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Acute respiratory distress syndrome subphenotypes and differential response to simvastatin: secondary analysis of a randomised controlled trial.

ABSTRACT: BACKGROUND:Precision medicine approaches that target patients on the basis of disease subtype have transformed treatment approaches to cancer, asthma, and other heterogeneous syndromes. Two distinct subphenotypes of acute respiratory distress syndrome (ARDS) have been identified in three US-based clinical trials, and these subphenotypes respond differently to positive end-expiratory pressure and fluid management. We aimed to investigate whether these subphenotypes exist in non-US patient populations and respond differently to pharmacotherapies. METHODS:HARP-2 was a multicentre, randomised controlled trial of simvastatin (80 mg) versus placebo done in general intensive care units (ICUs) at 40 hospitals in the UK and Ireland within 48 h of onset of ARDS. The primary outcome was ventilator-free days, and secondary outcomes included non-pulmonary organ failure-free days and mortality. In a secondary analysis of HARP-2, we applied latent class analysis to baseline data without consideration of outcomes to identify subphenotypes, and we compared clinical outcomes across subphenotypes and treatment groups. FINDINGS:540 patients were recruited to HARP-2. One patient withdrew consent for the use of their data, so data from 539 patients were analysed. In our secondary analysis, a two-class (two subphenotype) model was an improvement over a one-class model (p<0·0001), with 353 (65%) patients in the hypoinflammatory subphenotype group and 186 (35%) in the hyperinflammatory subphenotype group. Additional classes did not improve model fit. Clinical and biological characteristics of the two subphenotypes were similar to previous studies. Patients with the hyperinflammatory subphenotype had fewer ventilator-free days (median 2 days [IQR 0-17] vs 18 [IQR 0-23]; p<0·0001), fewer non-pulmonary organ failure-free days (15 [0-25] vs 27 [21-28]; p<0·0001), and higher 28-day mortality (73 [39%] vs 59 [17%]; p<0·0001) than did those with the hypoinflammatory subphenotype. Although HARP-2 found no difference in 28-day survival between placebo and simvastatin, significantly different survival was identified across patients stratified by treatment and subphenotype (p<0·0001). Specifically, within the hyperinflammatory subphenotype, patients treated with simvastatin had significantly higher 28-day survival than did those given placebo (p=0·008). A similar pattern was observed for 90-day survival. INTERPRETATION:Two subphenotypes of ARDS were identified in the HARP-2 cohort, with distinct clinical and biological features and disparate clinical outcomes. The hyperinflammatory subphenotype had improved survival with simvastatin compared with placebo. These findings support further pursuit of predictive enrichment strategies in critical care clinical trials. FUNDING:UK Efficacy and Mechanism Evaluation Programme and National Institutes of Health.

SUBMITTER: Calfee CS

PROVIDER: S-EPMC6201750 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Acute respiratory distress syndrome subphenotypes and differential response to simvastatin: secondary analysis of a randomised controlled trial.

Calfee Carolyn S CS Delucchi Kevin L KL Sinha Pratik P Matthay Michael A MA Hackett Jonathan J Shankar-Hari Manu M McDowell Cliona C Laffey John G JG O'Kane Cecilia M CM McAuley Daniel F DF

The Lancet. Respiratory medicine 20180802 9

<h4>Background</h4>Precision medicine approaches that target patients on the basis of disease subtype have transformed treatment approaches to cancer, asthma, and other heterogeneous syndromes. Two distinct subphenotypes of acute respiratory distress syndrome (ARDS) have been identified in three US-based clinical trials, and these subphenotypes respond differently to positive end-expiratory pressure and fluid management. We aimed to investigate whether these subphenotypes exist in non-US patient ...[more]

