Characteristics associated with occurrence of stroke in patients with infective endocarditis - a retrospective cohort study.

BACKGROUND: Stroke is a severe complication of infective endocarditis (IE), associated with high rates of mortality. Data on how IE patients with and without stroke differ may help to improve understanding contributing mechanisms. METHODS: All patients treated for IE between 2019 and 2021 with and without associated stroke were identified from the medical records of three academic tertiary care hospitals in Germany, all part of Charité - Universitätsmedizin Berlin, Germany. Multivariable logistic regression analyses were performed to identify variables associated with the occurrence of stroke. RESULTS: The study population consisted of 353 patients diagnosed with IE. Concomitant stroke occurred in 96/353 (27.2%) patients. Acute stroke was independently associated with co-occurring extracerebral arterial embolism [adjusted Odds ratio (aOR = 2.52; 95% confidence interval (CI) 1.35-4.71)], acute liver failure (aOR = 2.62; 95% CI 1.06-6.50), dental focus of infection (aOR = 3.14; 95% CI 1.21-8.12) and left-sided IE (aOR = 28.26; 95% CI 3.59-222.19). Stroke was found less often in IE patients with congenital heart disease (aOR = 0.20; 95% CI 0.04-0.99) and atypical pathogens isolated from blood culture (aOR = 0.31; 95% CI 0.14-0.72). CONCLUSIONS: Stroke is more likely to occur in individuals with systemic complications affecting other organs, too. Special attention should be addressed to dental status. The low incidence of stroke in patients with congenital heart disease may reflect awareness and prophylactic measures.

Embryonal sarcoma of the liver in pediatric and young adult patients: A report from Children's Oncology Group study ARST0332.

BACKGROUND: Embryonal sarcoma of the liver (ESL) is a rare mesenchymal tumor most common in childhood; the optimal treatment approach is uncertain. The clinical features and outcomes of patients with ESL enrolled in a Children's Oncology Group (COG) clinical trial that evaluated a risk-based strategy for treating soft tissue sarcomas in patients aged <30 years were evaluated. METHODS: This subset analysis included patients with ESL enrolled in COG study ARST0332. Central review of records, pathology, and imaging confirmed the diagnosis, presenting features, and surgery extent and complications. All patients received dose-intensive ifosfamide/doxorubicin chemotherapy, with cycle timing dependent on surgery and radiotherapy. Tumor resection occurred before study entry or after four cycles of chemotherapy; radiotherapy for residual tumor was optional. RESULTS: Thirty-nine eligible/evaluable patients with ESL were analyzed. All tumors were >10 cm in diameter; four were metastatic. Tumor resection was performed upfront in 23 and delayed in 16. Positive surgical margins (n = 6) and intraoperative tumor rupture (n = 6) occurred only in upfront resections. Eight patients received radiotherapy. Estimated 5-year event-free and overall survival were 79% (95% confidence interval [CI], 65%-93%) and 95% (95% CI, 87%-100%), respectively. Positive margins increased the local recurrence risk. One of 13 patients with documented hemorrhagic ascites and/or tumor rupture developed extrahepatic intra-abdominal tumor recurrence. CONCLUSIONS: The treatment strategy used in ARST0332 achieved favorable outcomes for patients with ESL despite a substantial proportion having high-risk disease features. Deferring tumor resection until after neoadjuvant chemotherapy may decrease the risk of intraoperative tumor rupture and improve the likelihood of adequate surgical margins.

Presence of subfoveal hyperreflective dots as an anatomic and functional prognostic biomarker in macular holes.

