Risk Groups Research Articles

Development of Chromatin Regulator-related Molecular Subtypes and a Signature to Predict Prognosis and Immunotherapeutic Response in Head and Neck Squamous Cell Carcinoma.

Chromatin regulators (CRs) serve as indispensable factors in tumor biological processes by influencing tumorigenesis and the immune microenvironment and have been identified in head and neck squamous cell carcinoma (HNSCC). Hence, CR-related genes (CRRGs) are considered potential biomarkers for predicting prognosis and immune infiltration in HNSCC. In this study, we established a novel signature for predicting the prognosis and immunotherapeutic response of HSNCC. A total of 870 CRRGs were obtained according to previous studies. Subsequently, patients in the TCGA-HNSC cohort were divided into different clusters based on the expression of prognostic CRRGs. Kaplan‒Meier (K‒M) survival analysis was conducted to compare the prognosis in clusters, and the CIBERSORT and ssGSEA methods assessed the immune infiltration status. In addition, the differences in immunotherapeutic responses were determined based on the TICA database. Furthermore, the differentially expressed CRRGs between clusters were identified, and the predictive signature was established according to the results of univariate Cox, least absolute shrinkage and selection operator regression analysis, and multivariate Cox. The predictive effects of the risk model were evaluated according to the area under the receiver operating characteristic (ROC) curve (AUC) in both the training and external test cohorts. A nomogram was established, and survival comparisons, functional enrichment analyses, and immune infiltration status and clinical treatment assessments were performed. In addition, the hub gene network and related analysis were conducted with the Cytohubba application. Based on the expression of prognostic CRRGs, patients were divided into two clusters, in which Cluster 1 exhibited a better prognosis, more enriched immune infiltration, and a better immunotherapeutic response but exhibited chemotherapy sensitivity. The AUC values of the 1-, 3- and 5- year ROC curves for the risk model were 0.673, 0.732, and 0.692, respectively, as well as 0.645, 0.608, and 0.623 for the test set. In addition, patients in the low-risk group exhibited more immune cell enrichment and immune function activation, as well as a better immunotherapy response. The hub gene network indicated ACTN2 as the core gene differentially expressed between the two risk groups. We identified molecular subtypes and established a novel predictive signature based on CRRGs. This effective CRRS system can possibly provide a novel research direction for exploring the correlation between CRs and HNSCC and requires further experimental validation.

Exploring Novel Genome Instability-associated lncRNAs and their Potential Function in Pan-Renal Cell Carcinoma.

Genomic instability can drive clonal evolution, continuous modification of tumor genomes, and tumor genomic heterogeneity. The molecular mechanism of genomic instability still needs further investigation. This study aims to identify novel genome instabilityassociated lncRNAs (GI-lncRNAs) and investigate the role of genome instability in pan-Renal cell carcinoma (RCC). A mutator hypothesis was employed, combining the TCGA database of somatic mutation (SM) information, to identify GI-lncRNAs. Subsequently, a training cohort (n = 442) and a testing cohort (n = 439) were formed by randomly dividing all RCC patients. Based on the training cohort dataset, a multivariate Cox regression analysis lncRNAs risk model was created. Further validations were performed in the testing cohort, TCGA cohort, and different RCC subtypes. To confirm the relative expression levels of lncRNAs in HK-2, 786-O, and 769-P cells, qPCR was carried out. Functional pathway enrichment analyses were performed for further investigation. A total of 170 novel GI-lncRNAs were identified. The lncRNA prognostic risk model was constructed based on LINC00460, AC073218.1, AC010789.1, and COLCA1. This risk model successfully differentiated patients into distinct risk groups with significantly different clinical outcomes. The model was further validated in multiple independent patient cohorts. Additionally, functional and pathway enrichment analyses revealed that GI-lncRNAs play a crucial role in GI. Furthermore, the assessments of immune response, drug sensitivity, and cancer stemness revealed a significant relationship between GI-lncRNAs and tumor microenvironment infiltration, mutational burden, microsatellite instability, and drug resistance. In this study, we discovered four novel GI-lncRNAs and developed a novel signature that effectively predicted clinical outcomes in pan-RCC. The findings provide valuable insights for pan-RCC immunotherapy and shed light on potential underlying mechanisms.

