Diagnostic Accuracy of Blood-based Biomarkers for Pancreatic Cancer: A Systematic Review and Meta-analysis

Abstract

Pancreatic ductal adenocarcinoma (PDAC) has a 5-year survival rate below 5%. CA19-9 is the most commonly used blood-based biomarker for PDAC in current clinical practice, despite having been shown repeatedly to be inaccurate and have poor diagnostic performance. This review aims to assess the reported diagnostic accuracy of all blood-based biomarkers investigated to date in PDAC, by directly comparing individual biomarkers and multi-biomarker panels, both containing CA19-9 and not (novel). A systematic review was conducted in accordance with PRISMA standards in July 2020. Individualised search strategies for three academic databases identified 5,885 studies between the years 1973-2020. After two rounds of screening, 250 studies were included. Data were extracted and assessed for bias. A multivariate three-level meta-analysis with subgroup moderators was run in R using AUC values as effect size. Based on this model, the pooled AUC value for all multi-biomarker panels (AUC=0.898, 95% CI:0.88-0.91) was significantly higher than all single biomarkers (AUC=0.803, 95% CI:0.78-0.83)(p<0.0001). The pooled AUC value for CA19-9 alone was significantly lower compared to the multi-biomarker panels containing CA19-9 (p<0.0001). For the novel biomarkers, the pooled AUC for single biomarkers was also significantly lower compared to multi-biomarker panels (p<0.0001). Novel biomarkers that have been repeatedly examined across the literature, such as TIMP-1, CEA and CA125, are highlighted as promising. These results suggest that CA19-9 may be best used as an addition to a panel of biomarkers rather than alone, and that multi-biomarker panels generate the most robust results in blood-based PDAC diagnosis.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

“…There are essential method development steps (Figure 4) to establish biomarkers for a disease, namely biomarker discovery and validation. A panel of biomarkers may be used for better performance in terms of diagnostic accuracy 159–163 . In the following sections, selected research articles from the most popular subject areas of 2022 will be briefly discussed: oncology, metabolic diseases (e.g.…”

The Potent G-Quadruplex-Binding Compound QN-302 Downregulates S100P Gene Expression in Cells and in an In Vivo Model of Pancreatic Cancer

“…Monitoring of S100P levels may also be a useful predictor of tumor response to treatment with the experimental drug QN-302. The potential advantages of S100P as a biomarker in PDAC diagnosis have been extensively documented [ 33 , 34 , 35 , 36 , 37 , 39 ], comparing favorably to CA19-9 antigen, which can produce both false positive and false negative indications of disease [ 44 , 45 ].…”

“…The complete gene sequence contains 4493 nucleotides. The program QGRS Mapper [ 45 ] ( ), accessed on 12 June 2022 was used to locate putative quadruplex sequences in both sense (coding) and antisense (template) strands of the complete S100P gene. A cut-off of a maximum loop size of 12 nucleotides was used in the searches.…”

Investigating the Effects of Olaparib on the Susceptibility of Glioblastoma Multiforme Tumour Cells to Natural Killer Cell-Mediated Responses

“…As these copy number values were generated via high-throughput sequencing methods, it was not necessary to control for batch effects across these data. Indeed, a recent systematic review and meta-analysis of 250 studies showed that the variability introduced by patient-to-patient comparisons is much larger than any variability that could be introduced by the different high-throughput platforms used across these studies [ 43 ]. Significant differences in the survival between the quartiles are noted where the Logrank test p -value <0.05.…”