OBJECTIVE: To evaluate the presence of subfoveal hyperreflective dots (SfHD) using optical coherence tomography (OCT) in macular holes (MH) and establish whether there is a relationship with postoperative anatomical and functional outcomes. METHODS: An observational cross-sectional study was conducted at the Dr. Elías Santana Hospital. Sixty-eight eyes of 67 patients with a tomographic diagnosis of full-thickness MH who underwent pars plana vitrectomy (PPV) and internal limiting membrane (ILM) peeling were included. Preoperative and postoperative measurements were obtained using radial macular scans and HD raster scans with Optovue and Cirrus 5000 (Zeiss) OCT machines. The main outcome measures were anatomical closure by OCT and functional outcome through best-corrected visual acuity (BCVA). RESULTS: The anatomical closure rate in our study was 63%. MHs that failed to achieve anatomical closure exhibited a higher number of hyperreflective dots and worse postoperative BCVA. A statistically significant association was found between exposed retinal pigment epithelium (RPE) in microns and the number of SfHD (p = 0.001). CONCLUSION: SfHD is a common tomographic finding in MH, and the presence of a higher number of these points is associated with poorer anatomical and functional outcomes. This imaging finding is a potential prognostic biomarker in this pathology.

Identification and validation of an anoikis-related genes signature for prognostic implication in papillary thyroid cancer.

Thyroid cancer, notably papillary thyroid cancer (PTC), is a global health concern with increasing incidence. Anoikis, a regulator of programmed cell death, is pivotal in normal physiology and, when dysregulated, can drive cancer progression and metastasis. This study explored the impact of anoikis on PTC prognosis. Analyzing data from GEO, TCGA, and GeneCards, we identified a prognostic signature consisting of six anoikis-related genes (ARGs): EZH2, PRKCQ, CD36, INHBB, TDGF1, and MMP9. This signature independently predicted patient outcomes, with high-risk scores associated with worse prognoses. A robust predictive ability was confirmed via ROC analysis, and a nomogram achieved a C-index of 0.712. Differences in immune infiltration levels were observed between high- and low-risk groups. Importantly, the high-risk group displayed reduced drug sensitivity and poor responses to immunotherapy. This research provides insights into anoikis in PTC, offering a novel ARG signature for predicting patient prognosis and guiding personalized treatment strategies.

Utility of Initial Tumor Reduction as a Prognostic Factor in Esophageal Squamous Cell Cancer Patients Undergoing Neoadjuvant Chemotherapy Followed by Surgery : A Retrospective Cohort Study.

BACKGROUND: While a neoadjuvant chemotherapy regimen using docetaxel, cisplatin, and 5-fluorouracil (NAC-DCF) is considered the standard treatment for locally advanced esophageal cancer (EC) in Japan, a reliable marker for early prediction of treatment efficacy remains unclear. We investigated the utility of the tumor response after a first course of NAC-DCF as a post-surgery survival predictor in patients with EC. METHODS: We enrolled 150 consecutive patients who underwent NAC-DCF followed by surgery for EC between September 2009 and January 2019. The initial tumor reduction (ITR), defined as the percentage decrease in the shorter diameter of the tumor after the first course of NAC-DCF, was evaluated using computed tomography. We analyzed the relationship between ITR, clinicopathological parameters, and survival. RESULTS: The median ITR was 21.07% (range -11.45 to 50.13%). The optimal cut-off value for ITR for predicting prognosis was 10% (hazard ratio [HR] 3.30, 95% confidence interval [CI] 1.98-5.51), based on univariate logistic regression analyses for recurrence-free survival (RFS). Compared with patients with ITR <10%, patients with ITR ≥10% showed a significantly higher proportion of ypM0 (80.0% vs. 92.5%) and responders in terms of overall clinical response (50.0% vs. 80.8%). Multivariate analysis for RFS revealed that ypN2-3 (HR 2.78, 95% CI 1.67-4.62), non-response in terms of overall clinical response (HR 1.87, 95% CI 1.10-3.18), and ITR <10% (HR 2.48, 95% CI 1.42-4.32) were independent prognostic factors. CONCLUSIONS: Tumor response after the first course of NAC-DCF may be a good predictor of survival in patients with EC who underwent NAC-DCF plus surgery.

Prognosis stratification of cancer patients treated with immune checkpoint inhibitors through lung immune prognostic index: a meta-analysis and systematic review.

