Identifying molecular phenotypes in sepsis : an analysis of two prospective observational cohorts and secondary analysis of two randomised controlled trials
Copyright © 2023 Elsevier Ltd. All rights reserved..
BACKGROUND: In sepsis and acute respiratory distress syndrome (ARDS), heterogeneity has contributed to difficulty identifying effective pharmacotherapies. In ARDS, two molecular phenotypes (hypoinflammatory and hyperinflammatory) have consistently been identified, with divergent outcomes and treatment responses. In this study, we sought to derive molecular phenotypes in critically ill adults with sepsis, determine their overlap with previous ARDS phenotypes, and evaluate whether they respond differently to treatment in completed sepsis trials.
METHODS: We used clinical data and plasma biomarkers from two prospective sepsis cohorts, the Validating Acute Lung Injury biomarkers for Diagnosis (VALID) study (N=1140) and the Early Assessment of Renal and Lung Injury (EARLI) study (N=818), in latent class analysis (LCA) to identify the optimal number of classes in each cohort independently. We used validated models trained to classify ARDS phenotypes to evaluate concordance of sepsis and ARDS phenotypes. We applied these models retrospectively to the previously published Prospective Recombinant Human Activated Protein C Worldwide Evaluation in Severe Sepsis and Septic Shock (PROWESS-SHOCK) trial and Vasopressin and Septic Shock Trial (VASST) to assign phenotypes and evaluate heterogeneity of treatment effect.
FINDINGS: A two-class model best fit both VALID and EARLI (p<0·0001). In VALID, 804 (70·5%) of the 1140 patients were classified as hypoinflammatory and 336 (29·5%) as hyperinflammatory; in EARLI, 530 (64·8%) of 818 were hypoinflammatory and 288 (35·2%) hyperinflammatory. We observed higher plasma pro-inflammatory cytokines, more vasopressor use, more bacteraemia, lower protein C, and higher mortality in the hyperinflammatory than in the hypoinflammatory phenotype (p<0·0001 for all). Classifier models indicated strong concordance between sepsis phenotypes and previously identified ARDS phenotypes (area under the curve 0·87-0·96, depending on the model). Findings were similar excluding participants with both sepsis and ARDS. In PROWESS-SHOCK, 1142 (68·0%) of 1680 patients had the hypoinflammatory phenotype and 538 (32·0%) had the hyperinflammatory phenotype, and response to activated protein C differed by phenotype (p=0·0043). In VASST, phenotype proportions were similar to other cohorts; however, no treatment interaction with the type of vasopressor was observed (p=0·72).
INTERPRETATION: Molecular phenotypes previously identified in ARDS are also identifiable in multiple sepsis cohorts and respond differently to activated protein C. Molecular phenotypes could represent a treatable trait in critical illness beyond the patient's syndromic diagnosis.
FUNDING: US National Institutes of Health.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:11 |
|---|---|
| Enthalten in: |
The Lancet. Respiratory medicine - 11(2023), 11 vom: 15. Nov., Seite 965-974 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Sinha, Pratik [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Biomarkers |
|---|
| Anmerkungen: |
Date Completed 03.11.2023 Date Revised 06.03.2024 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1016/S2213-2600(23)00237-0 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM361314701 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM361314701 | ||
| 003 | DE-627 | ||
| 005 | 20240306232400.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/S2213-2600(23)00237-0 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1318.xml |
| 035 | |a (DE-627)NLM361314701 | ||
| 035 | |a (NLM)37633303 | ||
| 035 | |a (PII)S2213-2600(23)00237-0 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Sinha, Pratik |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Identifying molecular phenotypes in sepsis |b an analysis of two prospective observational cohorts and secondary analysis of two randomised controlled trials |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 03.11.2023 | ||
| 500 | |a Date Revised 06.03.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023 Elsevier Ltd. All rights reserved. | ||
| 520 | |a BACKGROUND: In sepsis and acute respiratory distress syndrome (ARDS), heterogeneity has contributed to difficulty identifying effective pharmacotherapies. In ARDS, two molecular phenotypes (hypoinflammatory and hyperinflammatory) have consistently been identified, with divergent outcomes and treatment responses. In this study, we sought to derive molecular phenotypes in critically ill adults with sepsis, determine their overlap with previous ARDS phenotypes, and evaluate whether they respond differently to treatment in completed sepsis trials | ||
