# Procalcitonin algorithm to guide initial antibiotic therapy in acute exacerbations of COPD admitted to the ICU: a randomized multicenter study

Cédric Daubin, Xavier Valette, Fabrice Thiolliere, Jean-Paul Mira, Pascal Hazera, Djillali Annane, Vincent Labbé, Bernard Floccard, François Fournel, Nicolas Terzi, et al.

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## To cite this version:

Cédric Daubin, Xavier Valette, Fabrice Thiolliere, Jean-Paul Mira, Pascal Hazera, et al. Procalcitonin algorithm to guide initial antibiotic therapy in acute exacerbations of COPD admitted to the ICU: a randomized multicenter study. Intensive Care Medicine, 2018, 44 (4), pp.428-437. 10.1007/s00134-018-5141-9. hal-02155549

HAL Id: hal-02155549

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# Procalcitonin algorithm to guide initial antibiotic therapy in acute exacerbations of COPD admitted to the ICU: a randomized multicenter study

Cédric Daubin¹*, Xavier Valette¹, Fabrice Thiollière², Jean-Paul Mira³, Pascal Hazera⁴, Djillali Annane⁵,⁶, Vincent Labbe⁷, Bernard Floccard⁸, François Fournel⁹, Nicolas Terzi¹⁰,¹¹, Damien Du Cheyron¹ and Jean-Jacques Parienti⁹,¹² for the BPCTrea Study Group

© 2018 The Author(s)

## Abstract

**Purpose:** To compare the efficacy of an antibiotic protocol guided by serum procalcitonin (PCT) with that of standard antibiotic therapy in severe acute exacerbations of COPD (AECOPDs) admitted to the intensive care unit (ICU).

**Methods:** We conducted a multicenter, randomized trial in France. Patients experiencing severe AECOPDs were assigned to groups whose antibiotic therapy was guided by (1) a 5-day PCT algorithm with predefined cutoff values for the initiation or stoppage of antibiotics (PCT group) or (2) standard guidelines (control group). The primary endpoint was 3-month mortality. The predefined noninferiority margin was 12%.

**Results:** A total of 302 patients were randomized into the PCT (n = 151) and control (n = 151) groups. Thirty patients (20%) in the PCT group and 21 patients (14%) in the control group died within 3 months of admission (adjusted difference, 6.6%; 90% CI –0.3 to 13.5%). Among patients without antibiotic therapy at baseline (n = 119), the use of PCT significantly increased 3-month mortality [19/61 (31%) vs. 7/58 (12%), p = 0.015]. The in-ICU and in-hospital antibiotic exposure durations, were similar between the PCT and control group (5.2 ± 6.5 days in the PCT group vs. 5.4 ± 4.4 days in the control group, p = 0.85 and 7.9 ± 8 days in the PCT group vs. 7.7 ± 5.7 days in the control group, p = 0.75, respectively).

**Conclusion:** The PCT group failed to demonstrate non-inferiority with respect to 3-month mortality and failed to reduce in-ICU and in-hospital antibiotic exposure in AECOPDs admitted to the ICU.

**Keywords:** Chronic obstructive pulmonary disease, Procalcitonin, Antibiotic stewardship, Respiratory tract infection, Community-acquired pneumonia, Viral infection

<footnote>*Correspondence: daubin-c@chu-caen.fr
¹Department of Medical Intensive Care, CHU de Caen, 14000 Caen, France
Full author information is available at the end of the article
The members of the BPCTrea Study Group are listed in the Acknowledgements and in the electronic supplementary material.</footnote>
<figure><img src="image_3.png" /></figure>

# Procalcitonin algorithm to guide initial antibiotic therapy in acute exacerbations of COPD admitted to the ICU: a randomized multicenter study

Cédric Daubin¹*, Xavier Valette¹, Fabrice Thiollière², Jean-Paul Mira³, Pascal Hazera⁴, Djillali Annane⁵,⁶, Vincent Labbe⁷, Bernard Floccard⁸, François Fournel⁹, Nicolas Terzi¹⁰,¹¹, Damien Du Cheyron¹ and Jean-Jacques Parienti⁹,¹² for the BPCTrea Study Group

© 2018 The Author(s)

## Abstract

**Purpose:** To compare the efficacy of an antibiotic protocol guided by serum procalcitonin (PCT) with that of standard antibiotic therapy in severe acute exacerbations of COPD (AECOPDs) admitted to the intensive care unit (ICU).

**Methods:** We conducted a multicenter, randomized trial in France. Patients experiencing severe AECOPDs were assigned to groups whose antibiotic therapy was guided by (1) a 5-day PCT algorithm with predefined cutoff values for the initiation or stoppage of antibiotics (PCT group) or (2) standard guidelines (control group). The primary endpoint was 3-month mortality. The predefined noninferiority margin was 12%.

**Results:** A total of 302 patients were randomized into the PCT (n = 151) and control (n = 151) groups. Thirty patients (20%) in the PCT group and 21 patients (14%) in the control group died within 3 months of admission (adjusted difference, 6.6%; 90% CI –0.3 to 13.5%). Among patients without antibiotic therapy at baseline (n = 119), the use of PCT significantly increased 3-month mortality [19/61 (31%) vs. 7/58 (12%), p = 0.015]. The in-ICU and in-hospital antibiotic exposure durations, were similar between the PCT and control group (5.2 ± 6.5 days in the PCT group vs. 5.4 ± 4.4 days in the control group, p = 0.85 and 7.9 ± 8 days in the PCT group vs. 7.7 ± 5.7 days in the control group, p = 0.75, respectively).

**Conclusion:** The PCT group failed to demonstrate non-inferiority with respect to 3-month mortality and failed to reduce in-ICU and in-hospital antibiotic exposure in AECOPDs admitted to the ICU.

**Keywords:** Chronic obstructive pulmonary disease, Procalcitonin, Antibiotic stewardship, Respiratory tract infection, Community-acquired pneumonia, Viral infection

<footnote>*Correspondence: daubin-c@chu-caen.fr
¹Department of Medical Intensive Care, CHU de Caen, 14000 Caen, France
Full author information is available at the end of the article
The members of the BPCTrea Study Group are listed in the Acknowledgements and in the electronic supplementary material.</footnote>
**Introduction**

Severe acute exacerbations of chronic obstructive pulmonary disease (AECOPDs) are a leading cause of admission to medical intensive care units (ICUs). Prompt initiation of antibiotics is recommended in this setting despite the fact that bacteria are found to be the cause of disease in only approximatively 50% of cases [1]. COPD exacerbations can be triggered by other factors, such as viruses, allergens and common pollutants [http://www.goldcopd.org]. However, in clinical practice, the signs and symptoms of bacterial and non-bacterial AECOPDs overlap [2, 3]. Therefore, identifying the patients with severe AECOPDs who are most likely to benefit from antibiotics remains a challenge for physicians focused on reducing the frequency and duration of antibiotic treatment to prevent the emergence of multidrug-resistant bacteria in the ICU. Procalcitonin (PCT) is considered useful for determining the likelihood that patients will develop bacterial infections in emergency settings. PCT-based strategies have been shown to substantially and safely reduce antibiotic use in patients without severe lower respiratory tract infections [4, 5], community-acquired pneumonia [6] or AECOPDs [7]. However, data on the efficacy and safety of PCT-based strategies in critically ill patients are scarce [8–11]. Previous studies regarding this issue showed that PCT-guided strategies reduced antibiotic exposure without causing adverse outcomes in heterogeneous groups of patients with suspected severe bacterial infections.

We hypothesized that the use of PCT reduces antibiotic exposure while not affecting or even lowering mortality. We compared 3-month mortality and in-ICU and in-hospital antibiotic use between groups of patients with severe AECOPDs who were admitted to the ICU whose antibiotic therapy was guided by a serum PCT protocol or current guidelines. The preliminary results of this study were presented at the Congrès REANIMATION 2017 (Submission reference 000533), Paris, France, January 2017.

**Methods**

**Patients**

We conducted a prospective, multicenter, parallel-group, randomized controlled trial in the ICUs of 11 hospitals, including 7 tertiary care hospitals, in France between October 2010 and March 2016. All consecutive adult patients experiencing severe AECOPDs with suspected lower respiratory tract infections with or without pneumonia who were admitted to the ICU were eligible for the study and were assigned 1:1 to groups whose antibiotic therapy was guided by (1) a PCT algorithm with predefined cutoff values for the initiation or stoppage of

**Take-home message**

The reduction of antibiotic use remains a major concern in ICU and procalcitonin is a promising biomarker in this field. This prospective randomized controlled trial of 302 severe acute exacerbation of COPD with or without pneumonia admitted in ICU failed to demonstrate the ability of a PCT-guided strategy to safely reduce antibiotic exposure, in particular among patients without antibiotics at inclusion. Prompt initiation of antibiotherapy in this population improves 3-month survival regardless of the level of PCT.

antibiotics (PCT group) or (2) standard guidelines (control group). The time interval between hospital admission and inclusion in the study was required to be less than 48 h.

This academic trial was registered at [ClinicalTrials.gov](http://ClinicalTrials.gov). The following patients were excluded from the study: those under 18 years, with known pregnancies, with clinical evidence of infection other than a lower respiratory tract infection, with severe acute asthma, who were moribund or suffering from a disease with an estimated survival time of less than 2 months, who were severely immunosuppressed (i.e., patients with HIV infection, with neutropenia, recipients of stem cell transplants, receiving immunosuppressive treatments, and receiving corticosteroid treatment at a dose greater than 0.5 mg/kg/day for more than 10 days), with nosocomial infections, refused to participate in the study, included in another biomedical research protocol that was in progress or lasted less than 30 days, and those with a known PCT level at the time of their ICU admission.

