Methods
Study design
We conducted a systematic review and meta-analysis following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.11 We registered this study in PROSPERO, an international prospective register for systematic reviews (CRD42020188680).
We focused our review on CRP, ESR, WBC, and PCT to understand the potential use of these biomarkers in clinical settings in which reference standard diagnostic testing may be limited. Though other biomarkers, including proadrenomedullin and various serum interleukins, have also been used to assess the presence of bacterial illness against reference standards,12 13 these are not currently routinely accessible in many settings, both in HICs and particularly in LMICs, so were excluded from the analysis.
Patient and public involvement statement
The development of the research question was informed by the high disease burden of neonatal sepsis. Patients were not involved in the design, recruitment, or conduct of the study, nor were they advisers in this study. Results of this study have been made publicly available through publication.
Data sources
We searched the Medline, EMBASE, DARE, CINAHL, and Babelmesh databases on 12 February 2021 and conducted an updated search on 29 August 2022. We extracted articles that were included in each of these databases from their inception to 29 August 2022. The search terms used to identify studies that focused on the use of the four biomarkers of interest are included in online supplemental appendix 1. Our search was limited to articles published in English, Spanish, French, German, Dutch, and Arabic as members of our team were fluent in these languages.
Inclusion and exclusion criteria
We included studies that met the following criteria (1) were peer-reviewed, original research articles published from the inception of each database to 29 August 2022, (2) evaluated the use of one of the four biomarkers of interest in the diagnosis of an infectious disease, (3) included participants aged 0–18 years and (4) included a control group that did not test positive with a reference standard as a comparison for the diagnostic performance of the biomarkers evaluated. Initially, our search was not restricted to specific diseases. However, post hoc, we decided to focus our analysis on neonatal sepsis as there were at least 20 studies that met our inclusion criteria, and it contributes to a large burden of childhood morbidity and mortality globally. There were >20 studies that reported the test characteristics of the included biomarkers for pneumonia. However, these were not included in our manuscript because those studies did not differentiate viral from bacterial disease.
We excluded studies that met any of the following criteria: (1) articles that were not published in English, Spanish, French, German, Dutch, or Arabic, (2) abstracts without full text, (3) articles that only included highly medicalised populations, (4) articles reporting only mean or median values for biomarkers, (5) articles that did not evaluate children separately if adults aged >18 years were included, (6) articles that only assessed changes in biomarkers during treatment, and (7) case reports, editorials, study protocols, review articles, systematic reviews, and meta-analyses. We reviewed systematic reviews and meta-analyses for other articles reporting primary data our initial query did not capture. Any potential articles identified therein were included if they met inclusion criteria.
Definitions
We used the definitions used for our outcome of neonatal sepsis as reported in the included studies (ie, either positive blood culture or clinical sepsis).14 Study countries were defined as low- middle-income and high-income according to the World Bank definitions.15
Data extraction and risk of bias assessment
Using the results from our database query, we uploaded all articles into the platform Covidence (Melbourne, Australia) to screen article titles and abstracts for potential inclusion. Two reviewers independently screened articles in two rounds. Each reviewer was blinded to the other reviewer’s screening. The first round included a review of all abstracts for the presence of exclusion criteria. All article titles and abstracts that resulted in disagreement between two independent reviewers were reviewed by an arbiter (CAR) to assess inclusion or exclusion. The second round included a review of article full texts for those remaining after titles and abstracts were reviewed. The full text of articles in Spanish, French, German, Dutch, or Arabic were screened and reviewed by a team member who was fluent in the respective language.
We reviewed the full text of each article that was included after the initial phase of article title and abstract review. We extracted the following information from each included article: study location (eg, outpatient, emergency department, inpatient such as neonatal intensive care unit), study design, study country, included patient ages, disease studied, biomarker(s) evaluated, reference standard and study inclusion and exclusion criteria. Biomarkers were considered diagnostic if they were used to distinguish an infection in a child from healthy controls or children who had negative reference standard testing. We extracted the reported number of true negatives (TNs), true positives (TPs), false negatives (FNs), and false positives (FPs) based on reported biomarker cut points and reference standard testing. For studies that did not report these numbers, we extracted the reported sensitivity, specificity, positive and negative likelihood ratios wherever possible and emailed the corresponding author to request additional data. If there was no answer to an initial email request, a second email was sent 2 weeks later.
The risk of bias of the included studies was assessed using the Quality Assessment of Studies for Diagnostic Accuracy Included in Systematic Reviews-2 (QUADAS-2) tool, which is designed to assess bias and applicability concerns for diagnostic studies.16
Statistical analyses
If a study did not provide the TN, TP, FN, and FP but provided sensitivity, specificity, and the total population number, and corresponding authors did not respond to our request, we calculated the 2×2 table numbers rounded to the nearest integer. We reported the aggregate performance of each biomarker cut point with up to two reference standards in the same studies (eg, blood culture or clinical sepsis) for neonatal sepsis and alone in cases in which ≥3 studies reported the same cut point.
Many of the studies that met our inclusion criteria used different cut points for their respective biomarker. We evaluated each biomarker cut point used by ≥3 studies individually using a bivariate model created by Reitsma et al through the reitsma function in the R package Mada.17 18 The bivariate analysis method created by Reitsma et al produces summary estimates of sensitivity and specificity that include 95% CIs that account for heterogeneity. We also calculated Holling’s sample size adjusted measure for heterogeneity (I2) which was developed for use in bivariate meta-analyses of diagnostic accuracy.19 We calculated the sensitivity, specificity, and the area under the curve (AUC) along with their respective 95% CIs, for each disease and biomarker combination. 95% CIs for AUCs were calculated through bootstrapping with 2000 resamplings via the AUC boot function in the dmetatools R package created by Noma H.20 We calculated and reported the highest Youden’s index for each biomarker and disease combination. Based on published standards, we used the following scale to qualify the discriminatory value of each score: AUC ≥0.90 for ‘excellent discrimination’, AUC 0.80–0.89 for ‘good discrimination’, AUC 0.70–0.79 for ‘minimal discrimination’, and ‘poor discrimination’ for AUC <0.70.21–23 We subanalysed all results by study country income group according to the World Bank and reference standard if there were ≥3 studies using the same cut point within that subgroup. All statistical analyses were conducted using SAS V.9.4 and R V.4.0.3 (R Foundation for Statistical Computing, Vienna, Austria).