PMID: 30078618

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Project description:BackgroundSubphenotypes have been identified within heterogeneous diseases such as asthma and breast cancer, with important therapeutic implications. We assessed whether subphenotypes exist within acute respiratory distress syndrome (ARDS), another heterogeneous disorder.MethodsWe used data from two ARDS randomised controlled trials (ARMA trial and ALVEOLI trial), sponsored by the National Heart, Lung, and Blood Institute. We applied latent class modelling to identify subphenotypes using clinical and biological data. We modelled data from both studies independently. We then tested the association of subphenotypes with clinical outcomes in both cohorts and with the response to positive end-expiratory pressure (PEEP) in the ALVEOLI cohort.FindingsWe analysed data for 1022 patients: 473 in the ARMA cohort and 549 in the ALVEOLI cohort. Independent latent class models indicated that a two-class (ie, two subphenotype) model was the best fit for both cohorts. In both cohorts, we identified a hyperinflammatory subphenotype (phenotype 2) that was characterised by higher plasma concentrations of inflammatory biomarkers, a higher prevalence of vasopressor use, lower serum bicarbonate concentrations, and a higher prevalence of sepsis than phenotype 1. Participants in phenotype 2 had higher mortality and fewer ventilator-free days and organ failure-free days in both cohorts than did those in phenotype 1 (p<0·007 for all). In the ALVEOLI cohort, the effects of ventilation strategy (high PEEP vs low PEEP) on mortality, ventilator-free days and organ failure-free days differed by phenotype (p=0·049 for mortality, p=0·018 for ventilator-free days, p=0·003 for organ-failure-free days).InterpretationWe have identified two subphenotypes within ARDS, one of which is categorised by more severe inflammation, shock, and metabolic acidosis and by worse clinical outcomes. Response to treatment in a randomised trial of PEEP strategies differed on the basis of subphenotype. Identification of ARDS subphenotypes might be useful in selecting patients for future clinical trials.FundingNational Institutes of Health.

Project description:BackgroundUsing latent class analysis (LCA) in five randomised controlled trial (RCT) cohorts, two distinct phenotypes of acute respiratory distress syndrome (ARDS) have been identified: hypoinflammatory and hyperinflammatory. The phenotypes are associated with differential outcomes and treatment response. The objective of this study was to develop parsimonious models for phenotype identification that could be accurate and feasible to use in the clinical setting.MethodsIn this retrospective study, three RCT cohorts from the National Lung, Heart, and Blood Institute ARDS Network (ARMA, ALVEOLI, and FACTT) were used as the derivation dataset (n=2022), from which the machine learning and logistic regression classifer models were derived, and a fourth (SAILS; n=715) from the same network was used as the validation test set. LCA-derived phenotypes in all of these cohorts served as the reference standard. Machine-learning algorithms (random forest, bootstrapped aggregating, and least absolute shrinkage and selection operator) were used to select a maximum of six important classifier variables, which were then used to develop nested logistic regression models. Only cases with complete biomarker data in the derivation dataset were used for variable selection. The best logistic regression models based on parsimony and predictive accuracy were then evaluated in the validation test set. Finally, the models' prognostic validity was tested in two external ARDS clinical trial datasets (START and HARP-2) by assessing mortality at days 28, 60, and 90 and ventilator-free days to day 28.FindingsThe six most important classifier variables were interleukin (IL)-8, IL-6, protein C, soluble tumour necrosis factor receptor 1, bicarbonate, and vasopressor use. From the nested models, three-variable (IL-8, bicarbonate, and protein C) and four-variable (3-variable plus vasopressor use) models were adjudicated to be the best performing. In the validation test set, both models showed good accuracy (AUC 0·94 [95% CI 0·92-0·95] for the three-variable model and 0·95 [95% CI 0·93-0·96] for the four-variable model) against LCA classifications. As with LCA-derived phenotypes, the hyperinflammatory phenotype as identified by the classifier model was associated with higher mortality at day 90 (87 [39%] of 223 patients vs 112 [23%] of 492 patients; p<0·0001) and fewer ventilator-free days (median 14 days [IQR 0-22] vs 22 days [0-25]; p<0·0001). In the external validation datasets, three-variable models developed in the derivation dataset identified two phenotypes with distinct clinical features and outcomes consistent with previous findings, including differential survival with simvastatin versus placebo in HARP-2 (p=0·023 for survival at 28 days).InterpretationARDS phenotypes can be accurately identified with parsimonious classifier models using three or four variables. Pending the development of real-time testing for key biomarkers and prospective validation, these models could facilitate identification of ARDS phenotypes to enable their application in clinical trials and practice.FundingNational Institutes of Health.

