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Empiric Echinocandin Therapy in Sepsis: Echino-“Can It Work” or Echino-“Can You Not”?

Luke Smedley, PharmD PGY-2 Critical Care Pharmacy Resident

Department of Pharmacotherapy and Pharmacy Services, University Hospital Division of Pharmacotherapy, University of Texas at Austin College of Pharmacy

Pharmacotherapy Education and Research Center, UT Health San Antonio San Antonio, Texas

August 8 and 17, 2018

Learning Objectives

1. Differentiate various diagnostic tools for invasive candidiasis and describe situations wherefalse positives or false negatives may arise

2. Appraise the data surrounding azole versus echinocandin therapy for invasive candidiasis3. Defend the choice to initiate or defer initiation of echinocandin therapy in a patient with

sepsis without proven invasive candidiasis

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Assessment Questions:

1. Which diagnostic tool provides the fastest results confirming the presence of a Candida spp. in the bloodstream?

a. BioFire FilmArray® Blood Culture ID Panel b. (1-3)-β-D-glucan c. T2Candida® d. Traditional blood culture

2. True or false: in clinical trials, fluconazole therapy has been consistently shown to

have better outcomes than echinocandin therapy.

3. True or false: due to their once daily dosing and limited side-effect profile, echinocandins can safely be given to all patients with septic shock without consequences.

***To obtain CE credit for attending this program please sign in. Attendees will be emailed a link to an electronic CE Evaluation Form. CE credit will be awarded upon completion of the electronic form. If you do not receive an email within 72 hours, please contact the CE Administrator at [email protected] *** Faculty (Speaker) Disclosure: Luke Smedley has indicated he has no relevant financial relationships to disclose relative to the content of this presentation.

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Invasive Candidiasis

1. Introduction1-4

a. Most common fungal disease in hospitalized patients

b. Ranks in top three or four pathogens causing nosocomial bloodstream infections (BSIs) in developed

countries

Table 1. Incidence rates, pathogen distribution, and crude mortality of nosocomial BSIs5

Pathogen BSIs per 10,000

admissions Percentage of BSIs Crude mortality, %

^ICU Non-ICU ICU Non-ICU

CoNS* 15.8 35.9 26.6 25.7 13.8

Staphylococcus aureus 10.3 16.8 23.7 34.4 18.9

Candida spp. 4.6 10.1 7.9 47.1 29.0

Escherichia coli 2.8 3.7 7.6 33.9 16.9

Klebsiella spp. 2.4 4.0 5.5 37.4 20.3

Pseudomonas aeruginosa 2.1 4.7 3.8 47.9 27.6

*Coagulase-negative Staphylococcus spp.

^Intensive Care Unit

i. Approximately 50% of candidemia cases occur in the ICU6

c. Epidemiologic studies of sepsis and septic shock have shown that approximately 3% of cases are due to fungal

pathogens7

d. Rates of community-acquired candidiasis rising due to:

i. Increased usage of long-term intravenous access devices (e.g. peripherally inserted central catheters

[PICC] lines and tunneled catheters)

ii. Outpatient parenteral antimicrobial therapy

2. Early appropriate treatment of invasive candidiasis (IC) is extremely important, as mortality is high with inappropriate

treatment and inadequate source control

a. In a study of patients with septic shock and a positive blood culture for Candida spp., mortality was

independently predicted by inadequate source control (AdjOR 77.4, 95% CI 21.52-278.38, p = 0.001) and

delayed antifungal treatment (AdjOR 33.75, 95% CI 9.65-118.04, p = 0.005) in a multivariate analysis8

i. Patients who survived were more likely to have received an echinocandin than patients who did not

(76.8% vs 49.0%, p < 0.001)

b. Another study of patients with septic shock attributed to Candida spp. found appropriate antifungal therapy

(OR 5.99, p = 0.048) and source control (OR 2.99, p = 0.001) to be independent predictors of hospital survival

in a multivariate analysis9

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Figure 1. Pathogenesis of invasive candidiasis2

3. Pathophysiology2

a. Candida spp. can cause infections of various organ systems2,10

i. Non-invasive infections generally occur as cutaneous or mucosal infections

ii. Invasive infections include BSIs, intra-abdominal infections, peritonitis, osteomyelitis, and other deep-

seated organ infections

b. Generally commensal organisms, but can turn into opportunistic pathogens

i. Occurs in context of mucosal microbiota changes and/or weakening of host’s immune system

c. Predisposing conditions for invasive infection

i. Long-term and/or repeated use of broad-spectrum antibiotics

1. Commensal gut microbiota species induce release of anti-Candida spp. protective factors

from mucosa11

2. Depletion of microbiota species removes protective factors and enables Candida spp.

overgrowth

ii. Breach of gastrointestinal and cutaneous barriers

1. Can occur with chemotherapy-induced mucositis, gastrointestinal surgery/perforation, or

central venous catheters

2. Enable commensal Candida spp. to travel from mucocutaneous sites to bloodstream

iii. Iatrogenic immunosuppression

1. Includes chemotherapy-induced neutropenia and corticosteroid therapy

2. Impairs innate immune defenses in tissues, which facilitates Candida spp. invasion from

bloodstream to organs

a. Can lead to infections in liver, spleen, kidneys, heart, or brain

d. Myeloid phagocytes (i.e. neutrophils, monocytes, macrophages, dendritic cells) are key in controlling and

preventing development of invasive candidiasis12,13

4. Causative pathogens1,2

a. At least 15 different species known to cause disease

b. Most common pathogenic species

i. Candida albicans – most prevalent species

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ii. Candida glabrata – second most common species in US and northwestern Europe

1. More common in patients > 60 years of age and in solid organ transplant

iii. Candida tropicalis and Candida parapsilosis – more common in Latin America, Southern Europe, India,

and Pakistan

1. C. parapsilosis more common in pediatric and neonatal patients14

iv. Candida krusei – more common in patients with underlying hematological malignancies who received

antifungal prophylaxis with fluconazole

c. Candida auris is emerging as a pathogen in certain areas of the world15

i. Often multidrug-resistant and develops resistance during therapy

ii. Frequently misclassified as other Candida spp.