A randomised trial of short- vs long-term androgen deprivation with salvage radiotherapy for biochemical failure following radical prostatectomy: URONCOR 06-24.

Salvage radiotherapy (SRT) and androgen-deprivation therapy (ADT) are widely used in routine clinical practice to treat patients with prostate cancer who develop biochemical recurrence (BCR) after radical prostatectomy (RP). However, there is no standard-of-care consensus on optimal duration ADT. Investigators propose three distinct risk groups in patients with prostate cancer treated with SRT in order to better define the indications and duration of ADT combined with SRT. The URONCOR 06-24 trial (ClinicalTrials.gov identifier NCT05781217) is a prospective, multicentre, randomised, open-label, phase III, clinical trial. The aim of the trial is to determine the impact of short-term (6 months) vs long-term (24 months) ADT in combination with SRT on distant metastasis-free survival (MFS) in patients with prostate cancer with BCR after RP (intermediate and high risk). The primary endpoint is 5-year MFS rates in patients with prostate cancer treated with long- vs short-term ADT in combination with SRT. Secondary objectives are biochemical-relapse free interval, pelvic progression-free survival, time to start of systemic treatment, time to castration resistance, cancer-specific survival, overall survival, acute and late toxicity, and quality of life. Total of 534 patients will be randomised 1:1 to ADT 6 months or ADT 24 months with a luteinizing hormone-releasing hormone analogue in combination with SRT, stratified by risk group and pathological lymph node status. The study is conducted under the guiding principles of the World Medical Association Declaration of Helsinki. The results will be disseminated at research conferences and in peer-reviewed journals. EudraCT number 2021-006975-41.

Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods

BackgroundIn randomized clinical trials, treatment effects may vary, and this possibility is referred to as heterogeneity of treatment effect (HTE). One way to quantify HTE is to partition participants into subgroups based on individual’s risk of experiencing an outcome, then measuring treatment effect by subgroup. Given the limited availability of externally validated outcome risk prediction models, internal models (created using the same dataset in which heterogeneity of treatment analyses also will be performed) are commonly developed for subgroup identification. We aim to compare different methods for generating internally developed outcome risk prediction models for subject partitioning in HTE analysis.MethodsThree approaches were selected for generating subgroups for the 2,441 participants from the United States enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) randomized controlled trial. An extant proportional hazards-based outcomes predictive risk model developed on the overall ASPREE cohort of 19,114 participants was identified and was used to partition United States’ participants by risk of experiencing a composite outcome of death, dementia, or persistent physical disability. Next, two supervised non-parametric machine learning outcome classifiers, decision trees and random forests, were used to develop multivariable risk prediction models and partition participants into subgroups with varied risks of experiencing the composite outcome. Then, we assessed how the partitioning from the proportional hazard model compared to those generated by the machine learning models in an HTE analysis of the 5-year absolute risk reduction (ARR) and hazard ratio for aspirin vs. placebo in each subgroup. Cochran’s Q test was used to detect if ARR varied significantly by subgroup.ResultsThe proportional hazard model was used to generate 5 subgroups using the quintiles of the estimated risk scores; the decision tree model was used to generate 6 subgroups (6 automatically determined tree leaves); and the random forest model was used to generate 5 subgroups using the quintiles of the prediction probability as risk scores. Using the semi-parametric proportional hazards model, the ARR at 5 years was 15.1% (95% CI 4.0–26.3%) for participants with the highest 20% of predicted risk. Using the random forest model, the ARR at 5 years was 13.7% (95% CI 3.1–24.4%) for participants with the highest 20% of predicted risk. The highest outcome risk group in the decision tree model also exhibited a risk reduction, but the confidence interval was wider (5-year ARR = 17.0%, 95% CI= -5.4–39.4%). Cochran’s Q test indicated ARR varied significantly only by subgroups created using the proportional hazards model. The hazard ratio for aspirin vs. placebo therapy did not significantly vary by subgroup in any of the models. The highest risk groups for the proportional hazards model and random forest model contained 230 participants each, while the highest risk group in the decision tree model contained 41 participants.ConclusionsThe choice of technique for internally developed models for outcome risk subgroups influences HTE analyses. The rationale for the use of a particular subgroup determination model in HTE analyses needs to be explicitly defined based on desired levels of explainability (with features importance), uncertainty of prediction, chances of overfitting, and assumptions regarding the underlying data structure. Replication of these analyses using data from other mid-size clinical trials may help to establish guidance for selecting an outcomes risk prediction modelling technique for HTE analyses.