The study protocol was approved by the local research ethic committee (Comité de Protection des Personnes Nord Ouest III) for all participating centers, and written informed consent was obtained from the patients or their surrogates upon their enrolment in the study. An independent data and safety monitoring board reviewed the trial's progress and adverse event rates according to treatment assignments.

**Randomization**

Patients were randomly assigned (in a 1:1 ratio) to groups whose antibiotic therapy was guided by a PCT protocol (PCT group) or standard guidelines (control group). The randomization was stratified on the center and the presence or absence of pneumonia. Randomization was performed with an independent, centralized 24-h, web-based system (eol®Medsharing Système de randomisation: IWRS/IVRS essaionline.com) using permuted-block randomization. The block sizes varied.

**Procedures**

Circulating PCT levels were sequentially assessed at inclusion (PCT-H0), at 6 h after inclusion (PCT-H6), and
## Introduction

Severe acute exacerbations of chronic obstructive pulmonary disease (AECOPDs) are a leading cause of admission to medical intensive care units (ICUs). Prompt initiation of antibiotics is recommended in this setting despite the fact that bacteria are found to be the cause of disease in only approximatively 50% of cases [1]. COPD exacerbations can be triggered by other factors, such as viruses, allergens and common pollutants [http://www.goldcopd.org]. However, in clinical practice, the signs and symptoms of bacterial and non-bacterial AECOPDs overlap [2, 3]. Therefore, identifying the patients with severe AECOPDs who are most likely to benefit from antibiotics remains a challenge for physicians focused on reducing the frequency and duration of antibiotic treatment to prevent the emergence of multidrug-resistant bacteria in the ICU. Procalcitonin (PCT) is considered useful for determining the likelihood that patients will develop bacterial infections in emergency settings. PCT-based strategies have been shown to substantially and safely reduce antibiotic use in patients without severe lower respiratory tract infections [4, 5], community-acquired pneumonia [6] or AECOPDs [7]. However, data on the efficacy and safety of PCT-based strategies in critically ill patients are scarce [8–11]. Previous studies regarding this issue showed that PCT-guided strategies reduced antibiotic exposure without causing adverse outcomes in heterogeneous groups of patients with suspected severe bacterial infections.

We hypothesized that the use of PCT reduces antibiotic exposure while not affecting or even lowering mortality. We compared 3-month mortality and in-ICU and in-hospital antibiotic use between groups of patients with severe AECOPDs who were admitted to the ICU whose antibiotic therapy was guided by a serum PCT protocol or current guidelines. The preliminary results of this study were presented at the Congrès REANIMATION 2017 (Submission reference 000533), Paris, France, January 2017.

## Methods

### Patients

We conducted a prospective, multicenter, parallel-group, randomized controlled trial in the ICUs of 11 hospitals, including 7 tertiary care hospitals, in France between October 2010 and March 2016. All consecutive adult patients experiencing severe AECOPDs with suspected lower respiratory tract infections with or without pneumonia who were admitted to the ICU were eligible for the study and were assigned 1:1 to groups whose antibiotic therapy was guided by (1) a PCT algorithm with predefined cutoff values for the initiation or stoppage of

## Take-home message

The reduction of antibiotic use remains a major concern in ICU and procalcitonin is a promising biomarker in this field. This prospective randomized controlled trial of 302 severe acute exacerbation of COPD with or without pneumonia admitted in ICU failed to demonstrate the ability of a PCT-guided strategy to safely reduce antibiotic exposure, in particular among patients without antibiotics at inclusion. Prompt initiation of antibiotherapy in this population improves 3-month survival regardless of the level of PCT.

antibiotics (PCT group) or (2) standard guidelines (control group). The time interval between hospital admission and inclusion in the study was required to be less than 48 h.

This academic trial was registered at ClinicalTrials.gov, NCT02521636. The following patients were excluded from the study: those under 18 years, with known pregnancies, with clinical evidence of infection other than a lower respiratory tract infection, with severe acute asthma, who were moribund or suffering from a disease with an estimated survival time of less than 2 months, who were severely immunosuppressed (i.e., patients with HIV infection, with neutropenia, recipients of stem cell transplants, receiving immunosuppressive treatments, and receiving corticosteroid treatment at a dose greater than 0.5 mg/kg/day for more than 10 days), with nosocomial infections, refused to participate in the study, included in another biomedical research protocol that was in progress or lasted less than 30 days, and those with a known PCT level at the time of their ICU admission.

The study protocol was approved by the local research ethic committee (Comité de Protection des Personnes Nord Ouest III) for all participating centers, and written informed consent was obtained from the patients or their surrogates upon their enrolment in the study. An independent data and safety monitoring board reviewed the trial's progress and adverse event rates according to treatment assignments.

## Randomization

Patients were randomly assigned (in a 1:1 ratio) to groups whose antibiotic therapy was guided by a PCT protocol (PCT group) or standard guidelines (control group). The randomization was stratified on the center and the presence or absence of pneumonia. Randomization was performed with an independent, centralized 24-h, web-based system (eol® Medsharing Système de randomisation: IWRS/IVRS essaionline.com) using permuted-block randomization. The block sizes varied.

## Procedures

Circulating PCT levels were sequentially assessed at inclusion (PCT-H0), at 6 h after inclusion (PCT-H6), and
on days 1, 3 and 5 after inclusion. PCT levels were measured by Elecsys BRAHMS PCT immunoassay (Roche Diagnostics, Mannheim, Germany) using a cobas e411 analyzer, according to the manufacturer's instructions.

In the PCT group, the antibiotic treatment was guided by serum procalcitonin levels. The patients were classified into the following three groups based on the probability of bacterial infection, according to the PCT level, which was measured as described in previous reports [4–7] and our prospective pilot studies in the indicated setting [12, 13]: group 1, PCT < 0.1 µg/L, which indicated that no bacterial infection was present, and the initiation or continuation of antibiotics was strongly discouraged; group 2, PCT > 0.1 and < 0.25 µg/L, which indicated that bacterial infection was possible [12, 13], and the initiation or continuation of antibiotics was encouraged; and group 3, PCT > 0.25 µg/L, which indicated that bacterial infection was present, and the initiation or continuation of antibiotics was strongly encouraged. In addition, the investigators were encouraged to discontinue antibiotics when the PCT concentration was less than 90% of the peak concentration or an absolute concentration less than 0.1 µg/L was noted.

In the control group, PCT concentrations were measured in all blood samples; however, the results were not disclosed to the treating physicians. Thus, the physicians were unaware of the results throughout the entire study period. The data were used only for the final analysis. Both the control and PCT groups could use CRP as a serial biomarker. Antibiotics were started and stopped according to usual care in each center; however, all physicians were encouraged to comply with current guidelines [1, 14].

Except for the prescription of antibiotics during the PCT algorithm period, all other treatments were left to the discretion of the attending physicians throughout the study period in both groups.

All patients were followed until 3 months after randomization.

## Outcomes

The primary endpoint was 3-month mortality from any cause, and the secondary endpoints were the in-ICU and in-hospital antibiotic exposure durations, which were defined as the cumulative numbers of 24-h periods in which the patients received antibiotics, and the number of patients who received antibiotics during the algorithm phase (i.e., the first 5 days after inclusion).

## Data collection and definitions

Detailed information regarding recorded baseline characteristics and definitions (i.e., AECOPD with and without

pneumonia [15, 16] and severity status [17–19]) may be found in the Supplemental Appendix.

## Sample size and statistical analysis

The hypotheses tested were that PCT-based antibiotic therapy was non-inferior to standard therapy with respect to 3-month mortality (primary endpoint) and that PCT-based therapy would significantly decrease in-ICU and in-hospital antibiotic exposure compared with standard therapy (secondary endpoint). The primary outcome was analyzed on an intention-to-treat basis.

The expected overall 3-month mortality rate was 20% (i.e., 30% [12] and 10% [13] for patients with and without pneumonia, respectively; the distributions were equal), the expected non-inferiority margin was 12%, and the expected one-sided alpha risk was 5%. We estimated that 140 patients per group were needed to demonstrate that excess mortality was absent in the PCT group with 80% power. We concluded that 300 patients were needed. Given the size of the study population and based on the results of our previous reports [12, 13], we estimated that the PCT protocol would reduce the number of days of in-hospital antibiotic exposure by more than 24% compared with standard therapy [an average decrease of 1.9 days in the PCT group (24% of 8 days of antibiotic therapy in the non-PCT group), with a standard deviation of ± 5 days, a two-sided alpha risk of 5% and 90% power]. The difference in 3-month mortality (the primary endpoint) between the randomized groups was computed by a generalized linear model of risk difference adjusting for the presence or absence of pneumonia, as appropriate. The upper-limit of the 90% CI, which corresponded to a 5% risk, had to be lower than the 12% non-inferiority margin for a declaration of non-inferiority. The difference in antibiotic therapy exposure (the secondary endpoint) between the randomized groups was computed by the weighted inverse variance mean difference. No interim analysis was planned. We conducted predefined subgroup analysis based on the presence or absence of pneumonia and post hoc subgroup analyses based on the presence or absence of antibiotic therapy at baseline and the delay between admission and randomization, using the same approach as the overall analysis. The presence of interaction between subgroups was tested by the Breslow-day test.

SAS v.9.4 software (SAS Institute, Cary, NC, USA) was used for the data analysis. All tests were 2-sided, and a *p* value < 0.05 was considered statistically significant.