BACKGROUND: Although numerous studies have reported the prognostic value of the lung immune prognostic index (LIPI) in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), the prognostic value of the LIPI in a pancancer setting remains unclear. METHODS: A comprehensive search was conducted until July 2023 across the PubMed, Embase, Web of Science, and Cochrane Library databases to identify relevant studies evaluating the prognostic value of the LIPI in cancer patients treated with ICIs. The outcomes were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR). We described and compared the pooled outcomes by stratifying the patients based on different groupings of LIPI (good vs. intermediate [0 vs. 1], good vs. poor [0 vs. 2], and good vs. intermediate / poor [0 vs. 1 + 2]). RESULTS: A total of 9959 patients in 35 studies were included. A higher score of LIPI was associated with impaired OS. The pooled HRs were 1.69 (95% CI: 1.55-1.85, p < 0.001; 0 vs. 1), 3.03 (95% CI: 2.53-3.63, p < 0.001; 0 vs. 2), and 2.38 (95% CI: 1.97-2.88, p < 0.001; 0 vs. 1 + 2). A higher LIPI score was associated with shorter PFS. The pooled HRs were 1.41 (95% CI: 1.31-1.52, p < 0.001; 0 vs. 1), 2.23 (95% CI: 1.87-2.66, p < 0.001; 0 vs. 2), and 1.65 (95% CI: 1.46-1.86, p < 0.001; 0 vs. 1 + 2). Similarly, a higher LIPI score was associated with a lower ORR. The pooled ORs were 0.63 (95% CI: 0.54-0.75, p < 0.001; 0 vs. 1) and 0.38 (95% CI: 0.29-0.50, p < 0.001; 0 vs. 2). A higher LIPI score was associated with a lower DCR. The pooled ORs were 0.47 (95% CI: 0.35-0.61, p < 0.001; 0 vs. 1) and 0.19 (95% CI: 0.12-0.30, p < 0.001; 0 vs. 2). CONCLUSION: In patients with NSCLC or other solid tumours, the lung immune prognostic index could robustly stratify the clinical outcomes into three groups among the patients who receive ICIs. LIPI is a low-cost, simple, accessible, and accurate prognostic tool in a pancancer setting and it may contribute to the evaluation of risk stratification in patients treated with ICIs.

Identification of exosome-related gene signature as a promising diagnostic and therapeutic tool for breast cancer.

Background: Exosomes are promising tools for the development of new diagnostic and therapeutic approaches. Exosomes possess the ability to activate signaling pathways that contribute to the remodeling of the tumor microenvironment, angiogenesis, and the regulation of immune responses. We aimed to develop a prognostic score based on exosomes derived from breast cancer. Materials and methods: Training was conducted on the TCGA-BRCA dataset, while validation was conducted on GSE20685, GSE5764, GSE7904, and GSE29431. A total of 121 genes related to exosomes were retrieved from the ExoBCD database. The Cox proportional hazards model is used to develop risk score model. The GSVA package was utilized to analyze single-sample gene sets and identify exosome signatures, while the WGCNA package was utilized to identify gene modules associated with clinical outcomes. The clusterProfiler and GSVA R packages facilitated gene set enrichment and variation analyses. Furthermore, CIBERSORT quantified immune infiltration, and a correlation between gene expression and drug sensitivity was assessed using the TIDE algorithm. Results: An exosome-related prognostic score was established using the following selected genes: ABCC9, PIGR, CXCL13, DOK7, CD24, and IVL. Various immune cells that promote cancer immune evasion were associated with a high-risk prognostic score, which was an independent predictor of outcome. High-risk and low-risk groups exhibited significantly different infiltration abundances (p < 0.05). By conducting a sensitivity comparison, we found that patients with high-risk scores exhibited more favorable responses to immunotherapy than those with low-risk scores. Conclusion: The exosome-related gene signature exhibits outstanding performance in predicting the prognosis and cancer status of patients with breast cancer and guiding immunotherapy.

The development and internal validation of a multivariable model predicting 6-month mortality for people with opioid use disorder presenting to community drug services in England: a protocol.