Diagnosis and Diagnostic Challenges

1. Gold standard for IC diagnosis is positive culture2,16

a. Sensitivity of blood culture for diagnosis is approximately 50% in patients with autopsy-proven IC2,10

i. Due to low inoculum during candidemia episodes (< 1 colony-forming unit (cfu)/mL)

b. Strategies to improve sensitivity of blood cultures include frequent sampling, larger culture volumes, use of

specialized fungal culture bottles, and sampling prior to receipt of antifungal therapy

i. Infectious Diseases Society of America (IDSA) guidelines for diagnosis of infection mention that

specialized blood cultures may be used, but are not required

c. Blood cultures have slow turnaround times (median time to positivity of 2-3 days, range 1 to ≥7 days)

d. PCR-based tests (e.g. BioFire FilmArray® Blood Culture ID panel) allow for identification of five most common

species (C. albicans, C. glabrata, C. krusei, C. tropicalis, and C. parapsilosis) from positive blood culture

i. Study of FilmArray® versus traditional blood culture identification methods showed that FilmArray®

identified infecting Candida spp. in a mean of 1 hr 12 min ± 23 min from positive blood culture

compared to 3-5 days for traditional blood culture methods17

e. Patients with non-candidemic IC require positive culture and/or histopathology from suspected infection site

2. T2 magnetic resonance assay (T2Candida®)10

a. Allows for pathogen detection from whole blood rather than needing to wait for positive blood culture

b. T2Candida Panel is approved by FDA with a sensitivity and specificity of 91.1% and 99.4%, respectively18

i. May also identify patients with lower inoculum who would normally have negative blood cultures

c. A study of time evaluating T2Candida versus traditional blood culture saw a reduction in time to appropriate

antifungal therapy (22 hrs vs 39 hrs, p = 0.003)19

d. T2Candida does not provide information on specific species; can only place in one of three groups:

i. C. albicans or C. tropicalis

ii. C. glabrata, C. krusei, Saccharomyces cerevisiae, or C. bracarensis

iii. C. parapsilosis, C. metapsilosis, or C. orthopsilosis

3. (1-3)-β-D-glucan10

a. β-D-glucan is a cell wall constituent in Candida spp., Aspergillus spp., and Pneumocystis jirovecii

b. Approved in US as an adjunct to cultures for diagnosis of invasive fungal infections

c. Sensitivity and specificity for diagnosis of IC was 75-80% and 80% in multiple meta-analyses20-22

d. False-positives are common in ICU patients

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Table 2. Causes of false-positive (1-3)-β-D-glucan tests10

Other systemic infections Exposure to β-lactam therapy

Hemodialysis Fungal colonization

Exposure to albumin Exposure to intravenous immunoglobulin (IVIG)

Use of surgical gauze containing glucan Disruptions of gastrointestinal mucosa

4. Guideline recommendations

a. IDSA 201610

i. No specific recommendations about how to diagnose candidemia or IC

ii. Due to low sensitivity and specificity of diagnostic tests, most treatment is initiated based on clinical

gestalt

Management

1. Non-pharmacological treatment10

a. Source control is most important aspect of candidiasis management

i. Central lines should be removed if possible in patients with proven or suspected candidemia

ii. Patients with a drainable source should receive appropriate drainage and/or debridement

iii. Patients with candidiasis of implantable devices should have devices removed if possible or receive

long-term suppression therapy

b. Non-neutropenic patients with candidemia need a dilated ophthalmological exam to rule out ocular candidal

infections

i. As many as 16% of patients with candidemia will have ocular involvement that could lead to

endophthalmitis

2. Pharmacological treatment10

a. Echinocandins are recommended as initial therapy in critically ill, non-neutropenic patients with IC

i. De-escalate to fluconazole after 5-7 days if patient is clinically stable, has isolate susceptible to

fluconazole, and negative repeat blood cultures

b. Echinocandins inhibit (1-3)--D-glucan synthesis by binding to (1-3)--D-glucan synthase

i. Compromises integrity and shape of fungal cell wall

ii. Causes osmotic lysis of cell, resulting in fungicidal activity against Candida spp.

Table 3. Pharmacologic characteristics of echinocandins23,24

Mode of Fungicidal Activity Concentration-dependent

PK/PD Target AUC/MIC > 3000 for non-parapsilosis spp.

AUC/MIC > 285 for C. parapsilosis

Absorption Poorly absorbed through GI tract

Only available IV

Distribution

Limited distribution to CNS and eyes

Very high protein binding (>95%)

Metabolism Caspofungin and micafungin undergo hepatic metabolism

Dose reductions recommended for caspofungin in hepatic dysfunction Elimination Long half-life (10-26 hrs)

Dosed once daily

Eliminated through nonenzymatic degradation to inactive products

Excreted via feces

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Dosing Caspofungin: 70 mg loading dose, then 50 mg every 24 hours (50 mg/m2/day)

Micafungin: 100 mg every 24 hours (1-3 mg/kg/day)

Anidulafungin: 200 mg loading dose, then 100 mg every 24 hours (no weight-based dose)

Spectrum of Activity Potently fungicidal against majority of Candida spp.

Higher MICs for C. parapsilosis and C. guilliermondii

Fungistatic against Aspergillus spp.

