Economical and easily detectable markers of digestive tumors: platelet parameters

A novel model for predicting immunotherapy response and prognosis in NSCLC patients

BACKGROUND

How to screen beneficiary populations has always been a clinical challenge in the treatment of non-small-cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs). Routine blood tests, due to their advantages of being minimally invasive, convenient, and capable of reflecting tumor dynamic changes, have potential value in predicting the efficacy of ICIs treatment. However, there are few models based on routine blood tests to predict the efficacy and prognosis of immunotherapy.

METHODS

Patients were randomly divided into training cohort and validation cohort at a ratio of 2:1. The random forest algorithm was applied to select important variables based on routine blood tests, and a random forest (RF) model was constructed to predict the efficacy and prognosis of ICIs treatment. For efficacy prediction, we assessed receiver operating characteristic (ROC) curves, decision curve analysis (DCA) curves, clinical impact curve (CIC), integrated discrimination improvement (IDI) and net reclassification improvement (NRI) compared with the Nomogram model. For prognostic evaluation, we utilized the C-index and time-dependent C-index compared with the Nomogram model, Lung Immune Prognostic Index (LIPI) and Systemic Inflammatory Score (SIS). Patients were classified into high-risk and low-risk groups based on RF model, then the Kaplan-Meier (K-M) curve was used to analyze the differences in progression-free survival (PFS) and overall survival (OS) of patients between the two groups.

RESULTS

The RF model incorporated RDW-SD, MCV, PDW, CD3+CD8+, APTT, P-LCR, Ca, MPV, CD4+/CD8+ ratio, and AST. In the training and validation cohorts, the RF model exhibited an AUC of 1.000 and 0.864, and sensitivity/specificity of (100.0%, 100.0%) and (70.3%, 93.5%), respectively, which had superior performance compared to the Nomogram model (training cohort: AUC = 0.531, validation cohort: AUC = 0.552). The C-index of the RF model was 0.803 in the training cohort and 0.712 in the validation cohort, which was significantly higher than Nomogram model, LIPI and SIS. K-M survival curves revealed that patients in the high-risk group had significantly shorter PFS/OS than those in the low-risk group.

CONCLUSIONS

In this study, we developed a novel model (RF model) to predict the response to immunotherapy and prognosis in NSCLC patients. The RF model demonstrated better predictive performance for immunotherapy responses than the Nomogram model. Moreover, when predicting the prognosis of immunotherapy, it outperformed the Nomogram model, LIPI, and SIS.

Association of mean platelet volume/lymphocyte ratio with inflammation in non-dialysis patients with chronic kidney disease stages 1-4: A retrospective study

OBJECTIVE

The mean platelet volume/ratio (MPVLR) is recognized as a novel marker of inflammation. We evaluated whether the MPVLR is associated with inflammation in non-dialysis patients with chronic kidney disease (CKD) stages 1-4.

METHODS

A total of 402 non-dialysis patients with CKD stages 1-4 were included. The indicators of hematological, renal function (urea, serum creatinine [Scr], estimated glomerular filtration rate [eGFR], and urine albumin to creatinine ratio [ACR]) and the markers of inflammation (high-sensitivity C-reactive protein [hsCRP] and fibrinogen [FIB]) were recorded. The MPVLR values at different CKD stages were analyzed. Next, based on the absence (hsCRP level < 5 mg/L) and presence (hsCRP level > 5 mg/L) of inflammation, the patients were categorized, and the differences in indices between the two groups were observed. The patients were divided into two groups based on the median MPVLR value (6.39) at admission. The laboratory indices of patients with CKD were compared. Simultaneously, a correlation analysis was performed to identify the association between the MPVLR and each parameter. A binary logistic regression analysis was performed to test whether the MPVLR was associated independently with the presence of inflammation in non-dialysis patients with CKD. The receiver operating characteristic (ROC) curve was used to analyzed diagnostic performance of the MPVLR in evaluating the inflammation of non-dialysis patients with CKD stages 1-4.

RESULTS

The MPVLR was higher in patients with CKD stages 3-4 than in those with CKD stages 1 and 2. Significant differences in urea, Scr, eGFR, ACR, lymphocyte (LYM), red blood cell (RBC), hemoglobin (HGB), RBC distribution width (RDW-CV), MPVLR, and FIB values were observed between the groups with and without inflammation. The patients with a higher MPVLR had higher urea, Scr, ACR, WBC, neutrophils (NEU), RDW-CV, platelet distribution width (PDW), mean platelet volume (MPV), and hsCRP values and lower eGFR, LYM, RBC, HGB, and platelet (PLT) values. The MPVLR showed a positive correlation with age, urea, Scr, WBC, NEU, RDW-CV, PDW, MPV, and hsCRP values and a negative correlation with the eGFR, LYM, RBC, HGB, and PLT values. A logistic analysis revealed that the MPVLR was associated independently with the presence of inflammation in non-dialysis patients with CKD, after adjustment for the confounding factors (odds ratio = 1.020; P = 0.024). Furthermore, MPVLR exhibited a modest diagnostic performance for the assessment of inflammation in non-dialysis patients with CKD stages 1-4, with an area under the curve (AUC) of 0.706, and the sensitivity, specificity being 46.2% and 83.2%, respectively.