PRF1 as a prognostic gene for lymphatic metastasis in skin melanoma

BackgroundMelanoma is a highly aggressive tumor, predominantly found in the skin, recognized as skin cutaneous melanoma (SKCM). Lymph node metastasis is commonly used as the route of metastasis in SKCM, necessitating the discovery of prognostic genes associated with this process for improved prognosis. MethodsThe prognostic significance of lymph node metastasis in SKCM was assessed through Kaplan-Meier analysis in SEER and TCGA-SKCM datasets. Prognostic genes were identified and a prognostic risk model was constructed Enrichment analysis and immune cell infiltration analysis were also carried out.Moreover, a validation in vitro and in vivo were conducted by CCK8,flow cytometry,transwell and animal study. ResultsThe Kaplan-Meier survival curve revealed that patients with lymph node metastasis had a worse prognosis compared to those without. FCGR3B and PRF1 were screened by TCGA analysis.Additionally, significant differences in nine immune cell types were observed between the two risk groups. Notably, a strong positive association with CD8 T cells and a negative relationship with M2 macrophages were exhibited by PRF1. The validation of our nomogram were conducted in vitro and in vivo, and the results showed the correlations between CD8+ T cell and PRF1. ConclusionIn summary, two prognostic genes (FCGR3B and PRF1) were identified, and a prognostic risk model was developed for SKCM. These findings provide a novel approach for the diagnosis and treatment of SKCM.

A novel prognostic index for extranodal natural killer/T-cell lymphoma in the era of pegaspargase/L-asparaginase.

Aim: This multicenter retrospective study aimed to develop a novel prognostic system for extranodal natural killer/T-cell lymphoma (ENKTL) patients in the era of pegaspargase/L-asparaginase. Materials & methods: A total of844 newly diagnosed ENKTL patients were included. Results: Multivariable analysis confirmed that Eastern Cooperative Oncology Group performance status, lactate dehydrogenase, Chinese Southwest Oncology Group and Asia Lymphoma Study Group ENKTL (CA) system, and albumin were independent prognostic factors. By rounding up the hazard ratios from foursignificant variables, a maximum of 7 points wereassigned. The model of Huaihai Lymphoma Working Group-Natural killer/T-cell Lymphoma prognostic index (NPI) was identified with four risk groups and the 5-year overall survival was 88.2, 66.7, 54.3and 30.5%, respectively. Conclusion: Huaihai Lymphoma Working Group-NPI provides a feasible stratification system for patients with ENKTL in the era of pegaspargase/L-asparaginase.

Correlates of stocking naloxone: a cross-sectional survey of community pharmacists.

Provision of take-home naloxone (THN) and overdose education reduces opioid-related mortality. In Australia, from July 2022, all Australian community pharmacies were eligible to supply naloxone for free through the nationalTHN Program. This study aimed to identify naloxone stocking rates and correlates of stocking naloxone across Australian pharmacies. Data were collected from a representative sample of Australian pharmacists in Victoria, New South Wales, Queensland and Western Australia via an online survey. Data collected included pharmacy and pharmacist characteristics and services offered within the pharmacy, including needle and syringe programs, opioid agonist treatment (OAT) and stocking naloxone. Binary probit regression analysis was used to identify correlates of stocking naloxone after controlling for key covariates. Data from 530 pharmacists were analysed. In total, 321 pharmacies (60.6%) reported stocking naloxone. Chain pharmacies and pharmacies that provided OAT had a greater probability of stocking naloxone (B = 0.307, 95%CI: [0.057, 0.556], and B = 0.543, 95%CI: [0.308, 0.777] respectively). Most (61.7%) pharmacists felt comfortable discussing overdose prevention with patients who use prescription opioids, and this comfort was associated with a higher probability of stocking naloxone (B = 0.392, 95%CI: 0.128, 0.655). Comfort discussing overdose prevention with people who use illicit opioids was lower (49.4%) and was not associated with stocking naloxone. There is scope to increase stocking of naloxone and comfort with overdose prevention, particularly through addressing comfort working with higher risk groups such as people who use illicit opioids.

