Predictive value of preoperative platelet-to-albumin ratio and apolipoprotein B-to-apolipoprotein A1 ratio for osteosarcoma in children and adolescents: a retrospective study of 118 cases

Prediction of Osteoporotic Hip Fracture Outcome: Comparative Accuracy of 27 Immune-Inflammatory-Metabolic Markers and Related Conceptual Issues

Objectives: This study, based on the concept of immuno-inflammatory-metabolic (IIM) dysregulation, investigated and compared the prognostic impact of 27 indices at admission for prediction of postoperative myocardial injury (PMI) and/or hospital death in hip fracture (HF) patients. Methods: In consecutive HF patient (n = 1273, mean age 82.9 ± 8.7 years, 73.5% females) demographics, medical history, laboratory parameters, and outcomes were recorded prospectively. Multiple logistic regression and receiver-operating characteristic analyses (the area under the curve, AUC) were used to establish the predictive role for each biomarker. Results: Among 27 IIM biomarkers, 10 indices were significantly associated with development of PMI and 16 were indicative of a fatal outcome; in the subset of patients aged >80 years with ischaemic heart disease (IHD, the highest risk group: 90.2% of all deaths), the corresponding figures were 26 and 20. In the latter group, the five strongest preoperative predictors for PMI were anaemia (AUC 0.7879), monocyte/eosinophil ratio > 13.0 (AUC 0.7814), neutrophil/lymphocyte ratio > 7.5 (AUC 0.7784), eosinophil count < 1.1 × 109/L (AUC 0.7780), and neutrophil/albumin × 10 > 2.4 (AUC 0.7732); additionally, sensitivity was 83.1-75.4% and specificity was 82.1-75.0%. The highest predictors of in-hospital death were platelet/lymphocyte ratio > 280.0 (AUC 0.8390), lymphocyte/monocyte ratio < 1.1 (AUC 0.8375), albumin < 33 g/L (AUC 0.7889), red cell distribution width > 14.5% (AUC 0.7739), and anaemia (AUC 0.7604), sensitivity 88.2% and above, and specificity 85.1-79.3%. Internal validation confirmed the predictive value of the models. Conclusions: Comparison of 27 IIM indices in HF patients identified several simple, widely available, and inexpensive parameters highly predictive for PMI and/or in-hospital death. The applicability of IIM biomarkers to diagnose and predict risks for chronic diseases, including OP/OF, in the preclinical stages is discussed.

Construction and validation of a novel NAD+ metabolism-related risk model for prognostic prediction in osteosarcoma

Currently, the prognosis of osteosarcoma (OS) remains discouraging, especially in elderly/metastatic OS patients. By impairing the antitumor effect of immune cells, tumor immune microenvironment (TIME) provides an environment conducive to tumor proliferation, which highly requires accelerated nicotinamide adenine dinucleotide (NAD+) metabolism for energy. Recently, many genes involved in the sustained production of NAD+ in malignant tumors have been verified to be possible prognostic indicators and therapeutic targets. Therefore, the current study was to probe into the association of NAD+ metabolism-related genes with TIME, immunotherapeutic response, and prognosis in OS. All OS data for the study were acquired from TARGET and GEO databases. In bioinformatics analysis, we performed Cox analysis, consensus clustering, principal component analysis, t-distributed stochastic neighbor embedding, uniform manifold approximation and projection, gene set enrichment analysis, gene set variation analysis, Lasso analysis, survival and ROC curves, nomogram, immune-related analysis, drug sensitivity analysis, and single-cell RNA sequencing (scRNA-seq) analysis. Cell transfection assay, RT-qPCR, western blot analysis, as well as cell wound healing, migration, and invasion assays were performed in vitro. Bioinformatics analysis identified A&B clusters and six NAD+ metabolism-related differentially expressed genes, constructed risk model and nomogram, and performed immune-related analysis, drug susceptibility analysis, and scRNA-seq analysis to inform the clinical treatment framework. In vitro experiment revealed that CBS and INPP1 can promote migration, proliferation as well as invasion of OS cells through TGF-β1/Smad2/3 pathway. Based on bioinformatics analysis and in vitro validation, this study confirmed that NAD+ metabolism affects TIME to suggest the prognosis of OS.

Prognostic utility of preoperative platelet-to-albumin ratio in surgically treated oral cavity cancer patients

BACKGROUND

This study aimed to explore the prognostic utility of the preoperative platelet-to-albumin ratio (PAR) among patients with oral cavity squamous cell carcinoma (OSCC).