CONCLUSIONS

The MPVLR was associated independently with the presence of inflammation in non-dialysis patients with CKD and may be useful for monitoring inflammation.

Mean platelet volume to lymphocyte ratio and platelet distribution width to lymphocyte ratio in Iraqi patients diagnosed with systemic lupus erythematosus

Introduction

The mean platelet volume to lymphocyte ratio (MPVLR) and platelet distribution width to lymphocyte ratio (PDWLR) have the potential to serve as markers of inflammation which may indicate disease activity. The mean platelet volume to lymphocyte ratio and PDWLR were assessed in patients with systemic lupus erythematosus (SLE) in this study.

Material and methods

Sixty-two patients with systemic lupus erythematosus and 79 controls who were age and gender matched were included. Their sociodemographic information, as well as disease activity scores based on the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI), disease duration, current medications, lymphocytes, platelets, platelet distribution width (PDW), and mean platelet volume (MPV), anti-nuclear antibody (ANA), anti-double stranded deoxyribonucleic acid (anti-dsDNA), and complement components (C3, C4) were recorded. The correlations of MPVLR and PDWLR with disease activity and some laboratory parameters were analyzed.

Results

Lupus patients had significantly higher median (interquartile range) values for MPVLR and PDWLR than controls (5.69 [1.16-23.67] vs. 4.40 [2.78-11.93], p = 0.009) and 10.51 (2.87-79.37) vs. 5.21 (2.88-14.66), p < 0.001] respectively. According to the ROC curve, > 7.53 was the best PDWLR cut-off value for predicting SLE with a sensitivity of 71%, a specificity of 87% and an accuracy of 82.6%, whereas the optimum MPVLR cut-off value was > 6.46 with a sensitivity of 45.2%, a specificity of 88.9% and an accuracy of 76.8%. In addition, MPVLR had a significant positive correlation with SLEDAI (r = 0.34, p = 0.008). However, there was no significant correlation between PDWLR and SLEDAI (r = 0.23, p = 0.067). Furthermore, PDWLR had a significant positive correlation with PDW (r = 0.482, p < 0.001), while MPVLR had a significant negative correlation with C3 level (r = -0.260, p = 0.042). Both PDWLR and MPVLR were positively correlated with nephritis (r = 0.388, p = 0.002; r = 0.246, p = 0.038, respectively).

Conclusions

The platelet distribution width to lymphocyte ratio can be considered as an assisting biomarker in the diagnosis of SLE with the other clinical and serological parameters. The mean platelet volume to lymphocyte ratio may be used in the evaluation of disease activity in SLE patients.

Serum Anti-BRAT1 is a Common Molecular Biomarker for Gastrointestinal Cancers and Atherosclerosis

Atherosclerosis (AS) and cancers are major global causes of mortality and morbidity. They also share common modifiable pathogenesis risk factors. As the same strategies used to predict AS could also detect certain cancers, we sought novel serum antibody biomarkers of cancers in atherosclerotic sera sampled by liquid biopsy. Using serological antigen identification by cDNA expression cloning (SEREX) and western blot, we screened and detected the antigens BRCA1-Associated ATM Activator 1 (BRAT1) and WD Repeat Domain 1 (WDR1) in the sera of patients with transient ischemic attacks (TIA). Amplified luminescence proximity homogeneous assay-linked immunosorbent assay (AlphaLISA) established the upregulation of serum BRAT1 antibody (BRAT1-Abs) and WDR1 antibody (WDR1-Abs) in patients with AS-related diseases compared with healthy subjects. ROC and Spearman’s correlation analyses showed that BRAT1-Abs and WDR1-Abs could detect AS-related diseases. Thus, serum BRAT1-Abs and WDR1-Abs are potential AS biomarkers. We used online databases and AlphaLISA detection to compare relative antigen and serum antibody expression and found high BRAT1 and BRAT1-Abs expression in patients with GI cancers. Significant increases (> 0.6) in the AUC for BRAT1-Ab vs. esophageal squamous cell carcinoma (ESCC), gastric cancer, and colorectal cancer suggested that BRAT1-Ab exhibited better predictive potential for GI cancers than WDR1-Ab. There was no significant difference in overall survival (OS) between BRAT1-Ab groups (P = 0.12). Nevertheless, a log-rank test disclosed that the highest serum BRAT1-Ab levels were associated with poor ESCC prognosis at 5–60 weeks post-surgery. We validated the foregoing conclusions by comparing serum BRAT1-Ab and WDR1-Ab levels based on the clinicopathological characteristics of the patients with ESCC. Multiple statistical approaches established a correlation between serum BRAT1-Ab levels and platelet counts. BRAT1-Ab upregulation may enable early detection of AS and GI cancers and facilitate the delay of disease progression. Thus, BRAT1-Ab is a potential antibody biomarker for the diagnosis of AS and GI cancers and strongly supports the routine clinical application of liquid biopsy in chronic disease detection and diagnosis.