| 520 | |a METHODS: We used clinical data and plasma biomarkers from two prospective sepsis cohorts, the Validating Acute Lung Injury biomarkers for Diagnosis (VALID) study (N=1140) and the Early Assessment of Renal and Lung Injury (EARLI) study (N=818), in latent class analysis (LCA) to identify the optimal number of classes in each cohort independently. We used validated models trained to classify ARDS phenotypes to evaluate concordance of sepsis and ARDS phenotypes. We applied these models retrospectively to the previously published Prospective Recombinant Human Activated Protein C Worldwide Evaluation in Severe Sepsis and Septic Shock (PROWESS-SHOCK) trial and Vasopressin and Septic Shock Trial (VASST) to assign phenotypes and evaluate heterogeneity of treatment effect | ||
| 520 | |a FINDINGS: A two-class model best fit both VALID and EARLI (p<0·0001). In VALID, 804 (70·5%) of the 1140 patients were classified as hypoinflammatory and 336 (29·5%) as hyperinflammatory; in EARLI, 530 (64·8%) of 818 were hypoinflammatory and 288 (35·2%) hyperinflammatory. We observed higher plasma pro-inflammatory cytokines, more vasopressor use, more bacteraemia, lower protein C, and higher mortality in the hyperinflammatory than in the hypoinflammatory phenotype (p<0·0001 for all). Classifier models indicated strong concordance between sepsis phenotypes and previously identified ARDS phenotypes (area under the curve 0·87-0·96, depending on the model). Findings were similar excluding participants with both sepsis and ARDS. In PROWESS-SHOCK, 1142 (68·0%) of 1680 patients had the hypoinflammatory phenotype and 538 (32·0%) had the hyperinflammatory phenotype, and response to activated protein C differed by phenotype (p=0·0043). In VASST, phenotype proportions were similar to other cohorts; however, no treatment interaction with the type of vasopressor was observed (p=0·72) | ||
| 520 | |a INTERPRETATION: Molecular phenotypes previously identified in ARDS are also identifiable in multiple sepsis cohorts and respond differently to activated protein C. Molecular phenotypes could represent a treatable trait in critical illness beyond the patient's syndromic diagnosis | ||
| 520 | |a FUNDING: US National Institutes of Health | ||
| 650 | 4 | |a Observational Study | |
| 650 | 4 | |a Journal Article | |
| 650 | 7 | |a Protein C |2 NLM | |
| 650 | 7 | |a Biomarkers |2 NLM | |
| 650 | 7 | |a Vasoconstrictor Agents |2 NLM | |
| 700 | 1 | |a Kerchberger, V Eric |e verfasserin |4 aut | |
| 700 | 1 | |a Willmore, Andrew |e verfasserin |4 aut | |
| 700 | 1 | |a Chambers, Julia |e verfasserin |4 aut | |
| 700 | 1 | |a Zhuo, Hanjing |e verfasserin |4 aut | |
| 700 | 1 | |a Abbott, Jason |e verfasserin |4 aut | |
| 700 | 1 | |a Jones, Chayse |e verfasserin |4 aut | |
| 700 | 1 | |a Wickersham, Nancy |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Nelson |e verfasserin |4 aut | |
| 700 | 1 | |a Neyton, Lucile |e verfasserin |4 aut | |
| 700 | 1 | |a Langelier, Charles R |e verfasserin |4 aut | |
| 700 | 1 | |a Mick, Eran |e verfasserin |4 aut | |
| 700 | 1 | |a He, June |e verfasserin |4 aut | |
| 700 | 1 | |a Jauregui, Alejandra |e verfasserin |4 aut | |
| 700 | 1 | |a Churpek, Matthew M |e verfasserin |4 aut | |
| 700 | 1 | |a Gomez, Antonio D |e verfasserin |4 aut | |
| 700 | 1 | |a Hendrickson, Carolyn M |e verfasserin |4 aut | |
| 700 | 1 | |a Kangelaris, Kirsten N |e verfasserin |4 aut | |
| 700 | 1 | |a Sarma, Aartik |e verfasserin |4 aut | |
| 700 | 1 | |a Leligdowicz, Aleksandra |e verfasserin |4 aut | |
| 700 | 1 | |a Delucchi, Kevin L |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Kathleen D |e verfasserin |4 aut | |
| 700 | 1 | |a Russell, James A |e verfasserin |4 aut | |
| 700 | 1 | |a Matthay, Michael A |e verfasserin |4 aut | |
| 700 | 1 | |a Walley, Keith R |e verfasserin |4 aut | |
| 700 | 1 | |a Ware, Lorraine B |e verfasserin |4 aut | |
| 700 | 1 | |a Calfee, Carolyn S |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t The Lancet. Respiratory medicine |d 2013 |g 11(2023), 11 vom: 15. Nov., Seite 965-974 |w (DE-627)NLM232005109 |x 2213-2619 |7 nnns |
| 773 | 1 | 8 | |g volume:11 |g year:2023 |g number:11 |g day:15 |g month:11 |g pages:965-974 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1016/S2213-2600(23)00237-0 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 11 |j 2023 |e 11 |b 15 |c 11 |h 965-974 | ||