Side Effects Side effects are rare, but more common with caspofungin

Phlebitis, fever, abdominal pain, nausea/vomiting, diarrhea, headache, rash, pruritis, leukopenia, neutropenia, thrombocytopenia, hypokalemia, abnormal LFTs

Abbreviations: AUC = area under the time-concentration curve, CNS = central nervous system, GI = gastrointestinal, IV = intravenous, LFT = liver function test, MIC = minimum inhibitory concentration

3. Multiple studies favor use of an echinocandin for management of IC

Table 4. Studies of fluconazole versus echinocandins for invasive candidiasis

Study Intervention Results

Reboli AC, Rotstein C, Pappas PG, et al. Anidulafungin versus fluconazole for invasive candidiasis. N Engl J Med. 2007;356:2472-82.

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Prospective, randomized controlled trial of anidulafungin (200 mg IV on day 1, then 100 mg IV daily) vs fluconazole (800 mg IV on day, then 400 mg IV daily)

Global response at end of IV therapy: 75.6% anidulafungin vs fluconazole 60.2% (p = 0.01) o Remained significant when

adjusted for baseline characteristics of immunosuppressive therapy, diabetes, prior azole therapy, presence of C. glabrata, and catheter removal

Remained significant at end of all treatment and 2-week follow-up

Lost statistical superiority at 6-week follow-up

Andes DR, Safdar N, Baddley JW, et al. Impact of treatment strategy on outcomes in patients with candidemia and other forms of invasive candidiasis: a patient-level quantitative review of randomized trials. Clin Infect Dis. 2012;54:1110-22.

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Patient-level meta-analysis of treatments for IC

Echinocandin use associated with improved 30-day all-cause mortality (OR 0.65, 95% CI 0.45-0.94, p = 0.02)

Also associated with higher success rate at end of therapy (OR 2.33, 95% 1.27-4.35, p = 0.01)

Eschenauer GA, Carver PL, Lin SW, et al. Fluconazole versus an echinocandin for Candida glabrata fungaemia: a retrospective cohort study. J Antimicrob Chemother. 2013;68:922-6.

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Retrospective cohort study of fluconazole versus an echinocandin for candidemia due to C. glabrata

In multivariate analysis, echinocandin use was associated with increased odds of complete response at day 14 (OR 2.305, 95% CI 1.124-4.727, p = 0.023)

Echinocandin use was not associated with 28-day survival (OR 1.843, 95% CI 0.835-4.069, p = 0.13)

4. Multiple mechanisms of resistance have been reported28

a. Adaptive stress response

i. When synthesis of (1-3)--D-glucan is inhibited, cell wall increases synthesis of chitin

ii. Compensatory increase in chitin synthesis occurs in response to echinocandin exposure in Candida

spp.

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iii. Has been seen in most Candida spp., but is more common in C. albicans

iv. Elevated cell wall chitin content is associated with protection against echinocandins

v. Some studies show paradoxical effect of high levels of caspofungin on C. albicans, where C. albicans is

able to grow at higher serum concentrations

1. May be due to higher chitin contents in fungal cell wall, reducing ability of caspofungin to

exhibit its mechanism of action

b. Acquired FKS mutations

i. Glucan synthase (molecular target of echinocandins) is made of at least two subunits: FKS1p

(encoded by genes FKS1, FKS2, and FKS3) and Rho1p

ii. Amino acid substitutions in FKS subunits confer reduced echinocandin susceptibility

iii. These mutations can be gained, and have been seen in C. albicans, C. tropicalis, C. krusei, and C.

glabrata

c. Intrinsic FKS mutations

i. C. parapsilosis and C. guilliermondii have naturally occurring mutations in FKS genes that confer

reduced susceptibility to echinocandins

ii. These species have consistently higher MIC values than other Candida spp.

iii. Echinocandins have still shown clinical efficacy in treatment of these species

5. Resistance is emerging as use of echinocandins increases

a. Pre-exposure to fluconazole or caspofungin was associated with decreased prevalence of C. albicans and an

increased prevalence of less susceptible species, such as C. glabrata and C. krusei, in a multicenter

prospective observational study of candidemia29

i. Recent exposure to caspofungin was independently associated with increased risk of infection with

isolate with decreased echinocandin susceptibility (OR 4.79, 95% CI 2.47-9.28, p < 0.001)

b. A single-center study evaluating echinocandin resistance in C. glabrata showed resistance increased from

4.9% of isolates in 2001 to 12.3% in 201030

i. In addition, prior echinocandin therapy independently predicted presence of an FKS mutant strain of

C. glabrata (OR 19.647, 95% CI 7.19-58.1)

Empiric Antifungal Therapy in Critically Ill Patients

1. Various treatment strategies have been suggested to reduce mortality with IC31

a. Prophylaxis = treat patients with high-risk of IC (> 5-10%) to prevent development of infection

b. Pre-emptive therapy = treat patients with one or more biological markers of infection risk (e.g. elevated β-D-

glucan, widespread Candida spp. colonization)

c. Empiric treatment = treat patients with continued signs of infections and clinical suspicion of IC without

proven fungal infection

2. Guidelines suggest therapy should be considered in critically ill patients with risk factors for IC and no other cause of

fever10

Table 5. Risk factors for invasive candidiasis10

Candida spp. colonization Increased severity of illness

Exposure to broad-spectrum antibiotics Recent major surgery

Abdominal surgery/procedures Hemodialysis

Total parenteral nutrition (TPN) High-dose corticosteroids

Use of central venous catheters Necrotizing pancreatitis

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3. Epidemiologic studies cited by guidelines for risk factors were done in surgical ICU patients32,33

a. Largest epidemiologic study of patients with candidemia identified risk factors listed above, but only prior

surgery (RR 7.3, 95% CI 1.0-53.8, p = 0.05), acute renal failure (RR 4.2, 95% CI 2.1-8.3, p < 0.001), and receipt

of parenteral nutrition (RR 3.6, 95% CI 1.8-7.5, p < 0.001) remained significant in multivariate analysis32

b. In subgroup of patients who actually underwent surgery, above risk factors remained significant as well as

triple-lumen catheter placement (RR 5.4, 95% CI 1.2-23.6, p = 0.03)

4. Risk factors included in guidelines are broad and apply to almost every ICU patient, however incidence of candidiasis

in the ICU is only about 10%10

Clinical Controversy #1

How do we predict who has invasive candidiasis in critically ill patients?

