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. 2022 Jan 10;8(1):00489-2021.
doi: 10.1183/23120541.00489-2021. eCollection 2022 Jan.

Community-acquired pneumonia subgroups and differential response to corticosteroids: a secondary analysis of controlled studies

Affiliations

Community-acquired pneumonia subgroups and differential response to corticosteroids: a secondary analysis of controlled studies

Esther Wittermans et al. ERJ Open Res. .

Abstract

Background: Latent class analysis (LCA) has identified subgroups with meaningful treatment implications in acute respiratory distress syndrome. We performed a secondary analysis of three studies to assess whether LCA can identify clinically distinct subgroups in community-acquired pneumonia (CAP) and whether the treatment effect of adjunctive corticosteroids differs between subgroups.

Methods: LCA was performed on baseline clinical and biomarker data from the Ovidius trial (n=304) and the Steroids in Pneumonia (STEP) trial (n=727), both randomised controlled trials investigating adjunctive corticosteroid treatment in CAP, and the observational TripleP cohort (n=201). Analyses were conducted independently in two cohorts (Ovidius-TripleP combined and the STEP trial). In both cohorts, differences in clinical outcomes and response to adjunctive corticosteroid treatment were examined between subgroups identified through LCA.

Results: A two-class model fitted both cohorts best. Class 2 patients had more signs of systemic inflammation compared to class 1. In both cohorts, length of stay was longer and in-hospital mortality rate was higher in class 2. In the Ovidius trial, corticosteroids reduced the median length of stay in class 2 (6.5 versus 9.5 days) but not in class 1 (p-value for interaction=0.02). In the STEP trial, there was no significant interaction for length of stay. We found no significant interaction between class assignment and adjunctive corticosteroid treatment for secondary outcomes.

Conclusions: In two independent cohorts, LCA identified two classes of CAP patients with different clinical characteristics and outcomes. Given the different response to adjunctive corticosteroids in the Ovidius trial, LCA might provide a useful basis to improve patient selection for future trials.

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Conflict of interest statement

Conflict of interest: E. Wittermans has nothing to disclose. Conflict of interest: P.A. van der Zee has nothing to disclose. Conflict of interest: H. Qi has nothing to disclose. Conflict of interest: E.M.W. van de Garde has nothing to disclose. Conflict of interest: C.A. Blum reports grants from the Helmut Horten Foundation, Switzerland, and Novo Nordisk, outside the submitted work. Conflict of interest: M. Christ-Crain has nothing to disclose. Conflict of interest: D. Gommers reports speaker fees and travel expenses from Drager and Maquet, personal fees and other support for a medical advisory board from 2009 to 2012 from GE Healthcare, and personal fees and other support for a medical advisory board from 2015 to 2018 from Novalung, outside the submitted work. Conflict of interest: J.C. Grutters has nothing to disclose. Conflict of interest: G.P. Voorn has nothing to disclose. Conflict of interest: W.J.W. Bos has nothing to disclose. Conflict of interest: H. Endeman has nothing to disclose.

Figures

FIGURE. 1
FIGURE. 1
Continuous variables (standardised) by class assignment for the a) Ovidius–TripleP cohort and b) Steroids in Pneumonia (STEP) cohort. Differences between the standardised values of each variable by class (y-axis) for the variable shown on the x-axis. The variables are sorted by degree of separation between classes: from the maximum positive separation on the left (where the standardised value of class 2 is higher than the standardised value of class 1) to the maximum negative separation on the right (where the standardised value of class 2 to is lower than the standardised value of class 1). The crossover of the lines indicates that the standardised value for this variable was the same for classes 1 and 2 (i.e. no difference between class 1 and class 2 for this variable). Therefore, variables near the intersection of both lines are similar in both classes and thus are not class-defining. The method of variable standardisation is described in the methods section. If the standardised value of a certain variable is 1 for a class, it means that the mean value for that variable within that class was one standard deviation higher than the mean value for that variable in the whole cohort. LAT: alanine transaminase; ASAT: aspartate transaminase; G-CSF: granulocyte colony-stimulating factor; IFN: interferon; IL: interleukin; MCP: monocyte chemoattractant protein; MIP:macrophage inflammatory protein; PaCO2: arterial carbon dioxide tension; PaO2: arterial oxygen tension; PSI: pneumonia severity index; TNF: tumour necrosis factor.

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