## Results

### Patient characteristics

A total of 302 patients were randomized into the PCT (n=151) and control (n=151) groups. Three ICUs from
on days 1, 3 and 5 after inclusion. PCT levels were measured by Elecsys BRAHMS PCT immunoassay (Roche Diagnostics, Mannheim, Germany) using a cobas e411 analyzer, according to the manufacturer's instructions.

In the PCT group, the antibiotic treatment was guided by serum procalcitonin levels. The patients were classified into the following three groups based on the probability of bacterial infection, according to the PCT level, which was measured as described in previous reports [4–7] and our prospective pilot studies in the indicated setting [12, 13]: group 1, PCT < 0.1 µg/L, which indicated that no bacterial infection was present, and the initiation or continuation of antibiotics was strongly discouraged; group 2, PCT > 0.1 and < 0.25 µg/L, which indicated that bacterial infection was possible [12, 13], and the initiation or continuation of antibiotics was encouraged; and group 3, PCT > 0.25 µg/L, which indicated that bacterial infection was present, and the initiation or continuation of antibiotics was strongly encouraged. In addition, the investigators were encouraged to discontinue antibiotics when the PCT concentration was less than 90% of the peak concentration or an absolute concentration less than 0.1 µg/L was noted.

In the control group, PCT concentrations were measured in all blood samples; however, the results were not disclosed to the treating physicians. Thus, the physicians were unaware of the results throughout the entire study period. The data were used only for the final analysis. Both the control and PCT groups could use CRP as a serial biomarker. Antibiotics were started and stopped according to usual care in each center; however, all physicians were encouraged to comply with current guidelines [1, 14].

Except for the prescription of antibiotics during the PCT algorithm period, all other treatments were left to the discretion of the attending physicians throughout the study period in both groups.

All patients were followed until 3 months after randomization.

## Outcomes

The primary endpoint was 3-month mortality from any cause, and the secondary endpoints were the in-ICU and in-hospital antibiotic exposure durations, which were defined as the cumulative numbers of 24-h periods in which the patients received antibiotics, and the number of patients who received antibiotics during the algorithm phase (i.e., the first 5 days after inclusion).

## Data collection and definitions

Detailed information regarding recorded baseline characteristics and definitions (i.e., AECOPD with and without

pneumonia [15, 16] and severity status [17–19]) may be found in the Supplemental Appendix.

## Sample size and statistical analysis

The hypotheses tested were that PCT-based antibiotic therapy was non-inferior to standard therapy with respect to 3-month mortality (primary endpoint) and that PCT-based therapy would significantly decrease in-ICU and in-hospital antibiotic exposure compared with standard therapy (secondary endpoint). The primary outcome was analyzed on an intention-to-treat basis.

The expected overall 3-month mortality rate was 20% (i.e., 30% [12] and 10% [13] for patients with and without pneumonia, respectively; the distributions were equal), the expected non-inferiority margin was 12%, and the expected one-sided alpha risk was 5%. We estimated that 140 patients per group were needed to demonstrate that excess mortality was absent in the PCT group with 80% power. We concluded that 300 patients were needed. Given the size of the study population and based on the results of our previous reports [12, 13], we estimated that the PCT protocol would reduce the number of days of in-hospital antibiotic exposure by more than 24% compared with standard therapy [an average decrease of 1.9 days in the PCT group (24% of 8 days of antibiotic therapy in the non-PCT group), with a standard deviation of ± 5 days, a two-sided alpha risk of 5% and 90% power]. The difference in 3-month mortality (the primary endpoint) between the randomized groups was computed by a generalized linear model of risk difference adjusting for the presence or absence of pneumonia, as appropriate. The upper-limit of the 90% CI, which corresponded to a 5% risk, had to be lower than the 12% non-inferiority margin for a declaration of non-inferiority. The difference in antibiotic therapy exposure (the secondary endpoint) between the randomized groups was computed by the weighted inverse variance mean difference. No interim analysis was planned. We conducted predefined subgroup analysis based on the presence or absence of pneumonia and post hoc subgroup analyses based on the presence or absence of antibiotic therapy at baseline and the delay between admission and randomization, using the same approach as the overall analysis. The presence of interaction between subgroups was tested by the Breslow-day test.

SAS v.9.4 software (SAS Institute, Cary, NC, USA) was used for the data analysis. All tests were 2-sided, and a *p* value < 0.05 was considered statistically significant.

## Results

### Patient characteristics

A total of 302 patients were randomized into the PCT (n=151) and control (n=151) groups. Three ICUs from
<figure><img src="image_2.png" /><figcaption>**Fig. 1** Flow chart. LRTI low respiratory tract infection</figcaption></figure>

teaching hospitals consecutively included 81% of the sample size. The groups included 64 and 61 patients with AECOPDs with pneumonia, respectively (Fig. 1). The baseline characteristics of the randomized patients are shown in Table 1 (detailed information pertaining to each subgroup may be found in the Supplemental Appendix). A higher percentage of patients with home oxygen and home noninvasive ventilator support were randomized in the PCT group. Overall, 264 patients (87%) needed mechanical ventilation.

Antibiotic therapy during the first 48 h after inclusion included: cephalosporins (31%), macrolides (25%), antipseudomonal penicillins (19%), aminopenicillins (18%), and fluoroquinolones (5%). Patients with pneumonia received combination therapy in 88% of cases (52/64 in PCT group and 58/61 in control group, *p* = 0.013).

During the ICU stay, there were no differences between the PCT and control groups with respect to the following parameters (detailed information may be found in the Supplemental Appendix): the number of patients needing vasopressors and dialysis; the incidences of shock (i.e., septic and cardiogenic shock), ARDS, multi-organ failure, ICU-acquired pneumonia, other ICU-acquired infections, and ICU-acquired pneumothoraxes; mechanical ventilation durations; lengths of stay; and the decision to withhold or withdraw treatment; and mortality. In addition, at the 3-month follow-up, the two groups had experienced a similar number of relapses needing hospitalization.

## Microbiological findings

No differences in microbiological findings were noted between the two study groups (Table 1). A total of 128 patients (42%) had AECOPDs with a confirmed microbiological cause (i.e., 53 (18%) patients had bacterial infections, 62 patients (20%) had viral infections, and 13 patients (4%) had bacterial and viral co-infections). (Detailed information pertaining to each subgroup may be found in the Supplemental Appendix.)

## PCT levels

The two study groups were also similar with regards to the circulating PCT levels at inclusion (PCT-H0), at 6 h after inclusion (PCT-H6), and on days 1, 3 and 5 after inclusion. (Detailed information regarding the two study groups and each subgroup may be found in the Supplemental Appendix.)

## Primary endpoint

At 3 months after inclusion, 51 (17%) patients had died [30 (20%) in the PCT group and 21 (14%) in the control group; adjusted difference, 6.6%; 90% CI -0.3 to 13.5%] (Fig. 2).

The results of the subgroup analyses are shown in Fig. 2. The effect size was not significantly different between patients with and without pneumonia (interaction test, *p*=0.2). Among patients without antibiotic therapy at baseline (*n*=119), the use of PCT significantly increased 3-month mortality [19/61 (31%) vs. 7/58 (12%); adjusted difference, 19.1%; 90% CI 7.2-31.1%, *p*=0.015 by Fisher exact test]. Among patients with antibiotic therapy at baseline (*n*=182), the use of PCT was noninferior to the control group regarding 3-month mortality [10/89 (11%) vs. 14/93 (15%); adjusted difference, -3.0%; 90% CI -10.6 to 4.6%]. The effect size was significantly different between patients with and without antibiotics at baseline (interaction test, *p*=0.019).

## Secondary endpoint

The number of patients in the PCT group who received antibiotics during the PCT algorithm phase was significantly lower than the number of patients in the control group who received antibiotics during the PCT algorithm phase (Fig. 3) (detailed information pertaining to each subgroup may be found in the Supplemental Appendix); however, the in-ICU and in-hospital antibiotic exposure durations, respectively, were similar between the PCT and control group (5.2±6.5 days in the PCT group vs. 5.4±4.4 days in the control group, *p*=0.85, and 7.9±8 days in the PCT group vs. 7.7±5.7 days in the control group, *p*=0.15).
<figure><img src="image_4.png" /><figcaption>**Fig. 1** Flow chart. LRTI low respiratory tract infection</figcaption></figure>

teaching hospitals consecutively included 81% of the sample size. The groups included 64 and 61 patients with AECOPDs with pneumonia, respectively (Fig. 1). The baseline characteristics of the randomized patients are shown in Table 1 (detailed information pertaining to each subgroup may be found in the Supplemental Appendix). A higher percentage of patients with home oxygen and home noninvasive ventilator support were randomized in the PCT group. Overall, 264 patients (87%) needed mechanical ventilation.

Antibiotic therapy during the first 48 h after inclusion included: cephalosporins (31%), macrolides (25%), antipseudomonal penicillins (19%), aminopenicillins (18%), and fluoroquinolones (5%). Patients with pneumonia received combination therapy in 88% of cases (52/64 in PCT group and 58/61 in control group, *p* = 0.013).

During the ICU stay, there were no differences between the PCT and control groups with respect to the following parameters (detailed information may be found in the Supplemental Appendix): the number of patients needing vasopressors and dialysis; the incidences of shock (i.e., septic and cardiogenic shock), ARDS, multi-organ failure, ICU-acquired pneumonia, other ICU-acquired infections, and ICU-acquired pneumothoraxes; mechanical ventilation durations; lengths of stay; and the decision to withhold or withdraw treatment; and mortality. In addition, at the 3-month follow-up, the two groups had experienced a similar number of relapses needing hospitalization.

## Microbiological findings

No differences in microbiological findings were noted between the two study groups (Table 1). A total of 128 patients (42%) had AECOPDs with a confirmed microbiological cause (i.e., 53 (18%) patients had bacterial infections, 62 patients (20%) had viral infections, and 13 patients (4%) had bacterial and viral co-infections). (Detailed information pertaining to each subgroup may be found in the Supplemental Appendix.)

## PCT levels

The two study groups were also similar with regards to the circulating PCT levels at inclusion (PCT-H0), at 6 h after inclusion (PCT-H6), and on days 1, 3 and 5 after inclusion. (Detailed information regarding the two study groups and each subgroup may be found in the Supplemental Appendix.)

## Primary endpoint

At 3 months after inclusion, 51 (17%) patients had died [30 (20%) in the PCT group and 21 (14%) in the control group; adjusted difference, 6.6%; 90% CI -0.3 to 13.5%] (Fig. 2).

The results of the subgroup analyses are shown in Fig. 2. The effect size was not significantly different between patients with and without pneumonia (interaction test, *p* = 0.2). Among patients without antibiotic therapy at baseline (*n* = 119), the use of PCT significantly increased 3-month mortality [19/61 (31%) vs. 7/58 (12%); adjusted difference, 19.1%; 90% CI 7.2–31.1%, *p* = 0.015 by Fisher exact test]. Among patients with antibiotic therapy at baseline (*n* = 182), the use of PCT was noninferior to the control group regarding 3-month mortality [10/89 (11%) vs. 14/93 (15%); adjusted difference, -3.0%; 90% CI -10.6 to 4.6%]. The effect size was significantly different between patients with and without antibiotics at baseline (interaction test, *p* = 0.019).

## Secondary endpoint

The number of patients in the PCT group who received antibiotics during the PCT algorithm phase was significantly lower than the number of patients in the control group who received antibiotics during the PCT algorithm phase (Fig. 3) (detailed information pertaining to each subgroup may be found in the Supplemental Appendix); however, the in-ICU and in-hospital antibiotic exposure durations, respectively, were similar between the PCT and control group (5.2±6.5 days in the PCT group vs. 5.4±4.4 days in the control group, *p* = 0.85, and 7.9±8 days in the PCT group vs. 7.7±5.7 days in
<table><caption>Table 1 Patient characteristics</caption><thead><tr><th></th><th>PCT group<br>n = 151</th><th>Standard group<br>n = 151</th></tr></thead><tbody><tr><td>Age (years), median (Q1-Q3)</td><td>67 (61-76)</td><td>67 (61-75)</td></tr><tr><td>Men, n (%)</td><td>108 (71.5)</td><td>100 (66.2)</td></tr><tr><td>Body mass index, median (Q1-Q3)</td><td>26.0 (22.5-32.0)</td><td>24.5 (21.7-30.1)</td></tr><tr><td>Current smokers, n (%)</td><td>61 (40.4)</td><td>53 (35.1)</td></tr><tr><td>Comorbidities</td><td></td><td></td></tr><tr><td>Arterial hypertension, n (%)</td><td>81 (53.6)</td><td>75 (49.7)</td></tr><tr><td>Cardiopathy, n (%)</td><td>57 (37.7)</td><td>48 (31.8)</td></tr><tr><td>Arteritis, n (%)</td><td>27 (17.9)</td><td>21 (13.9)</td></tr><tr><td>Diabetes mellitus, n (%)</td><td>32 (21.2)</td><td>27 (17.9)</td></tr><tr><td>Malignancy, n (%)</td><td>8 (5.3)</td><td>10 (6.6)</td></tr><tr><td>Chronic renal failure requiring dialysis, n (%)</td><td>4 (2.6)</td><td>1 (0.9)</td></tr><tr><td>Severity of COPD, n (%)</td><td></td><td></td></tr><tr><td>GOLD stage 0</td><td>6 (4)</td><td>4 (3)</td></tr><tr><td>GOLD stage I (FEV<sub>1</sub> ≥ 80% predicted)</td><td>6 (4.0)</td><td>8 (5.3)</td></tr><tr><td>GOLD stage II (FEV<sub>1</sub> ≥ 50 to &lt; 80% predicted)</td><td>25 (16.6)</td><td>22 (14.6)</td></tr><tr><td>GOLD stage III (FEV<sub>1</sub> ≥ 30 to &lt; 50% predicted)</td><td>41 (27.2)</td><td>50 (33.1)</td></tr><tr><td>GOLD stage IV (FEV<sub>1</sub> ≤ 30% predicted)</td><td>58 (38.4)</td><td>53 (35.1)</td></tr><tr><td>GOLD stage unknown</td><td>15 (9.9)</td><td>14 (9.3)</td></tr><tr><td>Baseline FEV<sub>1</sub>, mean (SD)</td><td>1050 (463)</td><td>1026 (522)</td></tr><tr><td>Baseline FEV<sub>1</sub> % predicted, mean (SD)</td><td>41 (15.5)</td><td>39 (16.5)</td></tr><tr><td>FEV<sub>1</sub>/FVC ratio, mean (SD)</td><td>48 (14)</td><td>47 (13.5)</td></tr><tr><td>Home oxygen, n (%)</td><td>63 (41.7)</td><td>51 (33.8)</td></tr><tr><td>Home noninvasive ventilatory support, n (%)</td><td>44 (29.1)</td><td>30 (19.9)</td></tr><tr><td>Number of hospitalizations for AECOPD in previous year</td><td></td><td></td></tr><tr><td>Mean (SD)</td><td>0.93 (1.45)</td><td>0.87 (1.43)</td></tr><tr><td>Median (Q1-Q3)</td><td>0 (0-1)</td><td>0 (0-1)</td></tr><tr><td>Acute exacerbation of COPD</td><td></td><td></td></tr><tr><td>With pneumonia, n (%)</td><td>64 (42.4)</td><td>61 (40.4)</td></tr><tr><td>Without pneumonia, n (%)</td><td>87 (57.6)</td><td>90 (59.6)</td></tr><tr><td>Severity of illness</td><td></td><td></td></tr><tr><td>SAPS II, median (Q1-Q3)</td><td>35 (28-44)</td><td>34 (27-43)</td></tr><tr><td>SOFA score, median (Q1-Q3)</td><td>4 (2-5)</td><td>3 (2-5.75)</td></tr><tr><td>Pneumonia severity index, n (%)</td><td></td><td></td></tr><tr><td>Score, median (Q1-Q3)</td><td>136 (109-155)</td><td>134 (108-156)</td></tr><tr><td>Score, mean (SD)</td><td>133.7 (33.13)</td><td>130.7 (36.2)</td></tr><tr><td>Pneumonia severity index class, n (%)</td><td></td><td></td></tr><tr><td>I (predicted mortality 0.1%)</td><td>0 (0.0)</td><td>0 (0.0)</td></tr><tr><td>II (predicted mortality 0.6%)</td><td>1 (1.6)</td><td>5 (8.2)</td></tr><tr><td>III (predicted mortality 2.8%)</td><td>7 (10.9)</td><td>2 (3.3)</td></tr><tr><td>IV (predicted mortality 8.2%)</td><td>21 (32.8)</td><td>22 (36.1)</td></tr><tr><td>V (predicted mortality 29.2%)</td><td>35 (54.7)</td><td>32 (52.5)</td></tr><tr><td>Time between hospital admission and inclusion, n (%)</td><td></td><td></td></tr><tr><td>&lt; 24 h</td><td>115 (76.2)</td><td>121 (80.1)</td></tr><tr><td>≥ 24 h &lt; 48 h</td><td>33 (21.9)</td><td>19 (12.6)</td></tr><tr><td>≥ 48 h &lt; 72 h</td><td>2 (1.3)</td><td>11 (7.3)</td></tr><tr><td>Mechanical ventilation at the time of inclusion, n (%)</td><td>137 (90.8)</td><td>127 (84.1)</td></tr><tr><td>Invasive, n (%)</td><td>42 (27.8)</td><td>40 (26.5)</td></tr><tr><td>Non-invasive, n (%)</td><td>95 (63)</td><td>87 (57.6)</td></tr></tbody></table>
<table><caption>Table 1 Patient characteristics</caption><thead><tr><th></th><th>PCT group<br>n = 151</th><th>Standard group<br>n = 151</th></tr></thead><tbody><tr><td>Age (years), median (Q1-Q3)</td><td>67 (61-76)</td><td>67 (61-75)</td></tr><tr><td>Men, n (%)</td><td>108 (71.5)</td><td>100 (66.2)</td></tr><tr><td>Body mass index, median (Q1-Q3)</td><td>26.0 (22.5-32.0)</td><td>24.5 (21.7-30.1)</td></tr><tr><td>Current smokers, n (%)</td><td>61 (40.4)</td><td>53 (35.1)</td></tr><tr><td>Comorbidities</td><td></td><td></td></tr><tr><td>Arterial hypertension, n (%)</td><td>81 (53.6)</td><td>75 (49.7)</td></tr><tr><td>Cardiopathy, n (%)</td><td>57 (37.7)</td><td>48 (31.8)</td></tr><tr><td>Arteritis, n (%)</td><td>27 (17.9)</td><td>21 (13.9)</td></tr><tr><td>Diabetes mellitus, n (%)</td><td>32 (21.2)</td><td>27 (17.9)</td></tr><tr><td>Malignancy, n (%)</td><td>8 (5.3)</td><td>10 (6.6)</td></tr><tr><td>Chronic renal failure requiring dialysis, n (%)</td><td>4 (2.6)</td><td>1 (0.8)</td></tr><tr><td>Severity of COPD, n (%)</td><td></td><td></td></tr><tr><td>GOLD stage 0</td><td>6 (4)</td><td>4 (3)</td></tr><tr><td>GOLD stage I (FEV<sub>1</sub> ≥ 80% predicted)</td><td>6 (4.0)</td><td>8 (5.3)</td></tr><tr><td>GOLD stage II (FEV<sub>1</sub> ≥ 50 to &lt; 80% predicted)</td><td>25 (16.6)</td><td>22 (14.6)</td></tr><tr><td>GOLD stage III (FEV<sub>1</sub> ≥ 30 to &lt; 50% predicted)</td><td>41 (27.2)</td><td>50 (33.1)</td></tr><tr><td>GOLD stage IV (FEV<sub>1</sub> ≤ 30% predicted)</td><td>58 (38.4)</td><td>53 (35.1)</td></tr><tr><td>GOLD stage unknown</td><td>15 (9.9)</td><td>14 (9.3)</td></tr><tr><td>Baseline FEV<sub>1</sub>, mean (SD)</td><td>1050 (463)</td><td>1026 (522)</td></tr><tr><td>Baseline FEV<sub>1</sub> % predicted, mean (SD)</td><td>41 (15.5)</td><td>39 (16.5)</td></tr><tr><td>FEV<sub>1</sub>/FVC ratio, mean (SD)</td><td>48 (14)</td><td>47 (13.5)</td></tr><tr><td>Home oxygen, n (%)</td><td>63 (41.7)</td><td>51 (33.8)</td></tr><tr><td>Home noninvasive ventilatory support, n (%)</td><td>44 (29.1)</td><td>30 (19.9)</td></tr><tr><td>Number of hospitalizations for AECOPD in previous year</td><td></td><td></td></tr><tr><td>Mean (SD)</td><td>0.93 (1.45)</td><td>0.87 (1.43)</td></tr><tr><td>Median (Q1-Q3)</td><td>0 (0-1)</td><td>0 (0-1)</td></tr><tr><td>Acute exacerbation of COPD</td><td></td><td></td></tr><tr><td>With pneumonia, n (%)</td><td>64 (42.4)</td><td>61 (40.4)</td></tr><tr><td>Without pneumonia, n (%)</td><td>87 (57.6)</td><td>90 (59.6)</td></tr><tr><td>Severity of illness</td><td></td><td></td></tr><tr><td>SAPS II, median (Q1-Q3)</td><td>35 (28-44)</td><td>34 (27-43)</td></tr><tr><td>SOFA score, median (Q1-Q3)</td><td>4 (2-5)</td><td>3 (2-5.75)</td></tr><tr><td>Pneumonia severity index, n (%)</td><td></td><td></td></tr><tr><td>Score, median (Q1-Q3)</td><td>136 (109-155)</td><td>134 (108-156)</td></tr><tr><td>Score, mean (SD)</td><td>133.7 (33.13)</td><td>130.7 (36.2)</td></tr><tr><td>Pneumonia severity index class, n (%)</td><td></td><td></td></tr><tr><td>I (predicted mortality 0.1%)</td><td>0 (0.0)</td><td>0 (0.0)</td></tr><tr><td>II (predicted mortality 0.6%)</td><td>1 (1.6)</td><td>5 (8.2)</td></tr><tr><td>III (predicted mortality 2.8%)</td><td>7 (10.9)</td><td>2 (3.3)</td></tr><tr><td>IV (predicted mortality 8.2%)</td><td>21 (32.8)</td><td>22 (36.1)</td></tr><tr><td>V (predicted mortality 29.2%)</td><td>35 (54.7)</td><td>32 (52.5)</td></tr><tr><td>Time between hospital admission and inclusion, n (%)</td><td></td><td></td></tr><tr><td>&lt; 24 h</td><td>115 (76.2)</td><td>121 (80.1)</td></tr><tr><td>≥ 24 h &lt; 48 h</td><td>33 (21.9)</td><td>19 (12.6)</td></tr><tr><td>≥ 48 h &lt; 72 h</td><td>2 (1.3)</td><td>11 (7.3)</td></tr><tr><td>Mechanical ventilation at the time of inclusion, n (%)</td><td>137 (90.8)</td><td>127 (84.1)</td></tr><tr><td>Invasive, n (%)</td><td>42 (27.8)</td><td>40 (26.5)</td></tr><tr><td>Non-invasive, n (%)</td><td>95 (63)</td><td>87 (57.6)</td></tr></tbody></table>
<table><caption>Table 1 continued</caption><thead><tr><th></th><th>PCT group<br>n=151</th><th>Standard group<br>n=151</th></tr></thead><tbody><tr><td>Antibiotics at the time of inclusion, n (%)</td><td>89 (58.9)</td><td>93 (61.6)</td></tr><tr><td>Steroids at the time of inclusion, n (%)</td><td>88 (58.3)</td><td>91 (60.3)</td></tr><tr><td>Oral</td><td>74 (49.0)</td><td>74 (49.0)</td></tr><tr><td>Intravenous</td><td>4 (2.6)</td><td>8 (5.3)</td></tr><tr><td>Oral and intravenous</td><td>10 (6.6)</td><td>8 (5.3)</td></tr><tr><td>Microbiologically documented cause of AECOPD, n (%)</td><td></td><td></td></tr><tr><td>Bacterial</td><td>27 (17.9)</td><td>26 (17.2)</td></tr><tr><td>Viral</td><td>35 (23.2)</td><td>27 (17.9)</td></tr><tr><td>Co-infection</td><td>3 (2.0)</td><td>10 (6.6)</td></tr><tr><td>PCT H0 (µg/L)</td><td>0.28 (0.10-0.90)</td><td>0.19 (0.08-0.79)</td></tr><tr><td>PCT &lt; 0.1 µg/L, n (%)</td><td>37 (25.0)</td><td>39 (25.8)</td></tr><tr><td>0.1 ≤ PCT &lt; 0.25 µg/L, n (%)</td><td>33 (22.3)</td><td>40 (28.2)</td></tr><tr><td>PCT ≥ 0.25 µg/L, n (%)</td><td>78 (52.7)</td><td>63 (44.4)</td></tr><tr><td>Data unknown, n (%)</td><td>3 (2.0)</td><td>9 (6.3)</td></tr><tr><td>Leukocyte count (×10<sup>9</sup>/L)</td><td></td><td></td></tr><tr><td>Mean (SD)</td><td>15,003 (12,578)</td><td>14,825 (10,630)</td></tr><tr><td>Median (Q1-Q3)</td><td>12,040 (8865-16,775)</td><td>12,820 (9607-17,152)</td></tr></tbody></table>

