Biomarkers in medicine最新文献

Purpose: After Cardiac Arrest (CA), serum biomarkers (SB) are released to the blood in response to brain damage and, therefore, may be helpful tools to predict neurological outcome. This systematic review aims at assessing the role of SB as neurological outcome indicators after pediatric CA.

Methods: A systematic literature search was performed in PubMed, Scopus, WebOfScience and Cochrane Library. All information retrieved from the selected articles was summarized in a data table.

Results: Eight studies, including a total of 539 patients, were analyzed. Neurological outcomes were assessed by using the Pediatric Cerebral Performance Category (PCPC) scale in all studies except one. Eleven serum biomarkers were evaluated, with higher concentrations observed in the unfavorable outcome group at various time points. However, only one study defined a specific cutoff value. The biomarkers with the highest predictive accuracy for neurological outcomes appear to be initial levels of IL-17 and CNFT, as well as NSE and S100B.

Conclusion: Following pediatric CA, SB may be helpful indicators of unfavorable neurological outcome, as they seem to appear in higher concentrations in this group. Further research is required to establish specific timepoints and cutoff values and to determine the implication of these findings in clinical practice.

Objective: To investigate the correlation between postoperative serum glial fibrillary acidic protein (GFAP) and 3-nitrotyrosine (3-NT) levels and neuronal injury severity in glioma patients.

Methods: 150 glioma patients were enrolled, with clinical baseline and pathological data recorded (age, sex, etc.). Neuronal injury was assessed using the National Institutes of Health Stroke Scale (NIHSS) postoperatively, categorizing patients into mild (NIHSS 1 ~ 4, n = 54) and moderate-to-severe (NIHSS ≥5, n = 96) groups. Serum GFAP and 3-NT levels were measured three days post-surgery via ELISA. Correlations with NIHSS were analyzed with Spearman's test. Patients were also stratified by median biomarker levels. Multivariate logistic regression identified severity risk factors. Receiver operating characteristic (ROC) curves evaluated diagnostic value.

Results: GFAP and 3-NT levels were higher in the moderate-to-severe group (p < 0.001) and positively correlated with NIHSS scores (GFAP: r = 0.552; 3-NT: r = 0.545). Higher biomarker levels were significantly associated with worse injury (p < 0.001). Both were independent risk factors for severity. Combining GFAP and 3-NT predicted severity significantly better than either alone (p < 0.001).

Conclusion: Postoperative serum GFAP and 3-NT levels correlate positively with neuronal injury severity in glioma patients. Their combination provides high diagnostic value for assessing postoperative injury severity.

Background: There are numerous controversies surrounding the diagnosis of matrix metalloproteinases (MMPs) in pancreatic cancer (PC). Consequently, this study conducts the first comprehensive meta-analysis evaluating the diagnostic performance of MMP family members in PC, highlight potential biomarkers, and investigate sources of heterogeneity.

Method: Articles on the MMP family and PC diagnosis were retrieved from PubMed and Web of Science. Diagnostic accuracy was assessed using sensitivity (SEN) and specificity (SPE). Threshold effects, heterogeneity (via meta-regression and subgroup analyses), and result robustness (via sensitivity analysis) were evaluated. Publication bias was examined using Deeks' funnel plot.

Result: This meta-analysis included 48 studies from 23 articles, covering 12 types of MMP. The aggregated SEN, SPE, and area under the curve (AUC) for MMPs in diagnosing PC ranged from 0.61 to 0.76, 0.66 to 0.78, and 0.7273 to 0.8840, respectively. Meta-regression identified sample type as a major contributor to heterogeneity, with tissue-based MMPs showing markedly superior diagnostic performance compared to serum or plasma-based assays. Overall, MMPs showed potential diagnostic value, but their accuracy remains moderate and requires further validation in larger, well-designed studies.

Conclusion: MMPs represent potential candidates for PC diagnosis, but current evidence is insufficient for clinical application, requiring further prospective studies.

Assessment of biomarkers through liquid biopsy, accompanied by low invasiveness, provides a more comprehensive analysis of the genetic profile of tumors, a deeper understanding of cancer mechanisms, the capacity for repeated testing over time, a short processing time, ease of obtaining, and economic benefits, making it easier to monitor diseases compared to tissue biopsy. Circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), exosomes, non-coding RNAs, and metabolites provide precise and timely strategies for managing cancer patients. The main challenges are the low concentration of analytes isolated from liquid biopsies, the development of assays with both high sensitivity and specificity, and the lack of clear and comprehensive guidelines for assays, which further complicate the standardization process. Combined detection, including both CTCs and ctDNA assessment in circular bodies, provides valuable information at different stages of the tumor, despite the heterogeneity of tumor cells, for prognosis, dynamic monitoring, and mutation detection. In addition, the combination of biofluid biomarkers and artificial intelligence can enhance the accuracy and efficiency of liquid biopsy, improve real-time monitoring of tumor procedures and treatment responses, and provide precision medicine. This review examines the challenges in standardizing biofluid assays and explores potential solutions to achieve more consistent clinical outcomes.

Aim: In metastatic Non-small cell lung cancer (NSCLC) with driver mutations, resistance mechanisms may limit treatment benefit, and their detection is expensive. The aim of this retrospective study was to investigate the usability of inflammatory-nutritional indices and hemoglobin, albumin, lymphocyte and platelet (HALP) scores for predicting survival in patients with metastatic NSCLCs with driver mutations undergoing first-line treatment with tyrosine kinase inhibitors (TKIs).

Patients & methods: Ninety-two patients using TKIs for metastatic disease with driver mutations were followed up in our center from December 2018 to May 2024. We retrospectively investigated the effects on progression-free survival (PFS) and overall survival (OS) by calculating inflammatory-nutritional indices and HALP scores using pre-treatment laboratory values.

