Clinical trial NCT06916481: Definition of Sub-phenotypes of Pneumonia Based on the Respiratory Microbiome Composition to Predict Microbial and Clinical Treatment Failures
Official title: Definition of Sub-phenotypes of Pneumonia Based on the Respiratory Microbiome Composition to Predict Microbial and Clinical Treatment Failures
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Community Acquired or Acquiring Hospital Acquired Pneumonia
Keywords: Pneumonia, respiratory microbiome, antibiotic treatment
Lead sponsor: Assistance Publique - Hôpitaux de Paris
Sponsor class: OTHER
First posted: 2025-04-08
Enrollment: 300
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: The population of interest is specific to each cohort. \> For cohort 1: patients will be informed orally and in writing by the investigator on the delegation log during their hospitalization before inclusion. Patients will be informed of their right to decline participation and an informed written consent will be obtained by the investigator for biobank collection. \> For cohorts 2 and 3: some patients may not be able to decline participation (sedated, ventilated). In these cases, relatives, if they are present, will be informed orally and in writing by the investigator on the delegation log. Relatives will be informed of their right to decline participation on behalf of the patient. Patients will be informed as soon as their health allows it. Patients will be informed of their right to decline to continue, and of their right to forbid the use of already collected data and/or samples.

Brief summary: Background: Pneumonia remains a leading cause of antibiotic consumption globally, contributing significantly to the burden of antimicrobial resistance (AMR). The respiratory microbiome plays a crucial role in the emergence of AMR and therapeutic failure in both community-acquired pneumonia (CAP) and hospital-acquired pneumonia (HAP). The PHENOMENON study aims to investigate the relationship between the respiratory microbiome composition and clinical outcomes to improve the prediction of treatment failure and AMR emergence.

Methods: This multicenter prospective cohort study will include 300 adult patients across three cohorts: CAP in general wards, severe CAP in intensive care units (ICU), and ventilator-associated HAP (vHAP/VAP). Patients will undergo oropharyngeal and rectal swabbing at admission (Day 0), Day 3, Day 7-10, and Day 90, along with blood sampling and endotracheal aspirates in intubated patients. The primary objective is to assess the association between baseline respiratory microbiome composition and time to antibiotic response within 7-10 days. The composite primary endpoint includes clinical failure, microbiological failure, or AMR emergence. Secondary endpoints explore the association between microbiome composition and pneumonia recurrence, severity, hospital length of stay, and mortality at Day 28 and Day 90.

Expected Outcomes: This study will provide insights into the predictive value of respiratory microbiome composition on antibiotic response and AMR emergence. Understanding these relationships may guide personalized antibiotic strategies and optimize pneumonia management, ultimately reducing treatment failure rates and improving patient outcomes.

Detailed description: Pneumonia can be acquired in the community such as COVID-19 or flu, or during hospitalization for a different medical condition.

The significant burden of CAP is set to increase with ageing populations and growing rates of comorbidity. CAP was the leading cause of communicable diseases and the second cause of disability-adjusted life-years loss in the world in 2019, even before the COVID-19 pandemic (GBD 2019 Adolescent Mortality Collaborators 2021; GBD 2019 Diseases and Injuries Collaborators 2020). CAP is classically induced by virulent bacteria (such as Streptococcus pneumoniae) or viruses (influenza), but also new pathogenic viruses such as SARS-CoV-2 (COVID-19).

Incidence of VAP ranges from 5% to 67% depending on case mix and diagnostic criteria. In the US, the incidence of VAP ranges from 2 to 16 episodes per 1,000 ventilator-day. The estimated risk of VAP is initially high and decreases to less than 0.5% per day after 14 days of mechanical ventilation. VAP increases the duration of hospitalization by 7 days and health-care costs by approximately $40,000 USD per episode (Safdar et al. 2005; Eber et al. 2010). Antimicrobial resistance is rising, leading to increased durations of hospital stay and excess deaths in septic patients worldwide. The World Health Organization considers antibiotic resistance to be one of the biggest global health threats we are currently facing. AMR, including malaria, tuberculosis and bacterial infections, may increase to 10 million fatalities worldwide by 2050. While some resistance is intrinsic in some bacterial taxa, the main issue is acquired resistance, as bacteria can exchange genetic material and thereby spread antibiotic resistance genes (ARG).

