Choosing optimal antifungal agents to prevent fungal infections in non-neutropenic critically ill

43 Pages·2017·3.09 MB·English

AAC Accepted Manuscript Posted Online 9 October 2017
Antimicrob. Agents Chemother. doi:10.1128/AAC.00620-17
Copyright © 2017 American Society for Microbiology. All Rights Reserved.
1 Choosing optimal antifungal agents to prevent fungal infections in
2 non-neutropenic critically ill patients: trial sequential analysis, network
3 meta-analysis, and pharmacoeconomic analysis
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5 Yan Wang1, Jiao Xie1, Yuanming Xing2, Lu Chen1, Ying Li1, Ti Meng1, Weihua Dong1, D
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6 Xue Wang3, Yalin Dong1* nlo
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8 1Department of Pharmacy, The First Affiliated Hospital of Xi’an Jiaotong University, fro
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9 Xi’an 710061, China. h
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10 2Hou Zonglian medical class of 2014, Xi’an Jiaotong University, Xi’an 710061, ://
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11 China. .a
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12 3Central Intensive Care Unit, The First Affiliated Hospital of Xi’an Jiaotong .
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13 University, Xi’an 710061, China. /
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15 *Corresponding author: Yalin Dong, Ph.D. em
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16 Department of Pharmacy, The First Affiliated Hospital of Xi’an Jiaotong University, r

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17 Xi’an 710061, China. ,
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18 Phone: [phone]; Fax: [phone]

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19 Email: [email protected]; [email protected]
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21 Running Title: Antifungal agents used in critically ill patients
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22 Abstract
23 The use of antifungal interventions in critically ill patients prior to invasive fungal
24 infection (IFI) being microbiologically confirmed as well as the preferred drug are
25 still controversial. A systematic literature search was performed to identify
26 randomized controlled trials (RCTs) that have compared untargeted antifungal D
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27 treatments applied to non-neutropenic critically ill patients. The primary outcomes lo
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28 were all-cause mortality and proven IFI rates. A random-effects model was used with e
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29 trial sequential analyses (TSA), a network meta-analysis (NMA) was conducted to m

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30 obtain indirect evidence, and a cost-effectiveness analysis using a decision-analytic tp
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31 model was completed from the patient perspective over a lifetime horizon. In total, 19 a
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32 RCTs involving 2556 patients (7 interventions) were included. Untargeted antifungal m
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33 treatment did not significantly decrease all-cause mortality (odds ratio [OR]=0.89, 95% g/

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34 confidence interval [CI]=0.70–1.14), but it did reduce the incidence of proven IFI N
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35 (OR=0.45, 95%CI=0.29–0.71) relative to placebo/no intervention. The TSA showed m
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36 that there was sufficient evidence supporting these findings. In the NMA, the only r
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37 significant difference found for both primary outcomes was between fluconazole and 2
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38 placebo/no intervention in preventing proven IFI (OR=0.35, 95%CI=0.19–0.65). The b
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39 incremental cost-effectiveness ratios per life-years saved for fluconazole, caspofungin, u
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40 and micafungin relative to placebo/no intervention were US$ 889, US$ 9994 and
41 US$ 10351, respectively. Untargeted antifungal treatment significantly reduced
42 proven IFI rates in non-neutropenic critically ill patients but with no mortality benefits
43 relative to placebo/no intervention. Fluconazole remains an only effective for IFI
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44 prevention and well-tolerated antifungals that is significantly cheaper than
45 echinocandins.
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47 Keywords: untargeted treatment; invasive fungal infection; critically ill patients;
48 network meta-analysis; pharmacoeconomic analysis D
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49 Introduction
50 Invasive fungal infection (IFI) is one of the most common health-care-associated
51 infections in patients in intensive care units (ICUs), especially those caused by
52 Candida spp. IFI typically ranks as the third or fourth most common cause of
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53 bloodstream infection, and it is associated with considerable mortality and morbidity w
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54 that poses a serious threat to the patient’s health as well as large societal economic a
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55 losses(1-6). The prompt application of appropriate antifungal treatment for IFI
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56 generally improves the prognosis(5, 7, 8). However, such treatments are frequently
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57 delayed due to the relative insensitivity of blood cultures and the long time for :/
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58 cultures to yield growth, leading to worse outcomes and higher mortality(5, 9, 10). .a
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59 Several guidelines have focused on initiating antifungal therapy for critically ill rg
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60 patients prior to IFI being microbiologically confirmed; these therapies have been
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61 classified into prophylaxis, empirical treatment and pre-emptive treatment e
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62 (diagnosis-driven). Prophylaxis strategies are generally applied to patients who are at er

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63 risk for infection by a given pathogen(s), but have evidence for neither infection nor ,
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64 attributable clinical disease. Empirical treatment is often applied to a clinical disease 8

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65 syndrome that may be caused by a given pathogen(s), but for which there is no gu
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66 immediate microbiological evidence (e.g. for a persistent fever syndrome despite
67 broad-spectrum antibacterial therapy). Pre-emptive treatment is generally applied to
68 patients who may have evidence for infection by a pathogen (often a surrogate marker
69 such as a positive beta-d-glucan test), but no evidence for attributable clinical
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70 disease(10-12). A recent Cochrane analysis referred to these three strategies as
71 “untargeted treatments,” and demonstrated that these treatment cannot reduce the
72 incidence of all-cause mortality but may decrease the risk of developing IFI among
73 non-neutropenic critically ill patients(13).
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74 There is still doubt about whether untargeted antifungal treatment is effective in w
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75 clinical practice. Two recent clinical trials have provided new evidence on a
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76 little-studied agent (i.e., micafungin) with adequate statistical power, which may
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77 enhance the reliability of conclusions(14, 15). Furthermore, although traditional
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78 meta-analyses have estimated the effects of various antifungal agents versus :/
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79 placebo/no intervention, the relative efficacy of the available treatments is uncertain .a
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80 due to the absence of direct comparisons of the antifungal agents(13, 16, 17). The .o
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81 existence of untargeted antifungal agents that are more effective therefore remains o
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82 unclear. Moreover, any antifungal agents administered by clinicians prior to a o
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83 definitive diagnosis of IFI need to be comprehensively considered in terms of their b
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84 timing, risk and efficacy, with affordability also being critical. 0
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85 This study performed three types of analysis: 8

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86 1. A pairwise meta-analysis with trial sequential analysis (TSA) aimed at gu
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87 determining whether the currently available evidence is sufficient and conclusive.
88 2. A network meta-analysis (NMA) that comprehensively compared and ranked
89 antifungal agents according to their effectiveness and safety in non-neutropenic
90 critically ill patients.
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91 3. A pharmacoeconomic analysis to investigate the cost-effectiveness of antifungal
92 agents in this population using clinical efficacy data generated by the NMA,
93 epidemiological data, and local medical data.
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95 Results D
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96 Overall, 10709 titles were identified during the primary search, leaving 60 potentially lo
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97 eligible studies for full-text review after preliminary screening (Figure 1). Ultimately e
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98 only 19 of these RCTs published between 1990 and 2016 were regarded as eligible for m

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99 inclusion in the NMA(14, 15, 18-34). Supplementary Table S1 presented the main tp
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100 characteristics of these RCTs, which involved 2556 participants. The population a
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101 comprised 60% males (1370 of 2287 [evaluable population]) and the mean age was m
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102 58.1 years. These 19 studies covered 7 interventions: placebo/no intervention, g/

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103 fluconazole, caspofungin, micafungin, nystatin, amphotericin B, and anidulafungin; N
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104 and the network of eligible comparisons for primary outcomes are presented in Figure m
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105 2a and Figure 2b. r
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106 In terms of study quality, about half of the trials provided details of randomization 1
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107 procedures (11 RCTs, 58%) and allocation concealment (10 RCTs, 53%). The y
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108 presence of both blinding of outcome assessment and blinding of participants and s
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109 personnel was identified in 12 studies (Supplementary Figure S1 and Figure S2). An
110 intention-to-treat analysis was performed in most of the studies (14 RCTs, 74%) (14,
111 15, 18, 19, 21, 22, 25-28, 31-34).
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113 Untargeted antifungal treatment versus placebo/no intervention
114 The outcome of mortality was not reported for 1 of the 19 RCTs, and so this was not
115 included in the all-cause mortality analysis(26). Untargeted antifungal treatment did
116 not significant reduce the odds for all-cause mortality (odds ratio [OR]=0.89, 95%
117 confidence interval [CI]=0.70–1.14, I2=25.9%, Cochrane Q P=0.157) (Table 1 and D
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118 Figure 3). The TSA showed that the cumulative Z-curve crossed the futility boundary lo
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119 and entered the futility area, which established sufficient and conclusive evidence and e
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120 hence indicated that further trials were not required. The funnel plot showed no m