Geriatric nutritional risk index as a predictor for surgical site infection in malignant musculoskeletal tumours of the trunk.

Surgical site infection (SSI) is common in surgery for malignant musculoskeletal tumours, specifically those arising from the trunk. In this study, we investigated the risk factors for SSI after resection of musculoskeletal tumours of the trunk. This retrospective observational study included 125 patients (72 males, 53 females) with musculoskeletal tumours of the trunk in our hospital from 1 April 2008 to 31 August 2023. The incidence of SSI and its risk factors were investigated. SSI was observed in 26% (32/125), and the median time to SSI was 22days. On multivariate analysis, the following were identified as risk factors for SSI: tumours arising caudal to Jacoby's line (hazard ratio [HR] 4.04; P =.0107), soft tissue reconstruction (HR 3.43; P =.0131), and low Geriatric Nutritional Risk Index (GNRI) (HR 0.96; P =.0304). Patients were classified into two risk categories based on GNRI scores: the risk group (GNRI ≤98) and no risk group (>98). The risk group showed a significantly lower overall noninfection survival rate (P =.023). Tumours arising caudal to Jacoby line, soft tissue reconstruction, and lower GNRI were risk factors for SSI. Preoperative and postoperative nutritional interventions should be considered to improve GNRI.

Optimising the use of the prostate- specific antigen blood test in asymptomatic men for early prostate cancer detection in primary care: report from a UK clinical consensus.

Screening is not recommended for prostate cancer in the UK. Asymptomatic men aged ≥50 years can request a prostate-specific antigen (PSA) test following counselling on potential harms and benefits. There are areas of clinical uncertainty among GPs, resulting in the content and quality of counselling varying. To produce a consensus that can influence guidelines for UK primary care on the optimal use of the PSA test in asymptomatic men for early prostate cancer detection. Prostate Cancer UK facilitated a RAND/UCLA consensus. Statements covering five topics were developed with a subgroup of experts. A panel of 15 experts in prostate cancer scored (round one) statements on a scale of one (strongly disagree) to nine (strongly agree). Panellists met to discuss statements before rescoring (round two). A lived experience panel of seven men scored a subset of statements with outcomes fed into the main panel. Of the initial 94 statements reviewed by the expert panel, a final 48/85 (56%) achieved consensus. In the absence of screening, there was consensus on proactive approaches to initiate discussions about the PSA test with men who were at higher-than-average risk. Improvements in the prostate cancer diagnostic pathway may have reduced some of the harms associated with PSA testing; however, several areas of uncertainty remain in relation to screening, including optimal PSA thresholds for referral and intervals for retesting. There is consensus on proactive approaches to testing in higher-than-average risk groups. This should prompt a review of current guidelines.

Advancing bladder cancer management: development of a prognostic model and personalized therapy

BackgroundBladder cancer (BLCA) was recognized as a significant public health challenge due to its high incidence and mortality rates. The influence of molecular subtypes on treatment outcomes was well-acknowledged, necessitating further exploration of their characterization and application. This study was aimed at enhancing the understanding of BLCA by mapping its molecular heterogeneity and developing a robust prognostic model using single-cell and bulk RNA sequencing data. Additionally, immunological characteristics and personalized treatment strategies were investigated through the risk score.MethodsSingle-cell RNA sequencing (scRNA-seq) data from GSE135337 and bulk RNA-seq data from several sources, including GSE13507, GSE31684, GSE32894, GSE69795, and TCGA-BLCA, were utilized. Molecular subtypes, particularly the basal-squamous (Ba/Sq) subtype associated with poor prognosis, were identified. A prognostic model was constructed using LASSO and Cox regression analyses focused on genes linked with the Ba/Sq subtype. this model was validated across internal and external datasets to ensure predictive accuracy. High- and low-risk groups based on the risk score derived from TCGA-BLCA data were analyzed to examine their immune-related molecular profiles and treatment responses.ResultsSix molecular subtypes were identified, with the Ba/Sq subtype being consistently associated with poor prognosis. The prognostic model, based on basal-squamous subtype-related genes (BSSRGs), was shown to have strong predictive performance across diverse clinical settings with AUC values at 1, 3, and 5 years indicating robust predictability in training, testing, and entire datasets. Analysis of the different risk groups revealed distinct immune infiltration and microenvironments. Generally higher tumor mutation burden (TMB) scores and lower tumor immune dysfunction and exclusion (TIDE) scores were exhibited by the low-risk group, suggesting varied potentials for systemic drug response between the groups. Finally, significant differences in potential systemic drug response rates were also observed between risk groups.ConclusionsThe study introduced and validated a new prognostic model for BLCA based on BSSRGs, which was proven effective in prognosis prediction. The potential for personalized therapy, optimized by patient stratification and immune profiling, was highlighted by our risk score, aiming to improve treatment efficacy. This approach was promised to offer significant advancements in managing BLCA, tailoring treatments based on detailed molecular and immunological insights.

Wisdom affinity in the general population

BackgroundWisdom is an important coping resource for difficult and ambiguous life situations. Wisdom trainings have been developed in clinical and non-clinical settings. What has been missing so far are representative data on wisdom affinity from the general population. These are important regarding needs assessments and identification of risk groups with low wisdom affinity and potential problems in coping with difficult and ambiguous life situations.MethodThe study examined a population-representative sample of 2509 persons. Socio-demographic data, presence of chronic and mental illnesses was assessed, and wisdom attitudes by the 12-WD Wisdom Scale. The surveys were carried out by means of interviews and self-report questionnaires at the respondents’ homes, done by an experienced social research company (USUMA GmbH).ResultsOnly 6% of the whole sample appeared to be highly wisdom-affirmative (12-WD mean score 10 on scale 0–10), whereas 4% may appear low wisdom-affirm, due to very low agreement (12 WD mean score 0–4). Most of the moderately wisdom-affirm people had a religious denomination (70.9%), whereas only 57–59% of the high or low wisdom-affirm persons reported religious affiliations. Low wisdom-affirm were most often chronically ill (25%), with mental or physical illness in similar frequency, and had significantly more unemployment times than persons with higher wisdom scores. Wisdom affinity was independent from age, gender and age, household situation, and higher school education.ConclusionIt must be assumed that people with socio-medical risk factors also have impairments in their wisdom-related problem-solving strategies, and that these can be of interest for transdiagnostic wisdom trainings in prevention or rehabilitation, which has shown positive effects.

Genetic analyses and vaccinating risk groups against H5 avian influenza highlight the need for a duty-based code of professional ethics

Genetic analyses and vaccinating risk groups against H5 avian influenza highlight the need for a duty-based code of professional ethics

Cost-effectiveness of seasonal influenza vaccination in WHO-defined high-risk populations in Bangladesh.

Bangladesh carries a substantial health and economic burden of seasonal influenza, particularly among the World Health Organization (WHO)-defined high-risk populations. We implemented a modelling study to determine the cost-effectiveness of influenza vaccination in each of five high-risk groups (pregnant women, children under five years of age, adults with underlying health conditions, older adults (≥60 years), and healthcare personnel) to inform policy decisions on risk group prioritisation for influenza vaccination in Bangladesh. We implemented a Markov decision-analytic model to estimate the impact of influenza vaccination for each target risk group. We obtained model inputs from hospital-based influenza surveillance data, unpublished surveys, and published literature (preferentially from studies in Bangladesh, followed by regional and global ones). We used quality-adjusted life years (QALY) as the health outcome of interest. We also estimated incremental cost-effectiveness ratios (ICERs) for each risk group by comparing the costs and QALY of vaccinating compared to not vaccinating each group, where the ICER represents the additional cost needed to achieve one year of additional QALY from a given intervention. We considered a willingness-to-pay threshold (ICER) of less than one gross domestic product (GDP) per capita as highly cost-effective and of one to three times GDP per capita as cost-effective (per WHO standard). For Bangladesh, this threshold ranges between USD 2462 and USD 7386. The estimated ICERs were USD -99, USD -87, USD -4, USD 792, and USD 229 per QALY gained for healthcare personnel, older adults (≥60), children aged less than five years, adults with comorbid conditions, and pregnant women, respectively. For all risk groups, ICERs were below the WHO willingness-to-pay threshold for Bangladesh. Vaccinating pregnant women and adults with comorbid conditions was highly cost-effective per additional life year gained, while vaccinating healthcare personnel, older adults (≥60), and children under five years were cost-saving per additional life year gained. Influenza vaccination to all target risk groups in Bangladesh would be either cost-saving or cost-effective, per WHO guidelines of GDP-based thresholds.

