Biomarkers troponin and procalcitonin in addition to CRB-65 enhance risk stratification in patients with community-acquired pneumonia

Abstract

Background: Community-acquired pneumonia (CAP) remains a leading cause of infectious disease mortality globally, necessitating intensive care unit (ICU) admission for ∼10% of hospitalised patients. Accurate prediction of disease severity facilitates timely therapeutic interventions.

Methods: Our study aimed to enhance the predictive capacity of the clinical CRB-65 score by evaluating eight candidate biomarkers: troponin T high-sensitive (TnT-hs), procalcitonin (PCT), N-terminal pro-brain natriuretic peptide, angiopoietin-2, copeptin, endothelin-1, lipocalin-2 and mid-regional pro-adrenomedullin. We utilised a machine-learning approach on 800 samples from the German CAPNETZ network (competence network for CAP) to refine risk prediction models combining these biomarkers with the CRB-65 score regarding our defined end-point: death or ICU admission during the current CAP episode within 28 days after study inclusion.

Results: Elevated levels of biomarkers were associated with the end-point. TnT-hs exhibited the highest predictive performance among individual features (area under the receiver operating characteristic curve, AUC=0.74), followed closely by PCT (AUC=0.73). Combining biomarkers with the CRB-65 score significantly improved prediction accuracy. The combined model of CRB-65, TnT-hs and PCT demonstrated the best balance between high predictive value and parsimony, with an AUC of 0.77 (95% CI: 0.72-0.82), while CRB-65 alone achieved an AUC of 0.67 (95% CI: 0.64-0.73).

Conclusion: Our findings suggest that augmenting the CRB-65 score with TnT-hs and PCT enhances the prediction of death or ICU admission in hospitalised CAP patients. Validation of this improved risk score in additional CAP cohorts and prospective clinical studies is warranted to assess its broad clinical utility.

FIGURE 1

a) Receiver operating characteristic curves of eight biomarkers, of CRB-65 and of relaxed LASSO multivariable model (including CRB-65, troponin T high-sensitive (TnT-hs) and procalcitonin (PCT)) for predicting the primary end-point, intensive care unit (ICU) admission or death within 28 days. The corresponding area under the curve values are given in the key. b) Decision curve analysis: the standardised net benefit of the relaxed LASSO model and of CRB-65 alone at different risk thresholds. Thresholds correspond to predicted probabilities of reaching a clinical end-point. For clinical application of such a prediction model, a threshold for the estimated probability of the unfavourable outcome (reaching the end-point) needs to be set, at which the physician should decide to escalate treatment (e.g. ICU admission). Extreme decision scenarios correspond to treating all patients and treating no patients (x-axis). Cut-offs between 0.05 and 0.25 result in the highest standardised net benefits. NT-proBNP: N-terminal pro-brain natriuretic peptide; ET-1: endothelin-1; MR-proADM: mid-regional pro-adrenomedullin.

FIGURE 2

Subgroup analysis comparing performance of our prediction model between different risk groups of patients. For risk factor age, minimum p-value of the three pairwise group comparisons is given. Significant differences were only observed for COPD where prediction performance was significantly higher in the group of patients without COPD.