<figure><img src="image_3.png" /><figcaption>**Fig. 2** Effect of the PCT protocol on all-cause mortality</figcaption></figure>

the control group, *p*=0.75, respectively) (Fig. 4). Notably, the in-ICU antibiotic exposure duration was not significantly lower in AECOPDs without pneumonia in the PCT group than in AECOPDs without pneumonia in the control group (4±4.6 days in the PCT group vs. 4.8±4.6 days in the control group, *p*=0.25).

## Discussion

In this multicenter, randomized, controlled clinical study, the use of PCT-guided antibiotic therapy failed to demonstrate non-inferiority with respect to 3-month mortality among patients with severe AECOPDs with suspected lower respiratory tract infections who were admitted to
<table><caption>**Table 1 continued**</caption><thead><tr><th></th><th>PCT group<br>n=151</th><th>Standard group<br>n=151</th></tr></thead><tbody><tr><td>Antibiotics at the time of inclusion, n (%)</td><td>89 (58.9)</td><td>93 (61.6)</td></tr><tr><td>Steroids at the time of inclusion, n (%)</td><td>88 (58.3)</td><td>91 (60.3)</td></tr><tr><td>Oral</td><td>74 (49.0)</td><td>74 (49.0)</td></tr><tr><td>Intravenous</td><td>4 (2.6)</td><td>8 (5.3)</td></tr><tr><td>Oral and intravenous</td><td>10 (6.6)</td><td>8 (5.3)</td></tr><tr><td>Microbiologically documented cause of AECOPD, n (%)</td><td></td><td></td></tr><tr><td>Bacterial</td><td>27 (17.9)</td><td>26 (17.2)</td></tr><tr><td>Viral</td><td>35 (23.2)</td><td>27 (17.9)</td></tr><tr><td>Co-infection</td><td>3 (2.0)</td><td>10 (6.6)</td></tr><tr><td>PCT H0 (µg/L)</td><td>0.28 (0.10–0.90)</td><td>0.19 (0.08–0.79)</td></tr><tr><td>PCT &lt; 0.1 µg/L, n (%)</td><td>37 (25.0)</td><td>39 (25.8)</td></tr><tr><td>0.1 ≤ PCT &lt; 0.25 µg/L, n (%)</td><td>33 (22.3)</td><td>40 (28.2)</td></tr><tr><td>PCT ≥ 0.25 µg/L, n (%)</td><td>78 (52.7)</td><td>63 (44.4)</td></tr><tr><td>Data unknown, n (%)</td><td>3 (2.0)</td><td>9 (6.3)</td></tr><tr><td>Leukocyte count (×10<sup>9</sup>/L)</td><td></td><td></td></tr><tr><td>Mean (SD)</td><td>15,003 (12,578)</td><td>14,825 (10,630)</td></tr><tr><td>Median (Q1–Q3)</td><td>12,040 (8865–16,775)</td><td>12,820 (9607–17,152)</td></tr></tbody></table>

<figure><img src="image_5.png" /><figcaption>**Fig. 2** Effect of the PCT protocol on all-cause mortality</figcaption></figure>

the control group, *p*=0.75, respectively) (Fig. 4). Notably, the in-ICU antibiotic exposure duration was not significantly lower in AECOPDs without pneumonia in the PCT group than in AECOPDs without pneumonia in the control group (4±4.6 days in the PCT group vs. 4.8±4.6 days in the control group, *p*=0.25).

