Prevalence of biofilms in Candida spp. bloodstream infections: A meta-analysis

Abstract

Context: Candida-related infections are nowadays a serious Public Health Problem emerging multidrug-resistant strains. Candida biofilm also leads bloodstream infections to invasive systemic infections.

Objective: The present meta-analysis aimed to analyze Candida biofilm rate, type, and antifungal resistance among hospitalized patients between 1995 and 2020.

Data sources: Web of Science, Scopus, PubMed, and Google Scholar databases were searched for English papers using the following medical subject heading terms (MESH): "invasive candidiasis"; "bloodstream infections"; "biofilm formation"; "biofilm-related infections"; "mortality"; and "prevalence".

Study selection: The major inclusion criteria included reporting the rate of biofilm formation and the prevalence of biofilm-related to Candida species, including observational studies (more exactly, cohort, retrospective, and case-control studies). Furthermore, data regarding the mortality rate, the geographical location of the study set, and the use of anti-fungal agents in clinical isolates were also extracted from the studies.

Data extraction: Independent extraction of articles by 2 authors using predefined data fields, including study quality indicators.

Data synthesis: A total of 31 studies from publicly available databases met our inclusion criteria. The biofilm formation in the data set varied greatly from 16 to 100% in blood samples. Most of the studies belonged to Europe (17/31) and Asia (9/31). Forest plot showed a pooled rate of biofilm formation of 80.0% (CI: 67-90), with high heterogeneity (Q = 2567.45, I2 = 98.83, τ2 = 0.150) in random effects model (p < 0.001). The funnel plot and Egger's linear regression test failed to find publication bias (p = 0.896). The mortality rate in Candida-related bloodstream infections was 37.9% of which 70.0% were from biofilm-associated infections. Furthermore, Candida isolates were also characterized in low, intermediate, or high biofilm formers through their level of biofilm mass (crystal violet staining or XTT assays) after a 24h growth. When comparing between countries, statistical differences were obtained (p = 0.0074), showing the lower and higher biofilm prevalence values in Italy and Spain, respectively. The prevalence of low, intermediate, and high biofilms were 36.2, 18.9, and 35.0% (p < 0.0001), respectively. C. tropicalis was the prevalent species in high biofilm formation (67.5%) showing statistically significant differences when compared to other Candida species, except for C. krusei and C. glabrata. Finally, the rates of antifungal resistance to fluconazole, voriconazole, and caspofungin related to biofilm were 70.5, 67.9 and 72.8% (p < 0.001), respectively.

Conclusions: Early detection of biofilms and a better characterization of Candida spp. bloodstream infections should be considered, which eventually will help preserve public health resources and ultimately diminish mortality among patients.

Fig 1. Prisma flow chart of included and excluded studies of the selection process.

Fig 2. Forest plot of the meta-analysis of the prevalence of biofilm formation in Candida spp. isolated from blood clinical samples.

Fig 3. Funnel plot of the meta-analysis on the biofilm formation rate in Candida spp. isolated from blood clinical samples.

Studies are represented by a point. The X-axis represents the effect size (biofilm prevalence), and the Y-axis shows the standard error. Despite some asymmetry revealed by the funnel plot in the data set, Egger’s test failed to show publication bias (p = 0.896).