Prognostic analysis of anoikis-related genes in bladder cancer: An observational study.

Anoikis is proved to play a crucial role in the development of cancers. However, the impact of anoikis on the prognosis of bladder cancer (BLCA) is currently unknown. Thus, this study aimed to find potential effect of anoikis in BLCA. The Cancer Genome Atlas (TCGA)-BLCA and GSE13507 cohorts were downloaded from TCGA and the Gene Expression Omnibus (GEO) databases, respectively. Differentially expressed genes (DEGs) were screened between BLCA and normal groups, which intersected with anoikis-related genes to yield anoikis-related DEGs (AR DEGs). Univariate COX, rbsurv, and multivariate COX analyses were adopted in order to build a prognostic risk model. The differences of risk score in the different clinical subgroups and the relevance between survival rate and clinical characteristics were explored as well. Finally, chemotherapy drug sensitivity in different risk groups was analyzed. In total, 78 AR DEGs were acquired and a prognostic signature was build based on the 6 characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1), where the patients of low-risk group had longer survival time. The survival rate of BLCA patients was significantly differential in different groups of age, stage, smoking history, pathologic-T, and pathologic-N. The IC50 of 56 drugs showed significant differences between 2 risk groups, such as imatinib, docetaxel, and dasatinib. At last, the results of real time quantitative-polymerase chain reaction (RT-qPCR) demonstrated that the expression trend of CALR, HGF, and INHBB was consistent with the result obtained previously based on public databases. Taken together, this study identified 6 anoikis-related characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1) for the prognosis of BLCA patients, providing a scientific reference for further research on BLCA.

Wait-times Benchmarks for risk-based prioritization in Transcatheter Aortic Valve Implantation: a simulation study.

Demand for transcatheter aortic valve implantation (TAVI) has increased in the last decade, resulting in prolonged wait-times and undesirable health outcomes in many health systems. Risk-based prioritization and wait-times benchmarks can improve equitable access to patients. We used simulation models to follow-up a synthetic population of 50,000 individuals from referral to completion of TAVI. Based on their risk of adverse events, patients could be classified as "low-", "medium-" and "high-risk", and shorter wait-times were assigned for the higher risk groups. We assessed the impacts of the size and wait-times for each risk group on waitlist mortality, hospitalization and urgent TAVIs. All scenarios had the same resource constraints, allowing us to explore the trade-offs between faster access for prioritized patients and deferred access for non-prioritized groups. Increasing the proportion of patients categorized as high-risk, and providing more rapid access to the higher-risk groups achieved the greatest reductions in mortality, hospitalizations and urgent TAVIs (relative reductions of up to 29%, 23% and 38%, respectively). However, this occurs at the expense of excessive wait-times in the non-prioritized low-risk group (up to 25 weeks). We propose wait-times of up to 3 weeks for high-risk patients and 7 weeks for medium-risk patients. Prioritizing higher-risk patients with faster access leads to better health outcomes, however this also results in unacceptably long wait-times for the non-prioritized groups in settings with limited capacity. Decision-makers must be aware of these implications when developing and implementing waitlist prioritization strategies.

Acetylation model predicts prognosis of patients and affects immune microenvironment infiltration in epithelial ovarian carcinoma

