS OBSERVED AT 50% (A) AND

100% (B) OF THE DOSING INTERVAL

Roberts J A et al. Clin Infect Dis. 2014;58:1072-1083.

Ratio of 1 minimal

PK/PD target

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A, EFFECT OF INCREASING PK/PD RATIO AT 50% OF DOSING

INTERVAL INTERACTION WITH APACHE II ON PROBABILITY

OF POSITIVE CLINICAL OUTCOME (N = 248; Y-AXIS)

Roberts J A et al. Clin Infect Dis. 2014;58:1072-1083.

All No RRT

0 – 14

18 - 24

APACHE II

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• Host factors



• Source control


38 Kollef M, et al. Clin Infect Dis. 2012;54:1739-1746.

N = 180

N = 44

P < 0.001

Early treatment of candidemia decreases

mortality of ICU patients with septic shock

39 Kollef M, et al. Clin Infect Dis. 2012;54:1739-1746.

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I. Adequate therapy and adequate source control

II. Adequate therapy and inadequate source control

III. Inadequate therapy and inadequate source control

(I versus III, P< .001; log-rank test)

Multicenter Study of Candida Septic Shock :

Outcomes and Predictors of Mortality (N = 216)

Bassetti M, et al. Intens Care Med 2014;40:839-845.

Hospital Days

% S

urv

ival

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• Host factors



• Source control


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VTE Incidence and Risk Factors in Patients

With Severe Sepsis and Septic Shock

Kaplan D, et al. Chest. 2015;148:1224-1230.

N = 113

43 ARISE Investigators. N Engl J Med 2014;371:1496-1506.

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Conclusions Mortality in severe sepsis and septic shock is

often dictated by non-antibiotic factors:

• Host Factors

• Pathogen Virulence

• Source Control

• Other Complications

Therefore, interventions aimed at treating or

modifying these factors are needed to optimize

patient outcomes.

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Thank you!

DEATH DESPITE APPROPRIATE ANTIBIOTICS 7... · Marin H. Kollef, MD Professor of Medicine Virginia E....

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