Project description:IntroductionPatients with COVID-19-related acute respiratory distress syndrome (ARDS) have been postulated to present with distinct respiratory subphenotypes. However, most phenotyping schema have been limited by sample size, disregard for temporal dynamics, and insufficient validation. We aimed to identify respiratory subphenotypes of COVID-19-related ARDS using unbiased data-driven approaches.MethodsPRoVENT-COVID was an investigator-initiated, national, multicentre, prospective, observational cohort study at 22 intensive care units (ICUs) in the Netherlands. Consecutive patients who had received invasive mechanical ventilation for COVID-19 (aged 18 years or older) served as the derivation cohort, and similar patients from two ICUs in the USA served as the replication cohorts. COVID-19 was confirmed by positive RT-PCR. We used latent class analysis to identify subphenotypes using clinically available respiratory data cross-sectionally at baseline, and longitudinally using 8-hourly data from the first 4 days of invasive ventilation. We used group-based trajectory modelling to evaluate trajectories of individual variables and to facilitate potential clinical translation. The PRoVENT-COVID study is registered with ClinicalTrials.gov, NCT04346342.FindingsBetween March 1, 2020, and May 15, 2020, 1007 patients were admitted to participating ICUs in the Netherlands, and included in the derivation cohort. Data for 288 patients were included in replication cohort 1 and 326 in replication cohort 2. Cross-sectional latent class analysis did not identify any underlying subphenotypes. Longitudinal latent class analysis identified two distinct subphenotypes. Subphenotype 2 was characterised by higher mechanical power, minute ventilation, and ventilatory ratio over the first 4 days of invasive mechanical ventilation than subphenotype 1, but PaO2/FiO2, pH, and compliance of the respiratory system did not differ between the two subphenotypes. 185 (28%) of 671 patients with subphenotype 1 and 109 (32%) of 336 patients with subphenotype 2 had died at day 28 (p=0·10). However, patients with subphenotype 2 had fewer ventilator-free days at day 28 (median 0, IQR 0-15 vs 5, 0-17; p=0·016) and more frequent venous thrombotic events (109 [32%] of 336 patients vs 176 [26%] of 671 patients; p=0·048) compared with subphenotype 1. Group-based trajectory modelling revealed trajectories of ventilatory ratio and mechanical power with similar dynamics to those observed in latent class analysis-derived trajectory subphenotypes. The two trajectories were: a stable value for ventilatory ratio or mechanical power over the first 4 days of invasive mechanical ventilation (trajectory A) or an upward trajectory (trajectory B). However, upward trajectories were better independent prognosticators for 28-day mortality (OR 1·64, 95% CI 1·17-2·29 for ventilatory ratio; 1·82, 1·24-2·66 for mechanical power). The association between upward ventilatory ratio trajectories (trajectory B) and 28-day mortality was confirmed in the replication cohorts (OR 4·65, 95% CI 1·87-11·6 for ventilatory ratio in replication cohort 1; 1·89, 1·05-3·37 for ventilatory ratio in replication cohort 2).InterpretationAt baseline, COVID-19-related ARDS has no consistent respiratory subphenotype. Patients diverged from a fairly homogenous to a more heterogeneous population, with trajectories of ventilatory ratio and mechanical power being the most discriminatory. Modelling these parameters alone provided prognostic value for duration of mechanical ventilation and mortality.FundingAmsterdam UMC.

Project description:OBJECTIVES:Classification of patients with acute respiratory distress syndrome into hyper- and hypoinflammatory subphenotypes using plasma biomarkers may facilitate more effective targeted therapy. We examined whether established subphenotypes are present not only in patients with acute respiratory distress syndrome but also in patients at risk for acute respiratory distress syndrome (ARFA) and then assessed the prognostic information of baseline subphenotyping on the evolution of host-response biomarkers and clinical outcomes. DESIGN:Prospective, observational cohort study. SETTING:Medical ICU at a tertiary academic medical center. PATIENTS:Mechanically ventilated patients with acute respiratory distress syndrome or ARFA. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:We performed longitudinal measurements of 10 plasma biomarkers of host injury and inflammation. We applied unsupervised latent class analysis methods utilizing baseline clinical and biomarker variables and demonstrated that two-class models (hyper- vs hypoinflammatory subphenotypes) offered improved fit compared with one-class models in both patients with acute respiratory distress syndrome and ARFA. Baseline assignment to the hyperinflammatory subphenotype (39/104 [38%] acute respiratory distress syndrome and 30/108 [28%] ARFA patients) was associated with higher severity of illness by Sequential Organ Failure Assessment scores and incidence of acute kidney injury in patients with acute respiratory distress syndrome, as well as higher 30-day mortality and longer duration of mechanical ventilation in ARFA patients (p < 0.0001). Hyperinflammatory patients exhibited persistent elevation of biomarkers of innate immunity for up to 2 weeks postintubation. CONCLUSIONS:Our results suggest that two distinct subphenotypes are present not only in patients with established acute respiratory distress syndrome but also in patients at risk for its development. Hyperinflammatory classification at baseline is associated with higher severity of illness, worse clinical outcomes, and trajectories of persistently elevated biomarkers of host injury and inflammation during acute critical illness compared with hypoinflammatory patients. Our findings provide strong rationale for examining treatment effect modifications by subphenotypes in randomized clinical trials to inform precision therapeutic approaches in critical care.