**Discussion**

In this multicenter, randomized, controlled clinical study, the use of PCT-guided antibiotic therapy failed to demonstrate non-inferiority with respect to 3-month mortality among patients with severe AECOPDs with suspected lower respiratory tract infections who were admitted to
<figure><img src="image_4.png" /><figcaption>**Fig. 3** Patients receiving antibiotics during the PCT algorithm phase</figcaption></figure>

a In-ICU antibiotic treatment durations

<figure><img src="image_5.png" /></figure>

b In-hospital antibiotic treatment durations

<figure><img src="image_6.png" /><figcaption>**Fig. 4** Effect of the PCT protocol on in-ICU (a) and in-hospital (b) antibiotic treatment durations in the groups randomized according to the presence or absence of pneumonia</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Fig. 3** Patients receiving antibiotics during the PCT algorithm phase</figcaption></figure>

a In-ICU antibiotic treatment durations

<figure><img src="image_7.png" /></figure>

b In-hospital antibiotic treatment durations

<figure><img src="image_8.png" /><figcaption>**Fig. 4** Effect of the PCT protocol on in-ICU (a) and in-hospital (b) antibiotic treatment durations in the groups randomized according to the presence or absence of pneumonia</figcaption></figure>
the ICU. The upper limit of the 90% CI was 13.5%, a per-
centage that exceeded the 12% predefined non-inferiority
margin. This lack of non-inferiority is mainly due to the
subgroup of patients without antibiotic therapy at base-
line, who had a significant higher 3-month mortality in
the PCT group used to initiate antibiotic therapy com-
pared with the control group. Furthermore, the in-ICU
and in-hospital antibiotic exposure durations were simi-
lar between the PCT and control groups.

This result contrasts with those of all previous large
randomized trials assessing the effects of PCT-based
protocols on antibiotic use and outcomes in lower res-
piratory tract infections [4, 5, 20], community-acquired
pneumonia [6, 21] and moderate AECOPDs [7, 22]. In
these studies, PCT-based therapeutic strategies substan-
tially and safely reduced antibiotic use. However, in these
studies, the mean duration of antibiotic therapy in the
control group was rather long compared to the duration
of treatment recommended by more recent guidelines [1,
14], contributing statistical relevance to comparisons. In
addition, most of the patients included in the indicated
trials [4–7, 20–22] were admitted to the emergency
department for disease of low or moderate clinical sever-
ity. Only a minority of patients (range 0–14% [4–7, 20–
22]) required hospitalization in the ICU.

Our results also contrast with those of previous ran-
domized trials [8–11, 23–27] demonstrating that PCT-
guided strategies reduce antibiotic exposure (with the
exception of [24, 25]) without leading to adverse out-
comes in critically ill patients with suspected severe bac-
terial infections. However, only two of the trials were
also designed to demonstrate the non-inferiority of PCT-
guided strategies with respect to mortality. Interestingly,
these two large randomized trials reported contradictory
results. In one study [9], 60-day mortality was higher in
the PCT group than in the control group, and the non-
inferiority margin of 10% was almost reached. In the
other study [10], 28-day and 1-year mortality were signif-
icantly lower in the PCT group than in the control group,
and the non-inferiority margin was 8%. Between-study
differences in the PCT-guided antibiotic protocols may
explain the above discrepancies. One protocol provided
rules for the initiation, continuation and discontinuation
of antibiotic treatment [9], while the other focused on the
deescalation of antibiotic therapy [10]. One study [23],
designed to demonstrate the superiority of PCT-guided
therapy with respect to mortality, noted no improve-
ments in 28-day mortality in the PCT group compared
with the control group. The results of different meta-
analyses were also inconsistent [28–31]. In addition, a
large controlled clinical trial [32] failed to demonstrate
the ability of PCT-guided antimicrobial escalation to
improve survival of patients with severe sepsis or shock

in surgical ICUs. Therefore, the ability of PCT-based
strategies to safely reduce antibiotic exposure in critically
ill patients, especially patients with severe AECOPDs,
remains unclear.

To our knowledge, this was the first randomized con-
trolled clinical trial investigating the ability of a PCT-
based strategy to safely reduce antibiotic exposure in a
homogenous population of patients (i.e., patients with
AECOPDs) with suspected lower respiratory tract infec-
tions who need noninvasive or invasive mechanical ven-
tilation (a routine situation in an adult medical ICU).
This study failed to achieve its primary objective (i.e., to
demonstrate the non-inferiority of a PCT-based strat-
egy with respect to 3-month mortality) and to achieve its
secondary objective (i.e., to demonstrate that PCT-based
strategies decrease, the in-ICU and in-hospital antibi-
otic exposure durations) in the overall cohort and the
predefined subgroups (i.e., AECOPDs with and without
pneumonia). From a theoretical point of view, two differ-
ent explanations could explain the lack of non-inferior-
ity of PCT-guided algorithms in this cohort with severe
AECOPD. Firstly, PCT could fail to distinguish between
infectious and non-infectious causes of ACOPD. Alter-
natively, patients with AECOPD benefit from antibiotic
therapy regardless of the cause of AECOPD, and any
delay in antibiotic prescription in such patients leads to
poorer outcome. The subgroup analysis of patients with-
out antibiotic therapy at baseline strongly support the
latter hypothesis. Therefore, AECOPD patients admitted
in the ICU should promptly initiate antibiotic therapy,
regardless of the level of PCT. This point is also sup-
ported by a Cochrane meta-analysis [33] reporting that
antibiotics reduced the risk of treatment failure in severe
AECOPDs and reduced mortality in patients hospitalized
in the ICU.

Several limitations of the study warrant discussion.
First, this study was an open intervention trial in which
the clinicians knew that their treatment decisions were
observed. Second, the time frame required for reaching
the preplanned sample size (i.e., 6 years) was long. Third,
to reflect clinical practice, we chose to include pneu-
monic and non-pneumonic AECOPD patients with dif-
ferent prognoses; however, randomization was stratified
according to whether pneumonia was present or absent
allowing a similar distribution between groups. Fourth,
antibiotic treatment before the randomization of specific
subsets of patients may have affected PCT levels. How-
ever, previous reports showed that PCT levels were not
different between patients pre-treated with antibiotics
and antibiotic-naïve patients [6, 7, 12, 13]. Fifth, the algo-
rithm proposed in the present study may have underes-
timated the probability that a patient could be infected
at the lowest PCT threshold. However, our group has
the ICU. The upper limit of the 90% CI was 13.5%, a per-
centage that exceeded the 12% predefined non-inferiority
margin. This lack of non-inferiority is mainly due to the
subgroup of patients without antibiotic therapy at base-
line, who had a significant higher 3-month mortality in
the PCT group used to initiate antibiotic therapy com-
pared with the control group. Furthermore, the in-ICU
and in-hospital antibiotic exposure durations were simi-
lar between the PCT and control groups.

This result contrasts with those of all previous large
randomized trials assessing the effects of PCT-based
protocols on antibiotic use and outcomes in lower res-
piratory tract infections [4, 5, 20], community-acquired
pneumonia [6, 21] and moderate AECOPDs [7, 22]. In
these studies, PCT-based therapeutic strategies substan-
tially and safely reduced antibiotic use. However, in these
studies, the mean duration of antibiotic therapy in the
control group was rather long compared to the duration
of treatment recommended by more recent guidelines [1,
14], contributing statistical relevance to comparisons. In
addition, most of the patients included in the indicated
trials [4–7, 20–22] were admitted to the emergency
department for disease of low or moderate clinical sever-
ity. Only a minority of patients (range 0–14% [4–7, 20–
22]) required hospitalization in the ICU.

Our results also contrast with those of previous ran-
domized trials [8–11, 23–27] demonstrating that PCT-
guided strategies reduce antibiotic exposure (with the
exception of [24, 25]) without leading to adverse out-
comes in critically ill patients with suspected severe bac-
terial infections. However, only two of the trials were
also designed to demonstrate the non-inferiority of PCT-
guided strategies with respect to mortality. Interestingly,
these two large randomized trials reported contradictory
results. In one study [9], 60-day mortality was higher in
the PCT group than in the control group, and the non-
inferiority margin of 10% was almost reached. In the
other study [10], 28-day and 1-year mortality were signif-
icantly lower in the PCT group than in the control group,
and the non-inferiority margin was 8%. Between-study
differences in the PCT-guided antibiotic protocols may
explain the above discrepancies. One protocol provided
rules for the initiation, continuation and discontinuation
of antibiotic treatment [9], while the other focused on the
deescalation of antibiotic therapy [10]. One study [23],
designed to demonstrate the superiority of PCT-guided
therapy with respect to mortality, noted no improve-
ments in 28-day mortality in the PCT group compared
with the control group. The results of different meta-
analyses were also inconsistent [28–31]. In addition, a
large controlled clinical trial [32] failed to demonstrate
the ability of PCT-guided antimicrobial escalation to
improve survival of patients with severe sepsis or shock

in surgical ICUs. Therefore, the ability of PCT-based
strategies to safely reduce antibiotic exposure in critically
ill patients, especially patients with severe AECOPDs,
remains unclear.

