Biomarkers in Diagnosis of Sepsis and Infection: A Systematic Review and Bayesian Network Meta-Analysis

Background: Sepsis is estimated to affect over 30 million people worldwide and to result in 6 million deaths every year. Presepsin has demonstrated a promising diagnostic value for sepsis. Nevertheless, conflicting results and insufficient evidence comparing performance between presepsin and other biomarkers exists. Methods: We conducted a systematic review and synthesised both direct and indirect evidence by using network meta-analyses with bivariate hierarchical random-effects arm-based model in a Bayesian framework. We searched in PubMed, EMBASE, and Scopus from their inception to May 2019 for studies assessing the diagnostic performance of biomarkers. We applied the Quality Assessment of Diagnostic Accuracy Studies-2 criteria to assessing the risk of bias, investigated heterogeneity using Bayesian network meta-regression models, and estimated optimal adjusted cutoff values for each included biomarker. Findings: We identified 336 unique studies and included 134 studies representing 20,564 patients for evidence synthesis. Among the seven most-studied biomarkers, presepsin displayed the significantly better pooled sensitivities than procalcitonin to detect infection and sepsis (0·85 and 0·83; 95% credible interval [CrI]: 0·79-0·89 and 0·77-0·88; relative sensitivity 1·13 and 1·10, 95% CrI: 1·04-1·20 and 1·01-1·18). However, CD64 showed the significantly better pooled specificities than presepsin in detecting infection and sepsis (0·87 and 0·99; 95% CrI: 0·81-0·92 and 0·92-1·00, relative specificity 1·19 and 1·49, 95% CrI: 1·07-1·34 and 1·31-1·70). After adjusting for study quality, study populations, types of specimen and sponsorship, CD64 showed the best pooled sensitivities and specificities. We suggested 600-700 pg/mL as the optimal cutoffs for detecting infection for presepsin. Interpretation: CD64 performed the best in detecting both infection and sepsis. Further investigations will be needed to assess the potential risks of biases and the use of post-hoc cutoffs. Funding Statement: The study was supported by the Ministry of Science and Technology and Chang Gung Memorial Hospital in Taiwan (MOST 107-2314-B-182 -052 -MY2, CMRPG2H0322, CMRPG2H0312). Declaration of Interests: The authors declare that they have no conflicts of interest. Ethics Approval Statement: (PROSPERO number: CRD42018086545). This meta-analysis study is exempt from ethics approval, since the study authors were collecting and synthesising data from previous clinical studies in which informed consent has already been obtained by the investigators.