BACKGROUND: People with opioid use disorder have substantially higher standardised mortality rates compared to the general population; however, lack of clear individual prognostic information presents challenges to prioritise or target interventions within drug treatment services. Previous prognostic models have been developed to estimate the risk of developing opioid use disorder and opioid-related overdose in people routinely prescribed opioids but, to our knowledge, none have been developed to estimate mortality risk in people accessing drug services with opioid use disorder. Initial presentation to drug services is a pragmatic time to evaluate mortality risk given the contemporaneous routine collection of prognostic indicators and as a decision point for appropriate service prioritisation and targeted intervention delivery. This study aims to develop and internally validate a model to estimate 6-month mortality risk for people with opioid use disorder from prognostic indicators recorded at initial assessment in drug services in England. METHODS: An English national dataset containing records from individuals presenting to drug services between 1 April 2013 and 1 April 2023 (n > 800,000) (the National Drug Treatment Monitoring System (NDTMS)) linked to their lifetime hospitalisation and death records (Hospital Episode Statistics-Office of National Statistics (HES-ONS)). Twelve candidate prognostic indicator variables were identified based on literature review of demographic and clinical features associated with increased mortality for people in treatment for opioid use disorder. Variables will be extracted at initial presentation to drug services with mortality measured at 6 months. Two multivariable Cox regression models will be developed one for 6-month all-cause mortality and one for 6-month drug-related mortality using backward elimination with a fractional polynomial approach for continuous variables. Internal validation will be undertaken using bootstrapping methods. Discrimination of both models will be reported using Harrel's c and d-statistics. Calibration curves and slopes will be presented comparing expected and observed event rates. DISCUSSION: The models developed and internally validated in this study aim to improve clinical assessment of mortality risk for people with opioid use disorder presenting to drug services in England. External validation in different populations will be required to develop the model into a tool to assist future clinical decision-making.

Surgical outcomes including visual improvement after glaucoma surgery in patients with neovascular glaucoma.

Purpose: This study aimed to evaluate the prognostic factors affecting surgical outcomes, including visual acuity (VA) improvement, after glaucoma surgery in patients with neovascular glaucoma (NVG). Methods: The medical records of 116 patients (116 eyes) with NVG who had undergone trabeculectomy or Ahmed glaucoma valve implantation were reviewed retrospectively. The primary outcome measure was surgical success at 6 postoperative months, defined as sufficient intraocular pressure (IOP) reduction (IOP ≤21 mmHg, ≥20% reduction, regardless of topical medication use) without additional glaucoma surgery, hypotony, or progression to no light perception. Success was categorized as complete or qualified based on whether an improvement in VA was observed in addition to the abovementioned definition. Results: The complete and qualified success rates at 6 months were 44.6% and 92.2%, respectively. Age (p = 0.001), preoperative best-corrected VA (p = 0.031), duration of decreased VA (p = 0.001), closed-angle status (p = 0.013), and etiology (p = 0.007) differed significantly between the groups with and without complete success. Multivariate analysis revealed that age (odds ratio [OR] 1.05; p = 0.026), duration of decreased VA (OR 1.05; p = 0.016), and 360° closed-angle status (OR 3.27; p = 0.031) were risk factors for surgical failure according to the complete success criteria, but not the qualified success criteria. Conclusions: Patients with NVG showed improved visual prognosis and successful IOP reduction after glaucoma surgery at a relatively younger age if the duration of visual loss was not prolonged and the angle status was not completely closed.

Identification and Validation of Novel Metastasis-Related Immune Gene Signature in Breast Cancer.