Table 6. Risk scores for prediction of invasive candidiasis and/or candidemia

Study Patient Population Risk Scoring Results

León C, Ruiz-Santana S, Saavedra P, et al. A bedside scoring system ("Candida score") for early antifungal treatment in nonneutropenic critically ill patients with Candida colonization. Crit Care Med. 2006;34:730-7.

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Patients admitted for at least seven days to ICU

Excluded neutropenic patients

TPN = 1 point

Surgery on ICU admission = 1 point

Multifocal Candida spp. colonization = 1 point

Severe sepsis = 2 points

A score of > 2.5 had sensitivity of 81% and specificity of 74% for diagnosis of IC

OR of proven infection with score > 2.5 was 7.75 (95% CI 4.74-12.66)

AUROC = 0.847 (95% CI 0.8-0.894)

Shorr AF, Tabak YP, Johannes RS, et al. Candidemia on presentation to the hospital: development and validation of a risk score. Crit Care. 2009;13:R156.

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Admitted to acute care hospital

Age < 65 years

Temp ≤ 98° F OR severe altered mental status

Cachexia

Previous hospitalization within 30 days

Admitted from other healthcare facility

Mechanical ventilation at admission

Candidemia rates by score (P < 0.0001) o 0 = 0.4% o 1 = 0.8% o 2 = 1.6% o 3 = 3.2% o 4 = 4.2% o 5 = 9.6% o 6 = 27.3%

AUROC = 0.70

NPV 99% with score < 3

Hermsen ED, Zapapas MK, Maiefski M, et al. Validation and comparison of clinical prediction rules for invasive candidiasis in intensive care unit patients: a matched case-control study. Crit Care. 2011;15:R198.

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ICU stay ≥ 4 days

Excluded patients with IC or receipt of antifungal agents prior to day 4 of ICU stay

Broad-spectrum antibiotics on any of days 1-3 of ICU stay = 1.537 points

CVC on any of days 1-3 of ICU stay = 0.873 points

TPN on any of days 1-3 of ICU stay = 0.922 points

Corticosteroids from 7 days before ICU admission to day 3 of ICU stay = 0.402 points

Abdominal surgery = 0.879 points

Increasing pre-ICU LOS = 0.039 per day

Sensitivity 84.1% and specificity 60.2% for score > 2.45

PPV 4.7% and NPV 99.4% for score > 2.45

AUROC = 0.77

Abbreviations: AUROC = area under the receiver operating curve, CVC = central venous catheter, LOS = length of stay, NPV = negative predictive value, OR = odds ratio, PPV = positive predictive value,

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1. Further studies confirmed no score is perfect, either having low sensitivity (thus missing many patients with IC) or low

specificity (including many patients without IC)

a. Validation study of Candida score in patients with sepsis or septic shock showed Candida score > 3 had PPV of

23.8% and NPV of 100% for IC37

b. Study comparing use of (1-3)--D-glucan levels versus Candida score or Candida colonization index showed

varied sensitivity, specificity, PPV, and NPV38

Table 7. Sensitivity, specificity, PPV, and NPV of various prediction tools38

Prediction Method Sensitivity (%)

(95% CI) Specificity (%)

(95% CI) PPV (%) (95% CI)

NPV (%) (95% CI)

(1-3)--D-glucan > 80 pg/mL 92.9 (66.1-99.8) 93.7 (85.8-97.9) 72.2 (46.5-90.3) 98.7 (92.8-99.9)

Candida score 3 85.7 (57.2-98.2) 88.6 (79.5-94.7) 57.1 (34.0-78.2) 97.2 (90.3-99.7)

Colonization index 0.5 64.3 (35.1-87.2) 69.6 (58.2-79.5) 27.3 (13.3-45.5) 91.7 (81.6-97.2)

2. Development of a clinical prediction rule for candidemia specifically in patients presenting with sepsis or septic shock

Table 8. Guillamet CV, Vazquez R, Micek ST, et al. Development and validation of a clinical prediction rule for candidemia in hospitalized patients with severe sepsis and septic shock. J Crit Care. 2015;30:715-20.39

Design and Methods

Retrospective, cohort study to develop and internally validate a prediction rule to identify patients with sepsis or septic shock at risk for candidemia

Population Inclusion Exclusion

Presence of positive blood culture combined with primary or secondary ICD-9-CM codes indicative for sepsis and acute organ dysfunction and/or need for vasopressors

o Sepsis had to be temporally related (± 24 hours) to positive blood cultures

Isolation of usual blood culture contaminants (e.g. CoNS, Corynebacterium spp.)

o Included if had multiple cultures positive for same organism or if clinical scenario qualified organism as true pathogen

Factors Evaluated Presence of CVC for ≥48 hours prior to positive blood cultures

Mechanical ventilation

Septic shock (versus sepsis)

Prior antibiotic use within preceding 30 days

Diabetes mellitus

Presence of immunosuppression (e.g. hematologic malignancies, solid organ or bone marrow transplants, AIDS, long term or high dose corticosteroid administration, or administration of chemotherapy and/or radiation therapy)

TPN

Recent surgery

Duration of hospitalization prior to bloodstream infection

Recent hospitalization within preceding 90 days

Endpoints Presence of candidemia

Baseline Characteristics

n = 2597

Variable Candidemia

(n = 266) Non-candidemia

(n = 2331) p-value

Age in yrs, mean ± SD 61.4 ± 16 60.3 ± 15.8 0.275

Sex, male, n (%) 125 (47) 1299 (55.8) 0.008

Admission source, n (%) <0.001

Home 124 (46.6) 1540 (66.1)

Nursing home 31 (11.7) 197 (8.5)

Transferred from outside hospital 107 (40.2) 559 (24)

Charlson comorbidity score, median (IQR) 4 (2-7) 4 (2-7) 0.532

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Diabetes mellitus, n (%) 71 (26.7) 630 (27) 0.907

Cirrhosis, n (%) 40 (15) 345 (14.8) 0.918

Hemodialysis, n (%) 46 (17.3) 291 (12.5) 0.023

Immunosuppression, n (%) 84 (31.6) 819 (35.3) 0.259

TPN, n (%) 51 (19.2) 125 (5.4) <0.001

Surgery, n (%)

Abdominal 54 (20.3) 209 (13.3) 0.001

Any surgery 99 (37.2) 602 (25.8) <0.001

CVC, n (%) 213 (80.1) 1320 (56.6) <0.001

Prior hospitalization, n (%) 142 (58.9) 1190 (51.1) 0.168

Prior antibiotics, n (%) 197 (74.1) 1215 (52.1) <0.001

Days hospitalization prior to candidemia, median (IQR)

6 (0-17) 1 (0-10) <0.001

APACHE II score (mean ± SD) 17.1 ± 6.5 16.3 ± 6.2 0.049

Septic shock, n (%) 129 (48.5) 990 (42.5) 0.060

Mechanical ventilation, n (%) 94 (35.5) 584 (25.1) <0.001

Mortality, n (%) 125 (47) 662 (28.4) <0.01

Candida sp., n (%) Untreated (n = 1391)

Candida albicans 113 (42.5)

Candida glabrata 75 (28.2)

Candida parapsilosis 43 (16.2)

Candida tropicalis 20 (7.5)

Candida krusei 11 (4.1)

Candida lusitaniae 3 (1.1)

Candida dubliniensis 3 (1.1)

Candida guillermondii 2 (0.8)

Results

Variable

Univariate analysis Multivariate analysis

OR (95% CI) p-value Adjusted OR (95% CI) p-value

Duration of hospitalization (per day) 1.02 (1.0-1.0) <0.001

Mechanical ventilation 1.6 (1.2-2.1) <0.001 1.8 (1.2-2.3) 0.002

TPN 4.2 (3.0-6.0) <0.001 2.5 (1.7-3.8) <0.001

CVC 3.7 (2.6-5.2) <0.001 2.2 (1.5-3.3) <0.001

Septic shock 1.3 (1.0-1.6) 0.061

Prior antibiotics 2.6 (2.0-3.5) <0.001 2.4 (1.7-3.4) <0.001

APACHE II score (per point increase)

1.02 (1.0-1.0) 0.049

Diabetes mellitus 0.98 (0.7-1.3) 0.907

Source of infection

Intra-abdominal 1.4 (1.0-2.0) 0.81

CVC 1.6 (1.2-2.3) 0.005

Lung 0.05 (0.02-0.1) <0.001 0.04 (0.01-0.1) <0.001

Source of admission

Home 0.4 (0.3-0.6) <0.001

Nursing home 1.4 (1.0-2.1) 0.082 2.3 (1.4-3.6) 0.001

Outside hospital 2.1 (1.6-2.8) <0.001 1.8 (1.3-2.6) <0.001

Abdominal surgery 1.7 (1.2-2.3) 0.002

Any surgery 1.7 (1.3-2.2) <0.001

Probability prediction equation (using 1 if factor is present and 0 if factor absent): o (0.93 x TPN) + (0.88 x prior antibiotics within 30 days) + (0.61 x transfer from outside hospital) + (0.81 x admission from

nursing home) + (0.52 x mechanical ventilation) + (0.8 x presence of CVC for at least 48 hours) + (-3.22 x lung as presumed infection source) – 3.61

Area under the receiver operating characteristic curve (AUROC) for prediction equation was 0.798 (95% CI 0.77-0.82), indicating

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that the prediction equation will assign a randomly chosen positive patient a higher prediction score than a randomly chosen negative patient 80% of the time

Integer score, where score >3 indicates high risk of candidemia: o Prior antibiotics within 30 days = 2 points o CVC at least 48 hours = 2 points o Admitted from nursing home = 2 points o TPN = 2 points o Transferred from outside hospital = 1 point o Mechanical ventilation = 1 point o Lung as presumed source of infection = -6 points

AUROC for integer score with value of 3 to predict candidemia was 0.72 (0.7-0.74)

Specificity of score of 3 or higher was 87.6% (83-91.3%) and sensitivity was 55.9% (53.9-57.9%)

PPV of score of 3 or higher was 18.5% (16.4-20.7%) and NPV was 97.5% (96.5-98.3%) o Using cutoff score of 2 provided a negative predictive value of 98.8%

Authors’ Conclusions

The developed and validated prediction rule outperformed previous prediction rules

Locally derived prediction models may be superior by accounting for local case mix and risk factor distribution

Reviewer’s Critique

Strengths Limitations

Large sample size

Specifically evaluated patients with sepsis or septic shock

Prediction equation had highest AUROC of all available prediction scores (other scores ranged between 0.595 and 0.762)

Retrospective study

Score has not been externally validated

Although prediction equation had best AUROC, simplified version had lower AUROC than other rules

Unable to include dose of corticosteroids in analysis

Only evaluated risk of candidemia and not invasive candidiasis

Conclusion: Use of a complicated risk prediction equation was superior to all other models for prediction of candidemia in sepsis and septic shock, however the simplified version, which would be easier to implement in practice, was no better than other models.

3. Take-Home Points

a. First study to develop risk score specifically in patients with sepsis or septic shock

b. Useful for assessing risk to decide whether antifungal treatment is warranted

c. Risk tool still has limitations, including difficulty implementing into practice, low PPV, and limitation to

candidemia only


Which patients should be treated empirically with an echinocandin versus fluconazole?

Table 9. Ostrosky-Zeichner L, Harrington R, Azie N, et al. A risk score for fluconazole failure among patients with candidemia. Antimicrob Agents Chemother. 2017;64:e02091-16.40

Design and Methods

Retrospective, cohort study to develop a risk score for fluconazole failure in patients with candidemia


Aged 18 years or older

At least one positive blood culture for Candida spp.

Initiation of IV fluconazole treatment during hospital stay and no more than 5 days before positive Candida spp. blood culture

Second hospitalization in study period (4/01/2004 to 03/31/2013)

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Factors Evaluated Patient demographics (e.g. age, sex, race)

Index hospitalization characteristics

Candida sp. isolated

Time from admission until start of fluconazole treatment

Fluconazole use prior to positive blood culture

Underlying diagnosis

Procedures received (e.g. CVC placement, drain placement, ileostomy)

Treatments (e.g. parenteral or enteral nutrition, corticosteroids, other antifungals)

Endpoints Failure of fluconazole, defined as patients who met any of the following criteria o Switched to or added another antifungal after fluconazole initiation o Had a subsequent positive blood culture for Candida infection during index hospitalization and at

least 10 days after fluconazole initiation o Died during period from index date to end of index hospitalization


n = 987

Variable Fluconazole failure

(n = 488) No fluconazole failure

(n = 499) p-value

Age in yrs, mean ± SD 60.95 ± 16.55 61.24 ± 17.68 0.7

Sex, male, n (%) 252 (51.6) 255 (51.1) 0.866

Days from admission to fluconazole initiation, mean ± SD

22.88 ± 66.52 12.76 ± 15.2 <0.001

Fluconazole use prior to positive blood culture, n (%)

429 (87.9) 418 (83.8) 0.062

Charlson comorbidity index, mean ± SD 1.66 ± 2.42 1.51 ± 2.24 0.598

Diagnoses, n (%)

Hematological malignancy 17 (3.5) 7 (1.4) 0.034

Renal failure (including hemodialysis) 120 (24.6) 134 (26.9) 0.416

Hepatitis 33 (6.8) 22 (4.4) 0.107

Gastroenteritis 36 (7.4) 33 (6.6) 0.638

Abscess 34 (7.0) 45 (9.0) 0.235

Venous thromboembolism 22 (4.5) 30 (6.0) 0.29

Diabetes 75 (15.4) 77 (15.4) 0.978

Severe sepsis/bacteremia 75 (15.0) 84 (16.8) 0.421

Procedures, n (%)

Use, replacement, or removal of central line

192 (39.3) 199 (39.9) 0.863

Use of nonoperative intubation or irrigation

103 (21.1) 63 (12.6) <0.001

Ileostomy 13 (2.7) 8 (1.6) 0.248

Mechanical ventilation 168 (34.4) 121 (24.2) <0.001

Treatments, n (%)

Parenteral nutrition 81 (16.6) 96 (19.2) 0.280

Enteral nutrition 44 (9.0) 30 (6.0) 0.073

Corticosteroids 30 (6.1) 28 (5.6) 0.72

Other antifungals* 108 (22.1) 81 (16.2) 0.019

*other antifungals = amphotericin B, flucytosine, itraconazole, voriconazole, posaconazole, or an echinocandin

Candida sp. isolated, n (%) Fluconazole failure

(n = 488) No fluconazole failure

(n = 499) p-value

Candida albicans 256 (52.5) 291 (58.3) 0.064

Candida glabrata 134 (27.5) 84 (16.8) <0.001

Candida krusei 6 (1.2) 2 (0.4) 0.173

Candida parapsilosis 48 (9.8) 62 (12.4) 0.196

Other Candida spp. 47 (9.6) 65 (13.0) 0.093

14

Results

Risk factor Coefficient Standard Error Odds Ratio

Days to initiation of fluconazole after admission

0.02 0.01 1.02

Candida sp.

Candida glabrata 0.68 0.20 1.98

Candida krusei 2.1 1.12 8.20

Hematologic malignancy 1.18 0.60 3.25

Venous thromboembolism -0.67 0.41 0.51

Nonoperative intubation or irrigation 0.43 0.29 1.54

Mechanical ventilation 0.12 0.24 1.13

Enteral nutrition 0.44 0.32 1.56

Other antifungal use 0.34 0.21 1.4

AUROC was 0.65, meaning model will give a randomly selected positive case a higher score than a randomly selected negative case 65% of the time

Risk score cutoff # correctly predicted*

Sensitivity Specificity PPV NPV

0.1 163 100 0 49 0

0.2 162 99 2 50 75

0.3 158 97 17 53 85

0.4 127 78 42 57 66

0.5 91 56 68 63 61

0.6 53 33 84 66 56

0.7 25 15 95 74 63

0.8 10 6 98 77 52

0.9 5 3 100 100 51

Authors recommend a cutoff of 0.5 to balance sensitivity and specificity


This study identified clinical factors that may predict fluconazole failure in hospitalized patients with candidemia



First study to provide scoring system to predict fluconazole failure

Included many different variables to assess risk of failure

Retrospective, claims-based study

AUROC is less than generally accepted cutoff for a “good” model (0.7 or higher)

Recommended cutoff of 0.5 only provided 56% sensitivity and 68% specificity

Conclusion: This prediction model for risk of fluconazole failure may be used in combination with other tools to assess whether patients at high risk of candidiasis may benefit from initial echinocandin therapy over fluconazole therapy.

1. Take-Home Points

a. Although this tool may help predict patients who need echinocandin therapy rather than fluconazole therapy,

the tool did not perform well enough to recommend in clinical practice

b. Has not been validated as a tool to make initial treatment decisions

c. Risk score does not have the best accuracy, with an AUROC of 0.65

15


What is the clinical benefit of early antifungal therapy in critically ill patients with sepsis?

Table 10. Timsit JF, Azoulay E, Schwebel C, et al. Empirical micafungin treatment and survival without invasive fungal infection in adults with ICU-acquired sepsis, Candida colonization, and multiple organ failure: the EMPIRICUS randomized controlled trial. JAMA. 2016;316:1555-64.41

Design and Methods

Multicenter, double-blind, placebo-controlled trial to evaluate whether micafungin increases 28-day invasive fungal infection-free survival in patients with ICU-acquired sepsis, Candida spp. colonization at multiple sites, and multiple organ failure


Mechanically ventilated for at least 5 days

At least 1 colonization site (other than rectal swab or stool) positive for Candida sp.

At least 1 additional organ dysfunction (SOFA score ≥ 3)

Previous treatment for > 4 days using broad-spectrum antibacterial agents within last 7 days

Arterial or CVC

New finding of ICU-acquired sepsis of unknown origin (based on SIRS criteria)

Neutropenia (< 500 WBCs/mm2)

Previous organ or stem cell transplant

Ongoing systemic immunosuppression agent therapy other than 2 mg/kg/day of prednisolone or equivalent

Recent chemotherapy (within past six months)

Proven invasive infection at time of randomization

Antifungal treatment with an echinocandin agent for more than one day or with any other antifungal agent for more than 72 hours during the week prior to inclusion

Intervention Micafungin 100 mg IV daily x 14 days (n = 128) vs placebo (n = 123)

Endpoints 28-day survival free of proven invasive fungal infection o Also assessed in subgroups: medical vs surgical, low vs high SOFA score, low vs high (1-3)-β-D-

glucan level, low vs high colonization index, Candida score < 3 vs ≥ 3

New proven invasive fungal infections during follow-up

Survival at days 28 and 90

Antifungal-free survival at day 28

Incidence of ventilator-associated bacterial pneumonia

Evolution throughout 28-day study period of SOFA score and (1-3)-β-D-glucan


N = 251

Micafungin (n = 128) Placebo (n = 123)

Age in years, median (IQR) 65 (56-74) 64 (52-74)

Men, n (%) 81 (66) 82 (64)

Weight in kg, median (IQR) 84 (72-97) 80 (68-95)

Chronic disease categories, n (%)

Cardiac 30 (24) 34 (27)

Respiratory 20 (16) 33 (26)

Hepatic 11 (9) 14 (11)

Renal 15 (12) 7 (6)

Immunosuppression 4 (3) 8 (6)

Receiving corticosteroids, n (%) 11 (9) 11 (9)

Admission category, n (%)

Medical 92 (75) 94 (73)

Emergency surgery 29 (24) 31 (24)

Scheduled surgery 2 (2) 3 (2)

Main surgical procedures, n (%)

Cardiac 25 (20) 94 (73)

Abdominal 5 (4) 31 (24)

Other surgery or trauma 2 (2) 4 (3)

16

Main reason for ICU admission, n (%)

Acute respiratory failure 48 (39) 54 (41)

Septic shock 37 (31) 48 (37)

Cardiogenic shock 21 (17) 17 (13)

Coma 15 (12) 10 (8)

Acute pancreatitis 7 (6) 7 (6)

Duration of ICU stay prior to inclusion in days, median (IQR)

11 (7-17) 10 (7-15)

Variables assessed at inclusion

SOFA score, median (IQR) 8 (5-12) 8 (6-11)

Candida score, median (IQR) 3 (2.5-4) 3 (2-4)

No. of positive colonization sites, median (IQR)

3 (2-4) 3 (2-4)

Epinephrine or norepinephrine use, n (%) 70 (57) 71 (56)

Dialysis or hemofiltration, n (%) 42 (34) 40 (31)

Parenteral nutrition, n (%) 30 (24) 35 (27)

Results

Micafungin Placebo

Hazard Ratio p-

value 28-day IC-

free survival Total number

28-day IC-free survival

Total number

All patients 87 128 74 123 1.35 (0.87-2.08) 0.18

SOFA score

≤ 8 51 66 52 68 1.11 (0.53-2.33) 0.78

> 8 36 62 22 55 1.69 (0.96-2.94) 0.07

Candida score ≥ 3 64 96 47 85 1.37 (0.83-2.27) 0.21

(1-3)-β-D-glucan, pg/mL

> 80 58 91 47 84 1.41 (0.85-2.33) 0.19

≤ 80 29 37 27 39 0.98 (0.30-2.94) 0.97

Micafungin Placebo

Hazard Ratio p-

value 28-day Survival

Total number 28-day Survival

Total number

All patients 90 128 86 123 1.04 (0.64-1.67) 0.88

SOFA score

≤ 8 53 66 58 68 0.79 (0.32-1.96) 0.62

> 8 37 62 28 55 1.28 (0.71-2.27) 0.42

Candida score ≥ 3 66 96 58 85 0.95 (0.55-1.67) 0.87

(1-3)-β-D-glucan, pg/mL

> 80 61 91 58 84 0.98 (0.55-1.75) 0.96

≤ 80 29 37 28 39 0.85 (0.27-2.63) 0.78

Micafungin (n = 128) Placebo (n = 123)

