Abstract
Purpose Novel biomarkers to better predict outcome and select the best therapeutic strategy for the individual patient are necessary for pancreatic ductal adenocarcinoma (PDAC). Methods Using a panel assay, multiple biomarkers (IFN-gamma, IL-10, IL-6, IL-8, TNF-alpha, CEA, CA 19-9, CYFRA 21-1, HE4, PD-1 and PD-L1 levels) were measured in serum samples of 162 patients with resected, locally advanced and metastatic PDAC in this retrospective single-center study. Optimal cut-off values to differentiate prognostic subgroups with significantly different overall survival (OS) were determined by receiver operator characteristics and Youden Index analysis. Marker levels were assessed before the start of chemotherapy and correlated with OS by univariate and multivariate Cox analysis. Results Median OS for resected patients was 28.2 months, for locally advanced patients 17.9 months and for patients with metastatic disease 8.6 months. CYFRA 21-1 and IL-8 discriminated metastatic from locally advanced patients best (AUC 0.85 and AUC 0.81, respectively). In univariate analyses, multiple markers showed prognostic relevance in the various subgroups. However, multivariate Cox models comprised only CYFRA 21-1 in the resected group (HR 1.37, p = 0.015), IL-10 in locally advanced PDAC (HR 10.01, p = 0.014), as well as CYFRA 21-1 and CA 19-9 in metastatic PDAC (p = 0.008 and p = 0.010) as an independent prognostic marker for overall survival. Conclusion IL-10 levels may have independent prognostic value in locally advanced PDAC, whereas CYFRA 21-1 levels are prognostic after PDAC surgery. CYFRA 21-1 and IL-8 have been identified to best discriminate metastatic from locally advanced patients.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-106391-9 |
ISSN: | 0171-5216 |
Sprache: | Englisch |
Dokumenten ID: | 106391 |
Datum der Veröffentlichung auf Open Access LMU: | 11. Sep. 2023, 13:38 |
Letzte Änderungen: | 19. Sep. 2023, 19:30 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 491502892 |