Background: Distant metastasis remains the leading cause of death among patients with breast cancer (BRCA). The process of cancer metastasis involves multiple mechanisms, including compromised immune system. However, not all genes involved in immune function have been comprehensively identified. Methods: Firstly 1623 BRCA samples, including transcriptome sequencing and clinical information, were acquired from Gene Expression Omnibus (GSE102818, GSE45255, GSE86166) and The Cancer Genome Atlas-BRCA (TCGA-BRCA) dataset. Subsequently, weighted gene co-expression network analysis (WGCNA) was performed using the GSE102818 dataset to identify the most relevant module to the metastasis of BRCA. Besides, ConsensusClusterPlus was applied to divide TCGA-BRCA patients into two subgroups (G1 and G2). In the meantime, the least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a metastasis-related immune genes (MRIGs)_score to predict the metastasis and progression of cancer. Importantly, the expression of vital genes was validated through reverse transcription quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). Results: The expression pattern of 76 MRIGs screened by WGCNA divided TCGA-BRCA patients into two subgroups (G1 and G2), and the prognosis of G1 group was worse. Also, G1 exhibited a higher mRNA expression level based on stemness index score and Tumor Immune Dysfunction and Exclusion score. In addition, higher MRIGs_score represented the higher probability of progression in BRCA patients. It was worth mentioning that the patients in the G1 group had a high MRIGs_score than those in the G2 group. Importantly, the results of RT-qPCR and IHC demonstrated that fasciculation and elongation protein zeta 1 (FEZ1) and insulin-like growth factor 2 receptor (IGF2R) were risk factors, while interleukin (IL)-1 receptor antagonist (IL1RN) was a protective factor. Conclusion: Our study revealed a prognostic model composed of eight immune related genes that could predict the metastasis and progression of BRCA. Higher score represented higher metastasis probability. Besides, the consistency of key genes in BRCA tissue and bioinformatics analysis results from mRNA and protein levels was verified.

Analysis of the treatment and prognosis of 266 cases of extranodal natural killer/T-cell lymphoma, nasal type in a single medical center.

Objective: To assess the impact of different treatment strategies and risk factors on the prognosis of patients with extranodal NK/T-cell lymphoma, nasal type (ENKTL) in a single medical center. Methods and analysis: The clinical features of 266 patients with ENKTL were retrospectively analyzed, among whom those in stages I and II received sandwich therapy, while those in stages III and IV underwent chemotherapy plus autologous hematopoietic stem cell transplantation. The Kaplan-Meier curves, univariate and multivariate Cox regression analyses were employed for survival and prognosis analysis. Statistical significance was set at P<0.05. Results: Following treatment, the post-intervention outcomes demonstrated a complete remission (CR) rate of 71.05% and a partial remission (PR) rate of 3.76%. The 5-year progression-free survival (PFS) and overall survival (OS) rates were 70.4% and 70.9%, respectively. In addition, the PFS for patients in stage I/II was 79.8%, with an OS of 81.1%, whereas for those in stage III/IV, the PFS was 41.7% and the OS was 40.9%. Notably, the achievement of CR immediately after treatment was an independent prognostic factor (P<0.001). Patients in stage I/II depicted a favorable 5-year OS rate, while those in stage III/IV manifested a less favorable prognosis. Conclusion: Stages of the disease and whether CR was achieved following treatment are important factors determining the survival and prognosis of patients with ENKTL. Further researches focusing on disease onset and mechanisms of drug resistance will contribute to better management of ENKTL.

Bioinformatics-driven identification of prognostic biomarkers in kidney renal clear cell carcinoma.

Renal cell carcinoma (RCC), particularly the clear cell subtype (ccRCC), poses a significant global health concern due to its increasing prevalence and resistance to conventional therapies. Early detection of ccRCC remains challenging, resulting in poor patient survival rates. In this study, we employed a bioinformatic approach to identify potential prognostic biomarkers for kidney renal clear cell carcinoma (KIRC). By analyzing RNA sequencing data from the TCGA-KIRC project, differentially expressed genes (DEGs) associated with ccRCC were identified. Pathway analysis utilizing the Qiagen Ingenuity Pathway Analysis (IPA) tool elucidated key pathways and genes involved in ccRCC dysregulation. Prognostic value assessment was conducted through survival analysis, including Cox univariate proportional hazards (PH) modeling and Kaplan-Meier plotting. This analysis unveiled several promising biomarkers, such as MMP9, PIK3R6, IFNG, and PGF, exhibiting significant associations with overall survival and relapse-free survival in ccRCC patients. Cox multivariate PH analysis, considering gene expression and age at diagnosis, further confirmed the prognostic potential of MMP9, IFNG, and PGF genes. These findings enhance our understanding of ccRCC and provide valuable insights into potential prognostic biomarkers that can aid healthcare professionals in risk stratification and treatment decision-making. The study also establishes a foundation for future research, validation, and clinical translation of the identified prognostic biomarkers, paving the way for personalized approaches in the management of KIRC.

Prognostic model on pregnancy outcomes for women with recurrent spontaneous abortions treated with cyclosporin A: A single-institution experience.

BACKGROUND: This study aimed to identify prognostic factors for pregnancy outcomes and construct a prognostic model for pregnancy outcomes in women with Recurrent Spontaneous Abortions (RSA) treated with cyclosporin A. METHODS: A total of 154 RSA patients treated with cyclosporin A between October 2016 and October 2018 were retrospectively recruited. Multivariate logistic regression was applied to identify the prognostic factors for pregnancy success in RSA women treated with cyclosporin A. The Receiver Operating Characteristic (ROC) curve was applied to construct prognostic value, and the prognostic performance was assessed using area under the ROC. RESULTS: After adjusting potential confounding factors, the authors noted increased age (OR = 0.771; 95 % CI 0.693‒0.858; p < 0.001) and positive antinuclear antibodies (OR = 0.204; 95 % CI 0.079‒0.526; p = 0.001) were associated with a reduced incidence of pregnancy success, while positive anti-ß2 glycoprotein-I-antibody (OR = 21.941; 95 % CI 1.176‒409.281; p = 0.039) was associated with an increased incidence of pregnancy success after treated with cyclosporin A. The AUC of combining these variables for predicting pregnancy failure was 0.809 (95 % CI 0.735‒0.880). CONCLUSIONS: This study systematically identified the prognostic factors for pregnancy success in women treated with cyclosporin A, and the constructed prognostic model based on these factors with relatively higher prognostic value. Further large-scale prospective studies should be performed to validate the prognostic value of the constructed model.

Necroptosis-related lncRNA-based novel signature to predict the prognosis and immune landscape in soft tissue sarcomas.

BACKGROUND: Necroptosis-related long noncoding RNAs (lncRNAs) play crucial roles in cancer initiation and progression. Nevertheless, the role and mechanism of necroptosis-related lncRNAs in soft tissue sarcomas (STS) is so far unknown and needs to be explored further. METHODS: Clinical and genomic data were obtained from the UCSC Xena database. All STS patients' subclusters were performed by unsupervised consensus clustering method based on the prognosis-specific lncRNAs, and then assessed their survival advantage and immune infiltrates. In addition, we explored the pathways and biological processes in subclusters through gene set enrichment analysis. At last, we established the necroptosis-related lncRNA-based risk signature (NRLncSig) using the least absolute shrinkage and selection operator (LASSO) method, and explored the prediction performance and immune microenvironment of this signature in STS. RESULTS: A total of 911 normal soft tissue samples and 259 STS patients were included in current study. 39 prognosis-specific necroptosis-related lncRNAs were selected. Cluster 2 had a worse survival than the cluster 1 and characterized by different immune landscape in STS. A worse outcome in the high-risk group was observed by survival analysis and indicated an immunosuppressive microenvironment. The ROC curve analyses illustrated that the NRLncSig performing competitively in prediction of prognosis for STS patients. In addition, the nomogram presents excellent performance in predicting prognosis, which may be more beneficial towards STS patients' treatment. CONCLUSIONS: Our result indicated that the NRLncSig could be a good independent predictor of prognosis, and significantly connected with immune microenvironment, thereby providing new insights into the roles of necroptosis-related lncRNAs in STS.

PPP2R1A silencing suppresses LUAD progression by sensitizing cells to nelfinavir-induced apoptosis and pyroptosis.