To our knowledge, this was the first randomized con-
trolled clinical trial investigating the ability of a PCT-
based strategy to safely reduce antibiotic exposure in a
homogenous population of patients (i.e., patients with
AECOPDs) with suspected lower respiratory tract infec-
tions who need noninvasive or invasive mechanical ven-
tilation (a routine situation in an adult medical ICU).
This study failed to achieve its primary objective (i.e., to
demonstrate the non-inferiority of a PCT-based strat-
egy with respect to 3-month mortality) and to achieve its
secondary objective (i.e., to demonstrate that PCT-based
strategies decrease, the in-ICU and in-hospital antibi-
otic exposure durations) in the overall cohort and the
predefined subgroups (i.e., AECOPDs with and without
pneumonia). From a theoretical point of view, two differ-
ent explanations could explain the lack of non-inferior-
ity of PCT-guided algorithms in this cohort with severe
AECOPD. Firstly, PCT could fail to distinguish between
infectious and non-infectious causes of ACOPD. Alter-
natively, patients with AECOPD benefit from antibiotic
therapy regardless of the cause of AECOPD, and any
delay in antibiotic prescription in such patients leads to
poorer outcome. The subgroup analysis of patients with-
out antibiotic therapy at baseline strongly support the
latter hypothesis. Therefore, AECOPD patients admitted
in the ICU should promptly initiate antibiotic therapy,
regardless of the level of PCT. This point is also sup-
ported by a Cochrane meta-analysis [33] reporting that
antibiotics reduced the risk of treatment failure in severe
AECOPDs and reduced mortality in patients hospitalized
in the ICU.

Several limitations of the study warrant discussion.
First, this study was an open intervention trial in which
the clinicians knew that their treatment decisions were
observed. Second, the time frame required for reaching
the preplanned sample size (i.e., 6 years) was long. Third,
to reflect clinical practice, we chose to include pneu-
monic and non-pneumonic AECOPD patients with dif-
ferent prognoses; however, randomization was stratified
according to whether pneumonia was present or absent
allowing a similar distribution between groups. Fourth,
antibiotic treatment before the randomization of specific
subsets of patients may have affected PCT levels. How-
ever, previous reports showed that PCT levels were not
different between patients pre-treated with antibiotics
and antibiotic-naïve patients [6, 7, 12, 13]. Fifth, the algo-
rithm proposed in the present study may have underes-
timated the probability that a patient could be infected
at the lowest PCT threshold. However, our group has
prospectively evaluated the validity of the PCT algorithm
previously in similar patients [12, 13]. In these studies, no
bacteria judged responsible for infection exacerbations
were detected by the systematic screening of the sub-
group of patients with COPD with PCT levels < 0.1 µg/L.
Finally, this PCT algorithm was similar to those used in
previous major studies in the field [4–7].

Conclusion

In this study, we failed to demonstrate non-inferiority
with respect to 3-month mortality of a PCT-based strat-
egy focusing both on initiation or discontinuation of anti-
biotics in patients with severe AECOPDs with suspected
lower respiratory tract infections who needed mechani-
cal ventilation. Furthermore, the PCT-based strategy
failed to reduce in-ICU and in-hospital antibiotic expo-
sure durations. This result may have substantial clinical
implications for the management of critically ill patients
with AECOPDs. Finally, our study indirectly supports
the prompt initiation of antibiotic therapy among severe
AECOPD admitted in ICU to contribute to reduce
3-month mortality.

Electronic supplementary material

The online version of this article (https://doi.org/10.1007/s00134-018-5141-9) contains supplementary material, which is available to authorized users.

Author details

¹ Department of Medical Intensive Care, CHU de Caen, 14000 Caen, France.

² Intensive Care Unit, Centre Hospitalier Lyon Sud, Hospices Civils de Lyon, Pierre Bénite, France. ³ Department of Medial Intensive Care, Cochin University Hospital, Paris, France. ⁴ Department of Intensive Care Medicine, General Hospital, Saint Lô, France. ⁵ Service de Médecine Intensive et Réanimation, Hôpital Raymond Poincaré (APHP), Garches, France. ⁶ Laboratoire Infection and Inflammation, U1173 Université de Versailles SQY-Paris Saclay—INSERM, Paris, France. ⁷ Service de Réanimation et USC Médico-chirurgicale, AP-HP, Hôpitaux Universitaires de l'Est Parisien, Hôpital Tenon, Paris, France. ⁸ Department of Anesthesiology and Critical Care Medicine, Edouard Herriot Hospital, Hospices Civils de Lyon, Lyon, France. ⁹ Department of Biostatistics and Clinical Research, CHU de Caen, 14000 Caen, France. ¹⁰ Department of Medical Intensive Care, CHU de Grenoble Alpes, 38000 Grenoble, France. ¹¹ INSERM, U1042, University of Grenoble-Alpes, HP2, 38000 Grenoble, France. ¹² EA2656 Groupe de Recherche sur l'Adaptation Microbienne (GRAM 2.0), Université Caen Normandie, Caen, France.

Acknowledgements

We thank Marion Provent and Severine Fournel (Unité de Recherche Clinique, Intensive Care Unit, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France and Nathalie Marin (Unité de Recherche Clinique, Department of Medical Intensive Care, Cochin University Hospital, Paris, France) for their outstanding efforts in the monitoring of the study.

**BPCTrea Study Group members** Cédric Daubin, Xavier Valette, Amélie Seguin, Jennifer Brunet, Pierre Charbonneau and Damien Du Cheyron (CHU de Caen, Department of Medical Intensive Care, Caen, 14000, France); Stephane Allouche (Department of Biochemistry, Caen, F-14032, France, and Normandie Univ, UNICAEN, CHU Caen, Signalisation, Electrophysiologie et Imagerie des Lésions d'Ischémie-repefusion Myocardique, Caen, F-14032, France CHU de Caen); François Fournel and Jean-Jacques Parienti (CHU de Caen, Department of Biostatistics and Clinical Research, Caen, 14000, France, and EA4655 Risque Microbiens, Caen Normandie Université, Caen, France); Bertrand Sauneuf (Service de Réanimation Médicale Polyvalente, Centre Hospitalier Public du Cotentin, BP 208, 50102 Cherbourg-en-Cotentin, France); Fabrice Thiollière and Julien Bohe (Intensive Care Unit, Hospices Civils de Lyon,

Centre Hospitalier Lyon Sud, Pierre Bénite, France); Jean-Paul Mira and Fabrice Daviaud (Department of Medical Intensive Care, Cochin University Hospital, Paris, France); Nicolas Terzi (CHU de Grenoble Alpes, Department of Medical Intensive Care, F-38000 Grenoble, France and INSERM, U1042, University of Grenoble-Alpes, HP2, F-38000 Grenoble, France); Pascal Hazera and Michel Ramakers (Department of Intensive Care Medicine, General Hospital, Saint Lô, France); Djillali Annane and Andréa Polito (Service de Médecine Intensive et Réanimation, Hôpital Raymond Poincaré (APHP) and Laboratoire Infection & Inflammation, U1173 Université de Versailles SQY-Paris Saclay, INSERM General Intensive Care Unit, Raymond Poincaré Hospital, Garches, France U1173 Lab Inflammation & Infection, University of Versailles SQY-Paris Saclay—INSERM, Garches, France); Vincent Labbe and Muriel Fartoukh (Service de Réanimation et USC Médico-chirurgicale, AP-HP, Hôpitaux Universitaires de l'Est Parisien, Hôpital Tenon; Groupe de Recherche Clinique CARMAS, Collégium Gallilée); Bernard Floccard (Department of Anesthesiology and Critical Care Medicine, Edouard Herriot Hospital, Hospices Civils de Lyon, Lyon, France); Gérard Alvado and Olivier Cabon (Department of Intensive Care Medicine, General Hospital, Bayeux, France); Mehdi Bousta (Department of Intensive Care Medicine, General Hospital, Havre, France); Jean-Philippe Rigaud (Department of Intensive Care Medicine, General Hospital, Dieppe, France Department of Intensive Care, Dieppe General Hospital, Dieppe, France); and Claire Andrejak (Respiratory and Intensive Care Unit, University Hospital Amiens, Amiens, 80054, France).

Compliance with ethical standards

Conflicts of interest

The authors declare that they have no conflicts of interest.

Ethical approval

The study protocol was approved by the local research ethic committee (Comité de Protection des Personnes Nord Ouest III) for all participating centres.

Informed consent

Written informed consent was obtained from the patients or their surrogates upon their enrolment in the study.

Open Access

This article is distributed under the terms of the Creative Commons Attribu-
tion-NonCommercial 4.0 International License (http://creativecommons.org/
licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and
reproduction in any medium, provided you give appropriate credit to the
original author(s) and the source, provide a link to the Creative Commons
license, and indicate if changes were made.

Received: 31 January 2018 Accepted: 16 March 2018

Published online: 16 April 2018

References

1. Woodhead M, Blasi F, Ewig S, Garau J, Huchon G, Ieven M, Ortqvist A, Schaberg T, Torres A, van der Heijden G, Read R, Verheij TJ, Joint Taskforce of the European Respiratory Society and European Society for Clinical Microbiology and Infectious Diseases (2011) Guidelines for the management of adult lower respiratory tract infections–full version. Clin Microbiol Infect 17(Suppl 6):E1–E59

2. Soler N, Torres A, Ewig S, Gonzalez J, Celis R, El-Ebiary M, Hernandez C, Rodriguez-Roisin R (1998) Bronchial microbial patterns in severe exacerbations of chronic obstructive pulmonary disease (COPD) requiring mechanical ventilation. Am J Respir Crit Care Med 157:1498–1505

3. Cameron RJ, de Wit D, Welsh TN, Ferguson J, Grissell TV, Rye PJ (2006) Virus infection in exacerbations of chronic obstructive pulmonary disease requiring ventilation. Intensive Care Med 32:1022–1029

4. Christ-Crain M, Jaccard-Stolz D, Bingisser R, Gencay MM, Huber PR, Tamm M, Müller B (2004) Effect of procalcitonin-guided treatment on antibiotic use and outcome in lower respiratory tract infections: cluster-randomised, single-blinded intervention trial. Lancet 363:600–607

5. Schuetz P, Christ-Crain M, Thomann R, Falconnier C, Wolbers M, Widmer I, Neidert S, Fricker T, Blum C, Schild U, Regez K, Schoenenberger R, Henzen
prospectively evaluated the validity of the PCT algorithm previously in similar patients [12, 13]. In these studies, no bacteria judged responsible for infection exacerbations were detected by the systematic screening of the subgroup of patients with COPD with PCT levels < 0.1 µg/L. Finally, this PCT algorithm was similar to those used in previous major studies in the field [4–7].

## Conclusion

In this study, we failed to demonstrate non-inferiority with respect to 3-month mortality of a PCT-based strategy focusing both on initiation or discontinuation of antibiotics in patients with severe AECOPDs with suspected lower respiratory tract infections who needed mechanical ventilation. Furthermore, the PCT-based strategy failed to reduce in-ICU and in-hospital antibiotic exposure durations. This result may have substantial clinical implications for the management of critically ill patients with AECOPDs. Finally, our study indirectly supports the prompt initiation of antibiotic therapy among severe AECOPD admitted in ICU to contribute to reduce 3-month mortality.

## Electronic supplementary material

The online version of this article (https://doi.org/10.1007/s00134-018-5141-9) contains supplementary material, which is available to authorized users.

## Author details

¹ Department of Medical Intensive Care, CHU de Caen, 14000 Caen, France.

² Intensive Care Unit, Centre Hospitalier Lyon Sud, Hospices Civils de Lyon, Pierre Bénite, France. ³ Department of Medial Intensive Care, Cochin University Hospital, Paris, France. ⁴ Department of Intensive Care Medicine, General Hospital, Saint Lô, France. ⁵ Service de Médecine Intensive et Réanimation, Hôpital Raymond Poincaré (APHP), Garches, France. ⁶ Laboratoire Infection and Inflammation, U1173 Université de Versailles SQY-Paris Saclay—INSERM, Paris, France. ⁷ Service de Réanimation et USC Médico-chirurgicale, AP-HP, Hôpitaux Universitaires de l'Est Parisien, Hôpital Tenon, Paris, France. ⁸ Department of Anesthesiology and Critical Care Medicine, Edouard Herriot Hospital, Hospices Civils de Lyon, Lyon, France. ⁹ Department of Biostatistics and Clinical Research, CHU de Caen, 14000 Caen, France. ¹⁰ Department of Medical Intensive Care, CHU de Grenoble Alpes, 38000 Grenoble, France. ¹¹ INSERM, U1042, University of Grenoble-Alpes, HP2, 38000 Grenoble, France. ¹² EA2656 Groupe de Recherche sur l'Adaptation Microbienne (GRAM 2.0), Université Caen Normandie, Caen, France.

## Acknowledgements

We thank Marion Provent and Severine Fournel (Unité de Recherche Clinique, Intensive Care Unit, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France and Nathalie Marin (Unité de Recherche Clinique, Department of Medical Intensive Care, Cochin University Hospital, Paris, France) for their outstanding efforts in the monitoring of the study.

**BPCTrea Study Group members** Cédric Daubin, Xavier Valette, Amélie Seguin, Jennifer Brunet, Pierre Charbonneau and Damien Du Cheyron (CHU de Caen, Department of Medical Intensive Care, Caen, 14000, France); Stephane Allouche (Department of Biochemistry, Caen, F-14032, France, and Normandie Univ, UNICAEN, CHU Caen, Signalisation, Electrophysiologie et Imagerie des Lésions d'Ischémie-repefusion Myocardique, Caen, F-14032, France CHU de Caen); François Fournel and Jean-Jacques Parienti (CHU de Caen, Department of Biostatistics and Clinical Research, Caen, 14000, France, and EA4655 Risque Microbiens, Caen Normandie Université, Caen, France); Bertrand Sauneuf (Service de Réanimation Médicale Polyvalente, Centre Hospitalier Public du Cotentin, BP 208, 50102 Cherbourg-en-Cotentin, France); Fabrice Thiollière and Julien Bohe (Intensive Care Unit, Hospices Civils de Lyon,

Centre Hospitalier Lyon Sud, Pierre Bénite, France); Jean-Paul Mira and Fabrice Daviaud (Department of Medical Intensive Care, Cochin University Hospital, Paris, France); Nicolas Terzi (CHU de Grenoble Alpes, Department of Medical Intensive Care, F-38000 Grenoble, France and INSERM, U1042, University of Grenoble-Alpes, HP2, F-38000 Grenoble, France); Pascal Hazera and Michel Ramakers (Department of Intensive Care Medicine, General Hospital, Saint Lô, France); Djillali Annane and Andréa Polito (Service de Médecine Intensive et Réanimation, Hôpital Raymond Poincaré (APHP) and Laboratoire Infection & Inflammation, U1173 Université de Versailles SQY-Paris Saclay, INSERM General Intensive Care Unit, Raymond Poincaré Hospital, Garches, France U1173 Lab Inflammation & Infection, University of Versailles SQY-Paris Saclay—INSERM, Garches, France); Vincent Labbe and Muriel Fartoukh (Service de Réanimation et USC Médico-chirurgicale, AP-HP, Hôpitaux Universitaires de l'Est Parisien, Hôpital Tenon; Groupe de Recherche Clinique CARMAS, Collégium Gallilée); Bernard Floccard (Department of Anesthesiology and Critical Care Medicine, Edouard Herriot Hospital, Hospices Civils de Lyon, Lyon, France); Gérard Alvado and Olivier Cabon (Department of Intensive Care Medicine, General Hospital, Bayeux, France); Mehdi Bousta (Department of Intensive Care Medicine, General Hospital, Havre, France); Jean-Philippe Rigaud (Department of Intensive Care Medicine, General Hospital, Dieppe, France Department of Intensive Care, Dieppe General Hospital, Dieppe, France); and Claire Andrejak (Respiratory and Intensive Care Unit, University Hospital Amiens, Amiens, 80054, France).

## Compliance with ethical standards

### Conflicts of interest

The authors declare that they have no conflicts of interest.

### Ethical approval

The study protocol was approved by the local research ethic committee (Comité de Protection des Personnes Nord Ouest III) for all participating centres.

### Informed consent

Written informed consent was obtained from the patients or their surrogates upon their enrolment in the study.

### Open Access

This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Received: 31 January 2018 Accepted: 16 March 2018

Published online: 16 April 2018

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2. Soler N, Torres A, Ewig S, Gonzalez J, Celis R, El-Ebiary M, Hernandez C, Rodriguez-Roisin R (1998) Bronchial microbial patterns in severe exacerbations of chronic obstructive pulmonary disease (COPD) requiring mechanical ventilation. Am J Respir Crit Care Med 157:1498–1505

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6. Christ-Crain M, Stolz D, Bingisser R, Müller C, Miedinger D, Huber PR, Zimmerli W, Harbarth S, Tamm M, Müller B (2006) Procalcitonin guidance of antibiotic therapy in community-acquired pneumonia. Am J Respir Crit Care Med 174:84–93

7. Stolz D, Christ-Crain M, Bingisser R, Leuppi J, Miedinger D, Müller C, Huber P, Müller B, Tamm M (2007) Antibiotic treatment of exacerbations of COPD, a randomized, controlled trial comparing procalcitonin-guidance with standard therapy. Chest 131:9–19

8. Nobre V, Harbarth S, Graf JD, Rohner P, Pugin J (2008) Use of procalcitonin to shorten antibiotic treatment duration in septic patients. Am J Respir Crit Care Med 177:498–505

9. Bouadma L, Luyt CE, Tubach F, Cracco C, Alvarez A, Schwebel C, Schortgen F, Lasocki S, Veber B, Dehoux M, Bernard M, Pasquet B, Régnier B, Brun-Buisson C, Chastre J, Wolff M, PRORATA trial group (2010) Use of procalcitonin to reduce patients' exposure to antibiotics in intensive care units (PRORATA trial): a multicentre randomised controlled trial. Lancet 375:463–474

10. de Jong E, van Oers JA, Beishuizen A, Vos P, Vermeijden WJ, Haas LE, Loef BG, Dormans T, van Melsen GC, Kluiters YC, Kemperman H, van den Elsen MJ, Schouten JA, Streefkerk JO, Krabbe HG, Kieft H, Kluge GH, van Dam VC, van Pelt J, Bormans L, Otten MB, Reidinga AC, Endeman H, Twisk JW, van de Garde EM, de Smet AM, Kesecioglu J, Girbes AR, Nijsten MW, de Lange DW (2016) Efficacy and safety of procalcitonin guidance in reducing the duration of antibiotic treatment in critically ill patients: a randomised, controlled, open-label trial. Lancet Infect Dis 16:819–827

11. Stolz D, Smyrnios N, Eggimann P, Pargger H, Thakkar N, Siegemund M, Marsch S, Azzola A, Rakic J, Mueller B, Tamm M (2009) Procalcitonin for reduced antibiotic exposure in ventilator-associated pneumonia: a randomised study. Eur Respir 34:1364–1375

12. Daubin C, Parienti JJ, Fradin S, Vabret A, Ramakers M, Terzi N, Freymuth F, Charbonneau P, du Cheyron D (2009) Procalcitonin levels and bacterial aetiology among COPD patients admitted to the ICU with severe pneumonia: a prospective cohort study. BMC Infect Dis 21:157

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