Results: Higher plate-let-to-lymphocyte ratios (PLRs) were associated with shorter PFS, whereas a higher prognostic nutritional index (PNI) predicted longer PFS. Similarly, high HALP and PNI scores were significantly associated with longer OS, while lower platelet-to-lymphocyte ratio (PLR), systemic immune inflammatory index (SII) and systemic inflammation response index (SIRI) were linked to improved OS. Multivariate analysis identified only SII as an independent OS prognostic factor (OR = 7.182, p = 0.003).

Conclusions: HALP score, PLR, SII, PNI and SIRI may serve as potential prognostic biomarkers in NSCLC patients with driver mutations treated with first-line TKIs.

Aims: Pancreatic cancer has a very poor prognosis and is a leading cause of cancer-related deaths. Our aim is to investigate the presence of novel prognostic markers in pancreatic cancer that are easy to calculate, inexpensive, non-invasive, and do not cause a loss of time.

Methods: A total of 164 patients were included in the study. The demographic and clinical characteristics, laboratory findings, and radiological data of the patients were retrospectively reviewed using hospital records.

Results: Of the patients, 112 (68.3%) were male, and the mean age of all patients was 63.29 ± 12.5 years. The one-,two-,and five-year survival rates of the patients were determined to be 43.9% (n = 72), 29.3% (n = 48), and 21.3% (n = 35), respectively. During the 1-,2, and 5-year follow-ups, the absence of surgery, advanced disease stage, and elevated systemic inflammation response index (SIRI) were identified as independent risk factors for increased mortality in pancreatic cancer. SIRI was found to be a prognostic factor influencing both short- and long-term survival in pancreatic cancer.

Conclusion: We found that SIRI is a stronger prognostic factor than the NLR, PIV, and SII indices in predicting survival in pancreatic cancer. Monitoring SIRI in pancreatic cancer may provide insight into the status of the local immune response and systemic inflammation, and help in estimating patient survival.

Background: Patients with coronary artery disease (CAD) are at an increased risk of cognitive impairment, yet reliable noninvasive biomarkers for identifying high-risk individuals in this population remain scarce. This study aimed to investigate the association between the triglyceride-glucose (TyG) index and cognitive function in patients with CAD.

Methods: This study included 1163 patients with CAD who underwent cognitive function assessment. Multiple regression analyses were conducted to evaluate the relationship between the TyG index and cognitive function. Furthermore, receiver operating characteristic (ROC) curve analysis was conducted to determine the discriminatory ability of the TyG index in identifying patients with mild cognitive impairment (MCI).

Results: The TyG index was negatively correlated with Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) scores (r = -0.16, p < 0.001 and r = -0.33, p < 0.001, respectively). Specifically, when the TyG index was ≥8.72, higher values were associated with increased risk of MCI (OR: 3.69, 95% CI: 2.12, 6.58). ROC analysis revealed that the optimal cutoff value for the TyG index was 8.906 (specificity: 73.8%, sensitivity: 60.2%).

Conclusion: The TyG index is independently associated with cognitive function in patients with CAD, with elevated values associated with an increased risk of MCI.

Aim: A retrospective study was designed to compare the expression levels of TNF superfamily member 12 (TNFSF12), which encodes the protein TNF-like weak inducer of apoptosis (TWEAK), and CD163 in peripheral blood monocytes between rheumatoid arthritis (RA) patients and controls, and to correlate their expression with clinical parameters to investigate their potential association with RA.

Materials & methods: RT-qPCR method was used to determine gene expression of TNFSF12 and CD163 in patients with RA, ankylosing spondylitis (AS) and healthy controls (HC). ROC curve, Pearson correlation analysis, and western blot were used to access the diagnostic performance of TNFSF12/TWEAK and CD163, analyze their correlation with other clinical parameters in RA, and evaluate the protein expression of TWEAK and CD163 in RA.

Results: TNFSF12 and CD163 in RA patients were higher expressed compared with AS and HC; they were helpful to identify RA patients from controls, with area under ROC curve (AUC) being 0.813 and 0.826, respectively, and correlated with ESR and CRP. TWEAK and CD163 in monocytes from RA were significantly upregulated compared with controls.

Conclusion: TNFSF12 and CD163 gene higher expressed in RA patients and related with therapeutic response and inflammation status, can be used as reference index for RA diagnosis and disease monitoring.

Background: Infective endocarditis (IE) remains a life-threatening condition despite treatment advances. Early identification of high-risk patients is essential. The neutrophil percentage-to-albumin ratio (NPAR) is a novel inflammatory marker linked to poor outcomes in various diseases, but its prognostic value in IE remains unclear. This study aimed to investigate the association between NPAR and in-hospital mortality in patients with IE.

Methods: We retrospectively analyzed 263 patients diagnosed with IE between January 2009 and January 2024 at a tertiary care center. Clinical, laboratory, and echocardiographic data were collected. NPAR was calculated as (Neutrophil %/Albumin [g/dL]). Predictors of mortality were identified using LASSO-based logistic regression, and a nomogram was constructed to illustrate predictive performance.

Results: In-hospital mortality occurred in 59 patients (22.4%). NPAR was significantly higher among non-survivors (median: 0.335 vs. 0.228, p < 0.001). High NPAR ( >0.274) was independently associated with in-hospital mortality (OR: 6.70, 95% CI: 3.07-15.61, p < 0.001), along with large vegetation and diabetes mellitus. High NPAR showed good discriminative power (AUC = 0.72, 95% CI: 0.66-0.79, p < 0.001).

Conclusion: High NPAR was an independent predictor of in-hospital mortality in IE and may serve as a simple, cost-effective biomarker for early risk stratification.