Lung adenocarcinoma is a major public health problem with the low 5-year survival rate (15%) among cancers. Aberrant alterations of meiotic genes, which have gained increased attention recently, might contribute to elevated tumor risks. However, systematic and comprehensive studies based on the relationship between meiotic genes and LUAD recurrence and treatment response are still lacking. In this manuscript, we first confirmed that the meiosis related prognostic model (MRPM) was strongly related to LUAD progression via LASSO-Cox regression analyses. Furthermore, we identified the role of PPP2R1A in LUAD, which showed more contributions to LUAD process compared with other meiotic genes in our prognostic model. Additionally, repression of PPP2R1A enhances cellular susceptibility to nelfinavir-induced apoptosis and pyroptosis. Collectively, our findings indicated that meiosis-related genes might be therapeutic targets in LUAD and provided crucial guidelines for LUAD clinical intervention.

Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach.

Background: In the central nervous system, glioma is the most common malignant tumor, and patients have a poor prognosis. Identification of novel marker genes and establishment of prognostic models are important for early diagnosis and prognosis determination. Methods: Download glioma data from the CGGA and TCG databases. Application of bioinformatics to analyze the impact of CYBB on the clinicopathological characteristics, immunological features and prognosis of gliomas. Using single-cell sequencing data from 7 glioblastoma patients in the CGGA database, the role of CYBB in the tumor microenvironment was analyzed. In addition, a prognostic model was constructed based on CYBB high and low differentially expressed genes and mitochondrial genes. Results: The expression of CYBB is closely related to various clinical features, immune cell infiltration level, immune checkpoint and survival time of patients. A 10-gene prediction model was constructed based on the differentially expressed genes of low and high CYBB and mitochondria-related genes. Glioma patients with higher risk scores had significantly lower survival probabilities. Receiver operating characteristic curves and nomograms were plotted over time to show the predictive accuracy and predictive value of the 10-gene prognostic model. Conclusions: Our study shows that CYBB is strongly correlated with clinical characteristics features and prognosis of glioma patients, and can be used as a potential therapeutic target. Prognostic models based on CYBB and mitochondrial genes have good performance in predicting prognosis of glioma patients.

ALTA: a simple nutritional prognostic score for patients with hepatitis B virus-related acute-on-chronic liver failure.

Background: Malnutrition, despite being a common complication, is often neglected in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF). The objective of this study was to develop a simplified nutritional prognostic score to accurately predict mortality in HBV-ACLF patients. Methods: In this multicenter retrospective study, clinical data from 530 HBV-ACLF patients were used to create a new prognostic score, which was then validated in two external cohorts (n = 229 and 248). Results: Four independent factors were significantly associated with 28-day mortality in HBV-ACLF patients, forming a novel prognostic score (ALTA score = 0.187 × age-0.849 × lymphocyte count-2.033 × total cholesterol-0.148 × albumin-0.971). Notably, the AUROC of ALTA score for 28/90-day mortality (0.950/0.967) were significantly higher than those of three other ACLF prognostic scores (COSSH-ACLF II, 0.864/0.734; MELD, 0.525/0.488; MELD-Na, 0.546/0.517; all P < 0.001), and three known nutritional scores (CONUT, 0.739/0.861; OPNI, 0.279/0.157; NRS-2002, 0.322/0.286; all P < 0.001). The prediction error rates of ALTA score for 28-day mortality were significantly lower than COSSH-ACLF II (7.3%), MELD (14.4%), MELD-Na (12.7%), CONUT (9.0%), OPNI (30.6%), and NRS2002 (34.1%) scores. Further classifying ALTA score into two strata, the hazard ratios of mortality at 28/90 days were notably increased in the high-risk groups compared to the low-risk group (15.959 and 5.740). These results were then validated in two external cohorts. Conclusion: ALTA, as a simplified nutritional prognostic score for HBV-ACLF, demonstrates superiority over the COSSH-ACLF II and other scores in predicting short-term mortality among HBV-ACLF patients. Therefore, it may be used to guide clinical management, particularly in primary care settings.

MRI radiomics in head and neck cancer from reproducibility to combined approaches.