Project description:BackgroundFatty acid oxidation (FAO) defects have been implicated in experimental models of acute lung injury and associated with poor outcomes in critical illness. In this study, we examined acylcarnitine profiles and 3-methylhistidine as markers of FAO defects and skeletal muscle catabolism, respectively, in patients with acute respiratory failure. We determined whether these metabolites were associated with host-response ARDS subphenotypes, inflammatory biomarkers, and clinical outcomes in acute respiratory failure.MethodsIn a nested case-control cohort study, we performed targeted analysis of serum metabolites of patients intubated for airway protection (airway controls), Class 1 (hypoinflammatory), and Class 2 (hyperinflammatory) ARDS patients (N = 50 per group) during early initiation of mechanical ventilation. Relative amounts were quantified by liquid chromatography high resolution mass spectrometry using isotope-labeled standards and analyzed with plasma biomarkers and clinical data.ResultsOf the acylcarnitines analyzed, octanoylcarnitine levels were twofold increased in Class 2 ARDS relative to Class 1 ARDS or airway controls (P = 0.0004 and < 0.0001, respectively) and was positively associated with Class 2 by quantile g-computation analysis (P = 0.004). In addition, acetylcarnitine and 3-methylhistidine were increased in Class 2 relative to Class 1 and positively correlated with inflammatory biomarkers. In all patients within the study with acute respiratory failure, increased 3-methylhistidine was observed in non-survivors at 30 days (P = 0.0018), while octanoylcarnitine was increased in patients requiring vasopressor support but not in non-survivors (P = 0.0001 and P = 0.28, respectively).ConclusionsThis study demonstrates that increased levels of acetylcarnitine, octanoylcarnitine, and 3-methylhistidine distinguish Class 2 from Class 1 ARDS patients and airway controls. Octanoylcarnitine and 3-methylhistidine were associated with poor outcomes in patients with acute respiratory failure across the cohort independent of etiology or host-response subphenotype. These findings suggest a role for serum metabolites as biomarkers in ARDS and poor outcomes in critically ill patients early in the clinical course.

Project description:BackgroundPaediatric acute respiratory distress syndrome (PARDS) is a manifestation of severe, life-threatening lung injury necessitating mechanical ventilation with mortality rates ranging up to 40-50%. Neuromuscular blockade agents (NMBAs) may be considered to prevent patient self-inflicted lung injury in PARDS patients, but two trials in adults with severe ARDS yielded conflicting results. To date, randomised controlled trials (RCT) examining the effectiveness and efficacy of NMBAs for PARDS are lacking. We hypothesise that using NMBAs for 48 h in paediatric patients younger than 5 years of age with early moderate-to-severe PARDS will lead to at least a 20% reduction in cumulative respiratory morbidity score 12 months after discharge from the paediatric intensive care unit (PICU).MethodsThis is a phase IV, multicentre, randomised, double-blind, placebo-controlled trial performed in level-3 PICUs in the Netherlands. Eligible for inclusion are children younger than 5 years of age requiring invasive mechanical ventilation with positive end-expiratory pressure (PEEP) ≥ 5 cm H2O for moderate-to-severe PARDS occurring within the first 96 h of PICU admission. Patients are randomised to continuous infusion of rocuronium bromide or placebo for 48 h. The primary endpoint is the cumulative respiratory morbidity score 12 months after PICU discharge, adjusted for confounding by age, gestational age, family history of asthma and/or allergy, season in which questionnaire was filled out, day-care and parental smoking. Secondary outcomes include respiratory mechanics, oxygenation and ventilation metrics, pulmonary and systemic inflammation markers, prevalence of critical illness polyneuropathy and myopathy and metrics for patient outcome including ventilator free days at day 28, length of PICU and hospital stay, and mortality DISCUSSION: This is the first paediatric trial evaluating the effects of muscular paralysis in moderate-to-severe PARDS. The proposed study addresses a huge research gap identified by the Paediatric Acute Lung Injury Consensus Collaborative by evaluating practical needs regarding the treatment of PARDS. Paediatric critical care practitioners are inclined to use interventions such as NMBAs in the most critically ill. This liberal use must be weighed against potential side effects. The proposed study will provide much needed scientific support in the decision-making to start NMBAs in moderate-to-severe PARDS.Trial registrationClinicalTrials.gov NCT02902055 . Registered on September 15, 2016.

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Acute respiratory distress syndrome subphenotypes and differential response to simvastatin: secondary analysis of a randomised controlled trial.

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Acute respiratory distress syndrome subphenotypes and differential response to simvastatin: secondary analysis of a randomised controlled trial.

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