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121 asymmetry (Supplementary Figure S3a). The quality of evidence for this outcome was tp
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122 moderate (Supplementary Figure S4). a
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123 Outcomes for the incidence of proven IFI for 6 interventions of interest were included .o
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124 for 18 of the 19 included RCTs; the exception was 1 RCT involving anidulafungin(33). o
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125 The result indicated that a lower incidence of proven IFI was associated with o
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126 untargeted antifungal treatment (OR=0.45, 95%CI=0.29–0.71, I2=27.3%, Cochrane Q b
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127 P=0.162) (Table 1 and Figure 4). The TSA showed that the cumulative Z-curve 0
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128 crossed both the conventional boundary for benefit and trial sequential monitoring 1
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129 boundary for benefit and entered the area of benefit. This established that the evidence y
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130 was sufficient and conclusive, and hence indicated that further trials were not required. s
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131 The funnel plot was not symmetrical, and Egger’s test supported publication bias
132 (P=0.094) (Supplementary Figure S3b). The quality of evidence for this outcome was
133 low (Supplementary Figure S4).
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134 Regarding secondary outcomes, untargeted antifungal treatment was found to only
135 reduce the incidence of fungal colonization (OR=0.51, 95%CI=0.36–0.72). In terms
136 of proven or suspected IFI, suspected IFI, mortality attributable to IFI, drug
137 discontinuation due to adverse events, and proven IFI (fluconazole-resistant species),
138 there are no significant differences between untargeted antifungal treatment and D
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139 placebo/no intervention. The detailed results and GRADE quality are presented in lo
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140 Table 1 and Supplementary Figure S4, respectively. e
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141 We performed subgroup analysis investigating all-cause mortality and proven IFI. In
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142 the subgroup analysis for drug class, we evaluated the effect of fluconazole and :/
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143 echinocandins as untargeted treatment. Concerning the use of fluconazole, there was .a
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144 no difference between the two groups for all-cause mortality (OR=0.81, .o
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145 95%CI=0.51–1.28), whereas a significant difference existed for the risk of proven IFI o
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146 (OR=0.33, 95%CI=0.19–0.56). The effect of echinocandins was not statistically o
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147 significantly different between the two groups for both mortality (OR=1.10, b
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148 95%CI=0.80–1.51) and proven IFI (OR=0.42, 95%CI=0.13–1.39) (Supplementary 0
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149 Figure S5). 1
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150 In the subgroup analysis based on type of treatment strategies, the effect of gu
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151 prophylaxis was not statistically significantly different between the two groups for
152 mortality (OR=0.87, 95%CI=0.68–1.11), but a statistically significant difference was
153 noticed for proven IFI (OR=0.43, 95%CI=0.25–0.75). Concerning the use of
154 antifungal empirc/pre-emptive treatment, the mortality risk and the risk of developing
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155 proven IFI were not statistically significantly different between groups (OR=0.96,
156 95%CI=0.52–1.77 and OR=0.47, 95%CI=0.19–1.19, respectively) (Supplementary
157 Figure S5).
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159 Network meta-analysis D
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160 For both of the primary outcomes, the geometry of the network of interventions was lo
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161 open without closed loops, which resulted in low diversity (Figure 2). e
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162 There were no significant differences in the all-cause mortality between any two
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163 interventions (Figure 5a). The probability of being the most effective (Prbest) and the ://
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164 surface under the cumulative ranking (SUCRA) for all-cause mortality for the seven .a
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165 interventions are listed in Table 2. In terms of the incidence of proven IFI, the only .o
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166 significant difference was between fluconazole and placebo/no intervention (OR=0.35, o
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167 95%CI=0.19–0.65). There were no significant effect of caspofungin and micafungin o
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168 for reducing the incidence of IFI (OR=0.20, 95%CI=0.02–2.15 and OR=0.57, b
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169 95%CI=0.22–1.44, respectively). We found no substantial difference when comparing 0
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170 caspofungin and micafungin with fluconazole (Figure 5b). The ranking probabilities 1
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171 were most favorable for caspofungin (Prbest=65.2 and SUCRA=0.82), followed by y
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172 fluconazole, micafungin, nystatin, placebo/no intervention, and amphotericin B (Table s
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173 2). The values of the common heterogeneity variables for all comparisons in this
174 NMA for all-cause mortality and for the incidence of proven IFI were τ=0.18 and
175 τ=0.46, respectively (both values indicate moderate heterogeneity).
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176 The potential effect of several influential variables on the primary outcomes were
177 examined in meta-regression analyses. After adjusting for the mean age, Prbest and
178 SUCRA for micafungin changed from 2.4% and 0.49 to 61.8% and 0.80, respectively;
179 this suggests that age can influence estimates of all-cause mortality. Similarly, after
180 adjusting for the sex ratio, Prbest and SUCRA for micafungin changed from 5.7% and D
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181 0.55 to 52.8% and 0.88, respectively, might indicating that the effect of micafungin is lo
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182 more evident in male for preventing proven IFI. For the percentage of postsurgical e
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183 participants, the difference between micafungin and placebo/no intervention was m

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184 approximately significant (P=0.051) and the SUCRA for micafungin became highest tp
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185 among the six interventions, might also indicating the better effect of micafungin exist a
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186 in postsurgical participants for preventing proven IFI. The findings for other m
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187 comparisons did not differ markedly from those obtained in the primary analysis g/

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188 (Table 2). Similarly, the main results did not substantially differ between the three N
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189 preplanned sensitivity analyses (Supplementary Table S2). m
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190 r
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191 Cost-effectiveness analysis 2
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192 Base-case analysis b
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193 Fluconazole, caspofungin and micafungin were included in the economic analysis u
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194 comparing with placebo/no intervention. The total costs and outcomes for the four
195 treatment strategies are summarized in Table 3. Placebo/no intervention was used as
196 the baseline when calculating the incremental cost-effectiveness ratios (ICERs) of
197 other strategies. The ICERs per life-years (LY) saved for fluconazole, caspofungin,
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