The clinical applicability of radiomics in oncology depends on its transferability to real-world settings. However, the absence of standardized radiomics pipelines combined with methodological variability and insufficient reporting may hamper the reproducibility of radiomic analyses, impeding its translation to clinics. This study aimed to identify and replicate published, reproducible radiomic signatures based on magnetic resonance imaging (MRI), for prognosis of overall survival in head and neck squamous cell carcinoma (HNSCC) patients. Seven signatures were identified and reproduced on 58 HNSCC patients from the DB2Decide Project. The analysis focused on: assessing the signatures' reproducibility and replicating them by addressing the insufficient reporting; evaluating their relationship and performances; and proposing a cluster-based approach to combine radiomic signatures, enhancing the prognostic performance. The analysis revealed key insights: (1) despite the signatures were based on different features, high correlations among signatures and features suggested consistency in the description of lesion properties; (2) although the uncertainties in reproducing the signatures, they exhibited a moderate prognostic capability on an external dataset; (3) clustering approaches improved prognostic performance compared to individual signatures. Thus, transparent methodology not only facilitates replication on external datasets but also advances the field, refining prognostic models for potential personalized medicine applications.

Construction and validation of a nomogram for predicting overall survival of patients with stage III/IV early-onset colorectal cancer.

Purpose: This study aimed to identify prognostic factors and develop a nomogram for predicting overall survival (OS) in stage III/IV early-onset colorectal cancer (EO-CRC). Methods: Stage III/IV EO-CRC patients were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The datasets were randomly divided (2:1) into training and validation sets. A nomogram predicting OS was developed based on the prognostic factors identified by Cox regression analysis in the training cohort. Moreover, the predictive performance of the nomogram was assessed using the receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Subsequently, the internal validation was performed using the validation cohort. Finally, a risk stratification system was established based on the constructed nomogram. Results: Of the 10,387 patients diagnosed with stage III/IV EO-CRC between 2010 and 2015 in the SEER database, 8,130 patients were included. In the training cohort (n=3,071), sex, marital status, race/ethnicity, primary site, histologic subtypes, grade, T stage, and N stage were identified as independent prognostic variables for OS. The 1-, 3-, and 5-year area under the curve (AUC) values of the nomogram were robust in both the training (0.751, 0.739, and 0.723) and validation cohorts (0.748, 0.733, and 0.720). ROC, calibration plots, and DCA indicated good predictive performance of the nomogram in both the training and validation sets. Furthermore, patients were categorized into low-, middle-, and high-risk groups based on the nomogram risk score. Kaplan-Meier curve showed significant survival differences between the three groups. Conclusion: We developed a prognostic nomogram and risk stratification system for stage III/IV EO-CRC, which may facilitate clinical decision-making and individual prognosis prediction.

Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe condition with an uncertain origin and a dismal prognosis. There is presently no precise diagnostic test for ME/CFS, and the diagnosis is determined primarily by the presence of certain symptoms. The current study presents an explainable artificial intelligence (XAI) integrated machine learning (ML) framework that identifies and classifies potential metabolic biomarkers of ME/CFS. Metabolomic data from blood samples from 19 controls and 32 ME/CFS patients, all female, who were between age and body mass index (BMI) frequency-matched groups, were used to develop the XAI-based model. The dataset contained 832 metabolites, and after feature selection, the model was developed using only 50 metabolites, meaning less medical knowledge is required, thus reducing diagnostic costs and improving prognostic time. The computational method was developed using six different ML algorithms before and after feature selection. The final classification model was explained using the XAI approach, SHAP. The best-performing classification model (XGBoost) achieved an area under the receiver operating characteristic curve (AUCROC) value of 98.85%. SHAP results showed that decreased levels of alpha-CEHC sulfate, hypoxanthine, and phenylacetylglutamine, as well as increased levels of N-delta-acetylornithine and oleoyl-linoloyl-glycerol (18:1/18:2)[2], increased the risk of ME/CFS. Besides the robustness of the methodology used, the results showed that the combination of ML and XAI could explain the biomarker prediction of ME/CFS and provided a first step toward establishing prognostic models for ME/CFS.