BackgroundEpithelial ovarian carcinoma (EOC) is a prevalent gynaecological malignancy. The prognosis of patients with EOC is related to acetylation modifications and immune responses in the tumour microenvironment (TME). However, the relationships between acetylation-related genes, patient prognosis, and the tumour immune microenvironment (TIME) are not yet understood. Our research aims to investigate the link between acetylation and the tumour microenvironment, with the goal of identifying new biomarkers for estimating survival of patients with EOC.MethodsUsing data downloaded from the tumour genome atlas (TCGA), genotypic tissue expression (GTEx), and gene expression master table (GEO), we comprehensively evaluated acetylation-related genes in 375 ovarian cancer specimens and identified molecular subtypes using unsupervised clustering. The prognosis, TIME, stem cell index and functional concentration analysis were compared among the three groups. A risk model based on differential expression of acetylation-related genes was established through minimum absolute contraction and selection operator (LASSO) regression analysis, and the predictive validity of this feature was validated using GEO data sets. A nomogram is used to predict a patient's likelihood of survival. In addition, different EOC risk groups were evaluated for timing, tumour immune dysfunction and exclusion (TIDE) score, stemness index, somatic mutation, and drug sensitivity.ResultsWe used the mRNA levels of the differentially expressed genes related to acetylation to classify them into three distinct clusters. Patients with increased immune cell infiltration and lower stemness scores in cluster 2 (C2) exhibited poorer prognosis. Immunity and tumourigenesis-related pathways were highly abundant in cluster 3 (C3). We developed a prognostic model for ten differentially expressed acetylation-related genes. Kaplan–Meier analysis demonstrated significantly worse overall survival (OS) in high-risk patients. Furthermore, the TIME, tumour immune dysfunction and exclusion (TIDE) score, stemness index, tumour mutation burden (TMB), immunotherapy response, and drug sensitivity all showed significant correlations with the risk scores.ConclusionsOur study demonstrated a complex regulatory mechanism of acetylation in EOC. The assessment of acetylation patterns could provide new therapeutic strategies for EOC immunotherapy to improve the prognosis of patients.

Cardiovascular events after invasive pneumococcal disease: a retrospective cohort study

ObjectivesThis study aims to understand the magnitude of and mechanisms underlying the development of cardiovascular events (CVEs) in patients with invasive pneumococcal disease (IPD). We aimed to identify factors that contribute to the occurrence of CVEs within one year after admission and discuss implications for patient care. MethodsA multicentered cohort study, including adult patients from four Dutch hospitals who had a positive blood culture for S. pneumoniae and any type of clinical manifestation between 2012-2020. Disease characteristics and microbiological data were systematically collected from electronic patient files. Main outcome measures were the occurrence of stroke and acute coronary syndromes (ACS). ResultsOf 914 eligible patients, 4.2% experienced a CVE within one year after admission for IPD. ACS mainly occurred in the first two weeks, whereas stroke developed throughout follow-up. While ACS were positively associated with disease severity, the sole independent predictor was alcohol abuse (OR 3.840, 95% CI 1.108-13.303). Although stroke occurred in 6.3% of meningitis cases, the best clinical predictor of stroke was a body temperature >39.5°C at admission (OR 3.117 (1.154-8.423). In the adult IPD population <70 years old, pneumococcal serotypes were the primary predictors of ACS (7F; OR 15.733 (1.812-136.632)) and stroke (22F; OR 7.320 (1.193-44.903)). ConclusionAdverse cardiovascular events were not uncommon after IPD diagnosis and deserve attention, especially in the high risk groups we identified in our study population. Whether specific serotypes play a role in the development towards CVE requires substantiation in further research.

Factors influencing high cardiovascular risk in subpopulation of young adults

Abstract Introduction The cardiovascular risk factors determine the development of early atheriosclerotic lesions, and the susceptibility to their proartheriosclerotic action is programmed by external factors and also those present during fetal development. The occurrence of atherosclerotic risk factors depends on an age. In population of children and young adults it seems reasonable to assess the classical risk factors for atherosclerosis in the connection with such additional given as family history being an indirect surrogate of genetic factors, and a low birth weight. Aim of the study was to categorize the study group into two groups - those who exhibit a low-risk and those who exhibit a high-risk of cardiovascular disease, and to determine the factors characteristic for each risk group. Materials and Methods The study was done on 512 volunteers, students in the following Faculties: Health Care Faculty: Nursing Course (178 / 34,7%), Physiotherapy Course (109 / 21,3%), Obstetrics Course (49 / 9,5%), Faculty of Medicine (176 / 34,3%). The questionnaire on cardiovascular risk factors was constructed. According to the results of its assessment the following groups were divided: the group of high risk (10% of investigated with the highest awarding of points) and the group of low risk (10% of investigated with the lowest awarding of points). Results Significant quantitative and qualitative differences were found between the low-risk and high-risk groups. Groups of the high and low risk did not differ in respect of sexes investigated and in respect of the direction of studies. One ascertained essential differences in variable qualitative and quantitative between the group of the low and high risk. Family history of diabetes, arterial hypertension, cardiovascular diseases, lipid disturbances, stroke were indeed greater in the group of high risk. The low birth weight was significantly lower in the group of high risk (p=0,02). The current and chronic stress status grading according to the punctual scale (0-10) was significantly higher in the group of high risk as compared to the low risk group (p=0,01, p=0,03, respectively). The systolic pressure was significantly higher in the high risk group in comparison to the low risk subjects (p=0,01). Conclusions High cardiovascular risk in subgroup of young adults results from high smoking status, low physical activity, diet and family history of cardiovascular disorders. The numerous cardiovascular risk factors that occur in some students are associated with low birth weight and a positive family medical history. The above observations show the influence of genetic and fetal factors on the development of atherosclerosis. Young adults with high cardiovascular risk are characterized by higher subjective stress level. Quantitative differences in high risk Medical family history