METHODS

We retrospectively reviewed of 355 patients with surgically-treated OSCC between 2008 and 2017. The optimal PAR cutoff for patient stratification was determined through X-tile analysis. Prognostic variables for disease-free survival (DFS) and overall survival (OS) were identified using Cox proportional hazards models. We developed a PAR-based nomogram to predict personalized OS.

RESULTS

We determined the optimal PAR cutoff to be 7.45. A PAR of ≥7.45 was an independent negative prognostic factor for DFS and OS (hazard ratio = 1.748 and 2.386; p = 0.005 and p < 0.001, respectively). The developed nomogram demonstrates the practical utility of PAR and accurately predicts personalized OS.

CONCLUSIONS

The preoperative PAR is a promising and cost-effective prognostic biomarker for patients with surgically-treated OSCC; the PAR-based nanogram accurately predicts OS for such patients.

Exploring the relationship between metabolism and immune microenvironment in osteosarcoma based on metabolic pathways

BACKGROUND

Metabolic remodeling and changes in tumor immune microenvironment (TIME) in osteosarcoma are important factors affecting prognosis and treatment. However, the relationship between metabolism and TIME needs to be further explored.

METHODS

RNA-Seq data and clinical information of 84 patients with osteosarcoma from the TARGET database and an independent cohort from the GEO database were included in this study. The activity of seven metabolic super-pathways and immune infiltration levels were inferred in osteosarcoma patients. Metabolism-related genes (MRGs) were identified and different metabolic clusters and MRG-related gene clusters were identified using unsupervised clustering. Then the TIME differences between the different clusters were compared. In addition, an MRGs-based risk model was constructed and the role of a key risk gene, ST3GAL4, in osteosarcoma cells was explored using molecular biological experiments.

RESULTS

This study revealed four key metabolic pathways in osteosarcoma, with vitamin and cofactor metabolism being the most relevant to prognosis and to TIME. Two metabolic pathway-related clusters (C1 and C2) were identified, with some differences in immune activating cell infiltration between the two clusters, and C2 was more likely to respond to two chemotherapeutic agents than C1. Three MRG-related gene clusters (GC1-3) were also identified, with significant differences in prognosis among the three clusters. GC2 and GC3 had higher immune cell infiltration than GC1. GC3 is most likely to respond to immune checkpoint blockade and to three commonly used clinical drugs. A metabolism-related risk model was developed and validated. The risk model has strong prognostic predictive power and the low-risk group has a higher level of immune infiltration than the high-risk group. Knockdown of ST3GAL4 significantly inhibited proliferation, migration, invasion and glycolysis of osteosarcoma cells and inhibited the M2 polarization of macrophages.

CONCLUSION

The metabolism of vitamins and cofactors is an important prognostic regulator of TIME in osteosarcoma, MRG-related gene clusters can well reflect changes in osteosarcoma TIME and predict chemotherapy and immunotherapy response. The metabolism-related risk model may serve as a useful prognostic predictor. ST3GAL4 plays a critical role in the progression, glycolysis, and TIME of osteosarcoma cells.

Association between neutrophil-to-albumin ratio and long-term mortality of aneurysmal subarachnoid hemorrhage

OBJECTIVE

The prognosis of aneurysmal subarachnoid hemorrhage (aSAH) survivors is concerning. The goal of this study was to investigate and demonstrate the relationship between the neutrophil-to-albumin ratio (NAR) and long-term mortality of aSAH survivors.

METHODS

A retrospective observational cohort study was conducted at Sichuan University West China Hospital between January 2009 and June 2019. The investigation of relationship between NAR and long-term mortality was conducted using univariable and multivariable Cox regression models. To demonstrate the predictive performance of different biomarkers over time, time-dependent receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA) were created.

RESULTS

In total, 3173 aSAH patients were included in this study. There was a strong and continuous relationship between NAR levels and long-term mortality (HR 3.23 95% CI 2.75-3.79, p < 0.001). After adjustment, the result was still significant (adjusted HR 1.78 95% CI 1.49-2.12). Compared with patients with the lowest quartile (< 0.15) of NAR levels, the risk of long-term mortality in the other groups was higher (0.15-0.20: adjusted HR 1.30 95% CI 0.97-1.73; 0.20-0.28: adjusted HR 1.37 95% CI 1.03-1.82; >0.28: adjusted HR 1.74 95% CI 1.30-2.32). Results in survivors were found to be still robust. Moreover, out of all the inflammatory markers studied, NAR demonstrated the highest correlation with long-term mortality.

CONCLUSIONS

A high level of NAR was associated with increased long-term mortality among patients with aSAH. NAR was a promising inflammatory marker for long-term mortality of aSAH.