Absolute Difference (95% CI)

# of invasive fungal infections at follow-up (day 28)

≥ 1 4 (3) 15 (12) 9.1 (2.5 – 16.3)

2 0 2 (2) 1.6 (-1.5 – 5.7)

Invasive fungal infections by species

Candida albicans 3 10 19.4 (-29.7 – 49.4)

Candida glabrata 0 2 11.1 (-38.5 – 32.8

Candida parapsilosis 0 3 16.7 (-33.5 – 39.2)

Candida inconspicua 1 0 25.0 (-2.0 – 69.9)

Trichosporon 0 2 11.1 (-38.5 – 32.8)

Aspergillus fumigatus 0 1 5.6 (-43.7 – 25.8)

17


Among nonneutropenic critically ill patients with ICU-acquired sepsis, Candida species colonization at multiple sites, and multiple organ failure, empirical treatment with micafungin did not increase fungal infection-free survival at day 28



Double-blind, placebo-controlled randomized trial

Excluded transplant and neutropenic patients

Only included patients at highest risk of invasive candidiasis (exposure to broad-spectrum antibiotics, presence of central venous catheter)

Underpowered (expected 18% difference, found 8% difference)

Included invasive candidiasis diagnosed by samples found before initiation of therapy as an occurrence of the primary endpoint

Low percentage of abdominal surgery and acute pancreatitis as these patients are at higher risk of IC

Reviewer’s Conclusions

Underpowered to find an improvement in mortality with use of empiric echinocandin therapy in patients at highest risk of invasive candidiasis

Abbreviations: SAPS = Simplified Acute Physiology Score, SIRS = Systemic Inflammatory Response Syndrome, SOFA = Sequential Organ Failure Score

1. Why didn’t we see a difference?

a. Patients at risk for invasive candidiasis are extremely sick

i. Median SOFA score was 8, correlating with 15-20% mortality42,43

ii. Risk factors for IC are seen in patients with many chronic issues with a higher baseline risk of death

iii. Presence of IC could arguably be considered marker of disease severity in ICU patients

iv. Questions futility of echinocandin intervention in patients at high-risk

b. Micafungin was started late in hospital stay

i. Study only evaluated patients who had received broad-spectrum antibiotics for four or more days

ii. With knowledge that early treatment is associated with better outcomes, delayed micafungin

initiation may have resulted in lower rate of efficacy

c. Higher doses may have been needed to hit pharmacokinetic/pharmacodynamic targets

i. In population pharmacokinetic study of critically ill patients based on data from EMPIRICUS trial,

results showed higher doses may be needed to meet AUC:MIC targets for efficacy44

1. Covariates that significantly influenced clearance (CL), central distribution volume (Vc), and

peripheral distribution volume (Vp) were body weight, serum albumin, and SOFA score

2. In simulations of patients with C. albicans or C. glabrata with MICs > 0.015 mg/L, micafungin

doses of at least 150 mg were needed to achieve high probability of target attainment (PTA)

a. 100 mg dose adequate for isolates with MICs < 0.015 mg/L

3. In simulations of patients with C. parapsilosis, doses between 150 mg and 300 mg were

necessary to reach a PTA of 90% for isolates with MICs = 0.25-0.5 mg/L

a. High PTA never able to be obtained with isolates with MIC > 1 mg/L

b. 100 mg dose only adequate in patients with isolates with MICs ≤ 0.125 mg/L

c. Lower PTAs seen in models of patients with serum albumin < 2.5 g/dL

ii. Micafungin pharmacokinetics in obese, critically ill, and morbidly obese critically ill patients showed

difficulty meeting AUC/MIC targets45

1. 100 mg dose was never able to achieve > 90% fractional target attainment (FTA) for any

Candida spp.

2. 150 mg dose met 90% FTA for C. albicans in patients ≤115 kg, but never achieved > 90% for

other species

3. 200 mg dose meet 90% FTA for C. albicans in all patients and C. glabrata in patients ≤ 115 kg,

but never met goal for C. tropicalis or C. parapsilosis

18

Recommendation

1. Guillamet score should be used to assess the risk of candidemia in patients with septic shock presenting from the

community

a. Full calculation should be used rather than simplified scoring system better accuracy

2. Patients in the ICU for ≥7 days can be assessed with Candida score better accuracy than Guillamet score

3. For patients with either score ≥ 3, prior antifungal history should be assessed

a. Patients with history of fluconazole use should receive empiric echinocandin therapy

i. Should be given at least 150 mg of micafungin or 200 mg if ≥ 115 kg

b. Patients with no history of antifungal therapy AND low SOFA score (< 8) may be initially managed with

fluconazole

4. Blood cultures should be drawn before receipt of antifungal therapy, and T2Candida® and/or Biofire PCR testing

should be utilized if possible to enable targeted therapy

5. Empiric therapy can be discontinued in the following situations: a. Negative blood cultures after 5 days b. No clinical improvement after 4-5 days without proven IC c. Back-to-back negative (1-3)-β-D-glucan on separate days

6. If blood cultures come back positive, therapy can be de-escalated based on organism and susceptibilities

Conclusion

1. Although early treatment of IC is extremely important, diagnosis remains immensely difficult

2. Patients presenting with sepsis or septic shock with extensive exposure to the healthcare system should be assessed

for risk of IC

3. Care should be taken to avoid overuse of echinocandins in light of emerging resistance

4. Although IC is associated with high mortality, patients who are diagnosed are generally chronically ill, and the disease

may be a marker of disease severity

19

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