Previous carriage of extended-spectrum beta-lactamases-producing Enterobacterales (ESBL-E) is found in 5 to 25% of ICU patients. Although a previous carriage is the major risk factor associated with VAP related to ESBL-E, only 5% to 20% of the ESBL-E carriers will develop a VAP related to ESBL-E. Carriage status therefore has a high negative predictive value for ESBL-E-associated VAP, whereas positive predictive value, i.e., the probability of having an ESBL-E infection in case of ESBL-E carriage, is less than 50%.

When caring for patients with VAP, recent studies have shown that the adequacy of the initial antimicrobial therapy is not associated with a significant improvement of VAP prognosis, especially if a multidrug-resistant (MDR) Gram-negative bacterium is involved (Sommer et al. 2018; Titov et al. 2021). One likely explanation of the absence of benefit of adequate therapy within 24h is the rapid diffusion and expression of ARGs within the microbiome during treatment. It has been demonstrated the feasibility of characterizing lung microbiota by producing preliminary data from 174 respiratory samples collected in 65 patients included in the IBIS biobank within the IBIS cohort. These preliminary analyses have also confirmed that the respiratory microbiome of hospitalized patients shifts from a normal composition (day 1) to a specific pattern poor in Streptococcus and enriched in Haemophilus (day 7). Recently, it was observed in a randomized clinical trial that probiotics increase the ARG richness of the gut microbiome during antimicrobial treatment (Figure 2) (Montassier et al. 2021). These data demonstrated the ability to investigate the time course of ARG during treatment in human samples, and reinforce the hypothesis of rapid modifications of the ARG during treatment.

In summary, treatment failures are common in patients with CAP and HAP, even in cases of adequate antimicrobial therapy. Some specific antimicrobial therapies result in better outcomes than standard of cares and classical microbiology fail to explain this outcome.

Recent data demonstrated that the microbiome is a significant source of antibiotic resistance genes (ARG) which can rapidly be diffused between species during treatment.

In light of these preliminary results, we intend

1. to define VAP and CAP sub-phenotypes based on the real-time course of the load of ARG in vivo
2. to demonstrate in vivo that specific microbiome editing based on these phenotypes can enhance pneumonia outcomes.

The definition of these phenotypes of pneumonia is likely to impact the way patients are treated in daily practice, shifting the antimicrobial treatment from in vitro functional tests to in vivo prediction of response to treatment.

Eligibility criteria: Inclusion Criteria:

* Cohort 1: CAP at emergency department and requiring hospitalization in general wards :

  * Age ≥18 years
  * Hospitalization in a medical department (not ICU)
  * Presence of at least one acute clinical sign compatible with pneumonia (e.g. dyspnea, cough, purulent sputum or purulent tracheal aspirations or crackles), and temperature above 38°C in the 48 hours prior to inclusion
  * AND new pulmonary infiltrate on chest X-ray or CT scan (on Day 0 or within three days of inclusion)
  * Efficient treatment initiated for less than 24 hours
  * Sputum collection possible
* Cohort 2: Severe CAP with ICU hospitalization :

  * Age ≥18 years
  * Hospitalization in intensive care unit for at least 24 hours.
  * Presence of at least one acute clinical sign compatible with pneumonia (e.g. dyspnoea, cough, purulent sputum or crackles), temperature greater than 38°C in the 48 hours prior to hospital admission
  * AND new pulmonary infiltrate on chest X-ray or CT scan (on Day 0 or within three days of inclusion)
  * Efficient treatment initiated for less than 24 hours
  * Sputum collection or tracheal aspiration or any distal bacterial sample (BAL, plugged telescopic catheter) collection possible
* Cohort 3: vHAP or VAP :

  * Age ≥18 years
  * vHAP: mechanical ventilation, in a patient previously hospitalized for more than 48 hours at the onset of new or worsening radiological infiltrates and 2 of the following: fever or hypothermia, leukocytosis \> 12 G/L or leukopenia \< 4G/L, purulent tracheal aspirates,
  * VAP: mechanical ventilation for more than 48 hours, new or worsening radiological infiltrates and 2 of the following: fever (\>38°C) or hypothermia (\<36.5°C) in the 24 hours prior to inclusion, leucocytosis\> 12 G/L or leukopenia \< 4G/L, purulent tracheal aspirates
  * AND plugged telescopic catheter (PTC) ≥103colony-forming units (CFU)/ml or bronchoalveolar lavage (BAL) culture ≥104 CFU/ml or purulent tracheal aspirates ≥ 106 UFC/mL
  * AND treated with active antibiotic therapy for pneumonia for less than 24 hours