The fibrinogen-albumin ratio as a novel prognostic factor for elderly patients with osteosarcoma

To analyze the prognostic value of fibrinogen-albumin ratio (FAR) in predicting the overall survival in elderly osteosarcoma patients. One hundred nineteen elderly osteosarcoma patients (> 40 years old) from 2 centers were retrospectively reviewed and analyzed. The cutoff values of the biomarker were calculated via receiver operating characteristic curves, and the cohort was divided into high FAR group and low FAR group. The association between the FAR and clinical-pathological parameters was analyzed. And the prognosis of elderly osteosarcoma patients and the potential risk factors were analyzed using Kaplan-Meier method and Cox proportional hazards model. Finally, a clinical nomogram was constructed, and its predictive capacity was verified. According to receiver operating characteristic results, the cutoff value for FAR was 0.098, and the enrolled patients were divided into the low FAR group and high FAR group. The FAR was significantly correlated with several clinical-pathological characteristics, including age, tumor size, tumor stage, recurrence, and metastasis. Moreover, the multivariate Cox analyses results showed that the FAR, pathological fracture, and metastasis were independent risk factors for overall survival in elderly osteosarcoma patients. The predictive nomogram was subsequently constructed, representing satisfactory predictive performance for prognosis in elderly patients with osteosarcoma. The FAR value is a promising indicator for elderly osteosarcoma patients, which is correlated with the various clinical characteristics and prognosis. A clinical nomogram integrating FAR and other clinical indicators is a convenient and available tool to assess the prognosis and manage the individualized and precise treatment of elderly patients with osteosarcoma.

Development and validation of platelet-to-albumin ratio as a clinical predictor for diffuse large B-cell lymphoma

Introduction

Diffuse large B-cell lymphoma (DLBCL) is the most common subtypes of lymphoma. Clinical biomarkers are still required for DLBCL patients to identify high-risk patients. Therefore, we developed and validated the platelet-to-albumin (PTA) ratio as a predictor for DLBCL patients.

Methods

A group of 749 patients was randomly divided into a training set (600 patients) and an internal validation set (149 cases). The independent cohort of 110 patients was enrolled from the other hospital as an external validation set. Penalized smoothing spline (PS) Cox regression models were used to explore the non-linear relationship between the PTA ratio and overall survival (OS) as well as progression-free survival (PFS), respectively.

Results

A U-shaped relation between the PTA ratio and PFS was identified in the training set. The PTA ratio less than 2.7 or greater than 8.6 was associated with the shorter PFS. Additionally, the PTA ratio had an additional prognostic value to the well-established predictors. What's more, the U-shaped pattern of the PTA ratio and PFS was respectively validated in the two validation sets.

Discussion

A U-shaped association between the PTA ratio and PFS was found in patients with DLBCLs. The PTA ratio can be used as a biomarker, and may suggest abnormalities of both host nutritional aspect and systemic inflammation in DLBCL.

Comparison of Prognostic Value of 10 Biochemical Indices at Admission for Prediction Postoperative Myocardial Injury and Hospital Mortality in Patients with Osteoporotic Hip Fracture

Aim: To evaluate the prognostic impact at admission of 10 biochemical indices for prediction postoperative myocardial injury (PMI) and/or hospital death in hip fracture (HF) patients. Methods: In 1273 consecutive patients with HF (mean age 82.9 ± 8.7 years, 73.5% women), clinical and laboratory parameters were collected prospectively, and outcomes were recorded. Multiple logistic regression and receiver-operating characteristic analyses (the area under the curve, AUC) were preformed, the number needed to predict (NNP) outcome was calculated. Results: Age ≥ 80 years and IHD were the most prominent clinical factors associated with both PMI (with cardiac troponin I rise) and in-hospital death. PMI occurred in 555 (43.6%) patients and contributed to 80.3% (49/61) of all deaths (mortality rate 8.8% vs. 1.9% in non-PMI patients). The most accurate biochemical predictive markers were parathyroid hormone > 6.8 pmol/L, urea > 7.5 mmol/L, 25(OH)vitamin D < 25 nmol/L, albumin < 33 g/L, and ratios gamma-glutamyl transferase (GGT) to alanine aminotransferase > 2.5, urea/albumin ≥ 2.0 and GGT/albumin ≥ 7.0; the AUC for developing PMI ranged between 0.782 and 0.742 (NNP: 1.84−2.13), the AUC for fatal outcome ranged from 0.803 to 0.722, (NNP: 3.77−9.52). Conclusions: In HF patients, easily accessible biochemical indices at admission substantially improve prediction of hospital outcomes, especially in the aged >80 years with IHD.