A Microsimulation Model of Mpox (Monkeypox) in Los Angeles County (LAC): Implications for Future Disease Prevention and Control Strategies among Men Who Have Sex with Men (MSM)

Abstract Background The 2022 mpox outbreak in Los Angeles County (LAC) emphasized the need to prepare for emergent infectious disease outbreaks. Vaccination and promotion of sexual risk reduction practices appeared successful in LAC, as mpox cases declined starting in August. Nonetheless, questions persisted regarding the effectiveness of targeting vaccinations and the role of sexual risk reduction in reducing mpox cases. Methods We collaborated with the LAC Department of Public Health to develop a microsimulation for men who have sex with men (MSM). This model tracked mpox dynamics by age, race/ethnicity, and HIV status, and was calibrated and validated against surveillance data. We simulated counterfactual scenarios to understand the effects of variation in vaccination rates, timing of vaccination roll-out, vaccine allocation, and sexual contact rates. Results In the simulation, doubling the vaccination rate reduced cumulative cases over a 40-week time horizon by 13% but would necessitate 88,995 additional doses. Initiating vaccination two weeks earlier decreased cases by 11%, while an 8-week delay yielded a 20% increase in cases. A three-week earlier decrease in sexual contact rates reduced cumulative cases by 60%, while a three-week delay resulted in a 95% increase. Prioritizing people with HIV (PWH) for vaccination reduced cumulative cases while allocating vaccines to a single racial/ethnic group was not effective. Conclusions Our study highlights the significance of policies to support timely vaccination and sexual partnership reduction to address mpox outbreaks among MSM. These findings also underscore the need to target vulnerable risk groups, such as PWH.

Analysis of public policies to combat COVID-19 in the state of Paraná, Brazil

IntroductionThe COVID-19 pandemic had a great impact on several public sectors worldwide, requiring the implementation of public policies in an organized way to contain and control the disease. Thus, this study aimed to analyze public policies to face the COVID-19 pandemic in the State of Paraná, Brazil.MethodsThis was a cross-sectional, retrospective, quantitative survey carried out with data from March 2020 to March 2022 in the twenty-two municipalities that host the local health regions. Data collection was documentary, carried out from the municipal Portal da Transparência website, which is dedicated to making public all expenditures, and epidemiological bulletins released by the Health Department of the state of Paraná. The variables analyzed were New Cases and Deaths, Mortality and Lethality Coefficient, Incidence Rate, Vaccination Coverage, Number of Hospital and ICU beds exclusive to COVID-19, Settled Expenses destined for COVID-19 and coping measures, namely, the Declaration of Public Health Emergency, Curfew, Mandatory use of masks, Businesses closure, Teleworking of risk groups, and Suspension of activities with crowds and of classes. After collection, data underwent descriptive analysis, and subsequently, the correlation of variables was analyzed using the Spearman test. Multiple linear regression was applied using the variable selection method called best subset selection (BSS). The dependent variables listed were incidence rate, new cases and new deaths.ResultsThe results showed that coping measures, as well as the application of resources for the pandemic, were implemented heterogeneously in the municipalities studied, and the progression of the disease, the distribution of beds and vaccination occurred unevenly and may be a reflection of the limited Brazilian national governance. An important correlation was observed between the incidence rate and new deaths with vaccination coverage. In addition, the regression model showed that measures such as mandatory use of masks, closure of shops, suspension of classes, and curfew showed important correlations with the variables incidence rate, cases, and new deaths.DiscussionThe study highlighted the importance of carrying out a robust analysis of public policies to face emergencies of global importance so that government entities are prepared for future crises of great repercussions, such as the COVID-19 pandemic.