Exclusion Criteria:

* Cohort 1: CAP with hospitalization in general wards :

  * AIDS
  * Patient on high-dose corticosteroids \>2 mg/kg prednisone equivalent
  * Bone marrow transplant patients
  * Cancer patients undergoing chemotherapy within 3 months of inclusion
  * Opposition of the patient (absence of informed written consent)
  * Scheduled transfer to another hospital
  * Patient under guardianship or comparable legal status
  * NB: Patients included in the cohort 1 and referred to ICU within the first 24 hours will be included in the cohort 2.
* Cohort 2: Severe CAP with ICU hospitalization :

  * AIDS
  * Patient on high-dose corticosteroids \>2 mg/kg prednisone equivalent
  * Bone marrow transplant patients
  * Cancer patients undergoing chemotherapy within 3 months of inclusion
  * Stays shorter than 24h in the ICU will be exlcuded
  * Absence of informed written consent of the patient if they are fit, or absence of informed written consent of the relative/caregiver (for patients unable to understand the information and in the absence of a relative/caregiver, emergency inclusion is authorized)
  * Decision to forego life-sustaining therapy
  * Patient under guardianship or comparable legal status
* Cohort 3: vHAP or VAP :

  * AIDS
  * Patient on high-dose corticosteroids \>2 mg/kg prednisone equivalent
  * Bone marrow transplant patients
  * Cancer patients undergoing chemotherapy within 3 months of inclusion
  * Absence of informed written consent of the patient if he is fit, or absence of informed written consent of the relative (for patients unable to understand the information and in the absence of a relative, emergency inclusion is authorized)
  * Decision to forego life-sustaining therapy
  * Patient under guardianship or comparable legal status

Primary outcomes:
measure: To study the relationship between the composition of the respiratory microbiome at the start of treatment and time to response to antibiotic treatment.
timeFrame: 3 months
measure: To study the relationship between the composition of the respiratory microbiome at the start of treatment and time to response to antibiotic treatment.
timeFrame: 3 months
measure: To study the relationship between the composition of the respiratory microbiome at the start of treatment and time to response to antibiotic treatment.
timeFrame: 3 months
measure: To study the relationship between the composition of the respiratory microbiome at the start of treatment and time to response to antibiotic treatment.
timeFrame: 3 months
measure: To study the relationship between the composition of the respiratory microbiome at the start of treatment and time to response to antibiotic treatment.
timeFrame: 3 months
measure: To study the relationship between the composition of the respiratory microbiome at the start of treatment and time to response to antibiotic treatment.
timeFrame: 3 months
measure: To study the relationship between the composition of the respiratory microbiome at the start of treatment and time to response to antibiotic treatment.
timeFrame: 3 months
Secondary outcomes:
measure: Pneumonia relapse or recurrence
timeFrame: 3 months
measure: Time to clinical recovery (regardless of microbiological recovery or resistance failure)
timeFrame: 3 months
measure: Time to clinical recovery (regardless of microbiological recovery or resistance failure)
timeFrame: 3 months
measure: Presence or absence of antimicrobial resistance at any point during follow-up
timeFrame: 3 months
measure: Association between specific antibiotics and respiratory microbiome evolution
timeFrame: 3 months
measure: Association between specific antibiotics and gut microbiome evolution
timeFrame: 3 months
measure: Duration of antimicrobial treatment
timeFrame: 3 months
measure: Association between baseline microbiome and Acute Respiratory Distress Syndrome during pneumonia
timeFrame: 3 months
measure: Association between baseline microbiome and Length of initial hospital stay/ ICU stay
timeFrame: 3 months
measure: Association between baseline microbiome and All-cause mortality on day 28 and day 90
timeFrame: 3 months
measure: Quality of life questionnaires (EQ-5D-5L) on day 0, day 28 and day 90
timeFrame: 3 months
measure: Correlation between oropharyngeal, endotracheal and gut microbiota profiles in intubated patients
timeFrame: 3 months
Other outcomes:
Locations:
city: Paris
country: France
facility: Hospital Bichat
Study officials:
References: