High Risk Score Research Articles

The use of telehealth in a large community oncology practice prior to and during the COVID-19 pandemic.

1631 Background:The COVID-19 pandemic prompted implementation of telehealth services in oncology following CMS approval for reimbursement. Using data from a single large US-based community oncology practice, we characterized the adoption of telehealth, evaluated telehealth’s impact on patient transit to the site of care, and the frequency of ER visits and hospitalizations. Methods: A retrospective cohort analysis was conducted using data from January 2019 through June 2022 from the FCS EMR database, IQSS’s RefineIQ database, which captures and standardizes patient treatments for consistent analysis, InfoDive, a reimbursement platform with data on clinic visits, and Oncology Care Model data. The target population included all patients with cancer aged 18 or older under active management at FCS during the study window with at least 60 days of follow-up. Patient disease and demographic characteristics and ER/hospital care visits were compared between telehealth groups, as well as impact of telehealth use on transit time and distance traveled for patients was summarized using descriptive statistics. Results:178,531 patients were analyzed. Median age was 68, with 64% female and 47% white. 97% of patients lived in a metropolitan area, 97% in Florida, and 77% in areas with less than $78,000 median income. Median duration of disease was 41 months, 24% of patients were stage IV and 93% ECOG 0-1. 20% of patients used telehealth, with 81% having only one telehealth use per year. Patients using telehealth, compared to those that did not, were more likely to be white (50% vs 46%), have commercial insurance (30% vs 27%), live in areas where annual median income was > $78,000 (25% vs 22%) and ≥95% of the population graduated high school (31% vs 26%). Telehealth saved a median of 5 miles driven per user annually. Users tended to have more advanced disease than non-users, with a higher proportion of metastatic disease (27% vs 23%), high CMS risk score (16% vs 15%), and line of therapy 2 or greater (10% vs 7%). Users had higher median annual oncology clinic visits both pre- (5 vs 3) and post-telehealth approval (6 vs 5). Hospital admissions after ER visits were more frequent among users both pre- (14% vs 13%) and post-telehealth approval (29% vs 25%). Conclusions: Telehealth was somewhat more likely to be used by patients with cancer in more affluent communities, white patients, patients who had more advanced disease and more frequent clinic and hospital visits. Most patients who used telehealth used it only once, and the low utilization of telehealth had limited impact on patient transit effort to the clinic. This study is limited by its concentration at a single large practice in Florida, the relatively low use of telehealth, retrospective design, and selection bias, as the telehealth population had more advanced disease and likely needed more frequent intervention.

Prediction of Oncotype DX Recurrence Score Based on Systematic Evaluation of Ki-67 Scores in Hormone Receptor-Positive Early Breast Cancer.

Oncotype DX (ODX) predicts the risk of recurrence and benefits of adding chemotherapy for patients with estrogen receptor positive (ER+)/human epidermal growth factor receptor 2 negative (HER2-) early-stage breast cancer. We aimed to develop a simplified scoring system using readily available clinicopathological parameters to predict a high-risk ODX recurrence score (RS) while minimizing reproducibility issues regarding Ki-67 index evaluation methods. We enrolled 300 patients with ER+/HER2- early breast cancer, for whom ODX RS data were available in the test set. Using the QuPath image analysis platform, we systematically evaluated the average, hotspot, and hottest spot Ki-67 scores in the test set. Logistic regression analyses were conducted to establish a predictive scoring system for high-risk ODX RS. An independent validation set comprising 117 patients over different periods was established. Factors such as age ≤ 50 years, invasive ductal carcinoma tumor type, histologic grade 2 or 3, tumor necrosis, progesterone receptor negativity, and a high Roche-analyzed Ki-67 score (> 20) were associated with high-risk ODX RS. These variables were incorporated into our scoring system. The area under the curve of the scoring system was 0.8057. When applied to both the test and validation sets with a cutoff value of 3, the sensitivity of our scoring system was 92%. We successfully developed a scoring system based on the systematic evaluation of Ki-67 scoring methods. We believe that our user-friendly predictive scoring system for high risk ODX RS could help clinicians in identifying patients who may or may require additional ODX testing.

Concordance between risk scales for venous thromboembolism in patients treated in emergency departments.

To evaluate agreement between risk-assessment models for venous thromboembolism (VTE) in patients hospitalized for medical conditions and to analyze variables associated with the decision to prescribe pharmacological thromboprophylaxis in hospital emergency departments (EDs). Conclusions. Prospective observational multicenter cohort study. We included adults attended in 15 hospital EDs who were hospitalized for medical conditions, calculating VTE risk according to the International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) score, the Padua Prediction Score (PPS), and the National Institute for Health and Care Excellence (NICE) score. In addition to assessing interscore concordance, we analyzed variables associated with the prescription of thromboprophylaxis in the ED. A total of 1203 patients were included. The PADUA, IMPROVE, and NICE scales assigned high risk scores for 68.7%, 47.4%, and 69.5% of the patients, respectively. The κ statistic for agreement between the PADUA and NICE scores was 0.80 (95% CI, 0.76-0.84); 102 patients (8.5%) had discordant scores. The κ statistics for agreement between the IMPROVE score and the PADUA and NICE classifications were 0.47 (95% CI, 0.43-0.52) and 0.37 (95% CI, 0.33-0.42), respectively; 322 (26.8%) and 384 patients (31.9%), respectively, had discordant scores. Variables associated with starting thromboprophylaxis in the ED were a diagnosis of acute myocardial infarction or stroke (adjusted odds ratio [aOR], 4.26), immobility in the last 2 months (aOR, 2.19), chronic obstructive pulmonary disease (aOR, 1.97), ischemic heart disease (aOR, 1.51), reduced mobility of 3 days or longer (aOR, 1.14), body mass index (aOR, 1.04), age (aOR, 1.02), recent trauma or surgery (aOR, 0.40), and risk for bleeding (aOR, 0.56). There is disagreement among the recommended models for predicting risk for VTE in patients hospitalized for medical conditions. The basis for emergency physicians' clinical judgment regarding thromboprophylaxis extends beyond risk scales to include multiple risk factors for VTE and bleeding.

Exploring associations between eating habits, gastrointestinal health and perceived stress and anxiety symptoms in adults

Gastrointestinal (GI) disorders are becoming increasingly common in young people in India and globally (1). Diet (eating habits, nutrient intake, and dietary diversity) and mental health (stress and anxiety levels) factors can independently and synergistically regulate gut health through dietary modulation of gut microbiota composition and gut-brain axis-related mechanistic pathways (2-3). However, few studies have investigated the associations between diet, mental health, and GI-related disturbances. Hence, this observational study was conducted to explore the possible effects of eating behaviors and stress and anxiety symptoms on self-reported measures of gastrointestinal health among 18-45-year-old adults in India.A purposive cluster sampling method guided the recruitment of participants (n=407). Two non- consecutive day 24-hour diet recalls were conducted to estimate nutrient intakes and calculate Individual Diet Diversity (IDD) and Food Variety Scores (FVS). Gastrointestinal health was assessed using a validated instrument comprising 35 items related to gastric, small intestine, and colon function, and GI inflammation. Perceived Stress Scale (PSS-10 scores 0 to 40 with higher scores representing higher levels of stress), and Generalized Anxiety Disorder Scale (GAD-7 scores >5 (mild), >10 (moderate), and >15 (severe)) were used to evaluate perceived stress and anxiety (4-5). Socioeconomic status and eating habits were self-reported and the anthropometry measurements were recorded. Multivariable logistic regression analysis was performed using sociodemographic characteristics, anthropometry measurements, eating habits, and stress and anxiety levels as independent (predictor) variables, and composite gastrointestinal health risk scores as the dependent variables.Participants reported mild anxiety (mean (M) = 7.09, standard deviation (SD)= 3.25) and moderate stress (M=18.44; SD= 9.89) with preponderance among females, higher age groups (> 35 years), and lower socioeconomic status. Overall, 38.8% and 45.3% were at high-risk score categories for gastric function and GI inflammation respectively. Higher energy and fat consumption, frequent breakfast skipping, and lower IDDS and FVS scores were associated with higher scores for stress and anxiety. Moreover, participants having moderate to severe anxiety reported a higher frequency of GI symptoms such as indigestion (M= 3.23 SD= 2.1-4.6, p= 0.023), excessive belching (M= 2.36 SD =1.21, p=0.043), and post-meal lower abdominal discomfort and cramps (M= 3.07, SD = 2.22, p < 0.001) as compared to those having nominal/mild anxiety. Age-adjusted regression models showed higher waist circumference (OR= 4.69, 95% CI =1.33- 7.28, p= 0.034), and stress scores (OR= 1.66, 95% CI= 1.32-1.90, p = 0.042), lower IDDS (OR= 2.34, 95% CI=1.80- 2.91, p <0.001) and presence of > 2 co-morbid conditions (OR= 8.12, 95% CI = 5.34- 11.21, p < 0.001) as predictors of higher GI disorder risk scores.The preliminary findings of the study highlight associations between diet, stress, and GI health, presenting opportunities to modulate diet and optimize mental health to prevent and reduce the severity of GI disorders.

Identification of disulfidptosis-related clusters and construction of a disulfidptosis-related gene prognostic signature in triple-negative breast cancer

ObjectiveThis study aimed to explore disulfidptosis-related clusters of triple-negative breast cancer (TNBC) and build a reliable disulfidptosis-related gene signature for forecasting TNBC prognosis. MethodsThe disulfidptosis-related clusters of TNBC were identified based on public datasets, and a comparative analysis was conducted to assess their differences in the overall survival (OS) and immune cell infiltration. Morever, the differentially expressed genes (DEGs) between clusters were recognized. Then, the prognostic DEGs were then chosen. A prognostic signature was constructed by the prognostic DEGs, followed by nomogram construction, drug sensitivity, immune correlation, immunotherapy response prediction, and cluster association analyses. ResultsTwo disulfidptosis-related clusters of TNBC were identified, which had different OS and macrophage infiltration. Moreover, 235 DEGs were identified between two clusters. A prognostic signature was then constructed by five prognostic DEGs including HLA-DQA2, CCL13, GBP1, LAMP3, and SLC7A11. This signature was highly valuable in predicting prognosis. A nomogram was built by risk score and AJCC stage, which could forecast OS accurately. Moreover, patients with high-risk scores exhibited greater sensitivity to chemotherapy drugs such as lapatinib and had a lower immunotherapy response. ConclusionsTwo TNBC clusters linked to disulfidptosis were identified, with different OS and immune cell infiltration. Moreover, a five-disulfidptosis-related gene signature may be a powerful prognostic biomarker for TNBC.

Identification of Diagnosis and Typological Characteristics Associated with Ferroptosis for Ulcerative Colitis via Bioinformatics and Machine Learning

Objective: To investigate and validate ferroptosis genes (FRGs) in ulcerative colitis (UC) for diagnostic, subtype, and biological agent reactivity, with the goal of providing a foundation for the identification of novel therapeutic targets and the rational use of infliximab in clinical practice. Methods: UC datasets and FRGs were selected from the Gene Expression Omnibus (GEO) and FerrDb databases. WGCNA was used to identify characteristic genes of UC. LASSO and SVM models were used to discover key FRGs in UC. A nomogram was constructed for diagnosing UC using logistic regression (LR), We performed internal and external validation for the model. Furthermore, we constructed a hub-gene-signature prediction model for the effectiveness of infliximab in treating UC and deployed it on the website. Finally, the hub gene-drug interaction networks were constructed. Results: Nineteen ferroptosis-related genes associated with UC were identified through bioinformatics analysis. FTH1 and GPX4 were two of the down-regulated genes.The seventeen upregulated genes consisted of DUOX1, DUOX2, SOCS1, LPIN1, QSOX1, TRIM21, IDO1, SLC7A11, MUC1, HSPA5, SCD, ACSL3, NOS2, PARP9, PARP14, LCN2, and TRIB2. Five hub genes, including LCN2, QSOX1, MUC1, IDO1, and TRIB2, were acquried via machine learning. The mean auc of internal validation was 0.964 and 0.965 respectively, after using cross-validation and bootstrap in the training set based on the 5 hub-gene diagnostic models. In the external validation set, the AUC reached 0.976 and 0.858. RF model performs best in predicting infliximab effectiveness. In addition, we identified two ferroptosis subtypes. Cluster A mostly overlaps with the high-risk score group, with a hyperinflammatory phenotype. method: UC datasets and FRGs were selected from the Gene Expression Omnibus (GEO) and FerrDb databases. WGCNA was used to identify characteristic genes of UC. LASSO and SVM models were used to discover key FRGs in UC. A nomogram was constructed for diagnosing UC using logistic regression (LR), We performed internal and external validation for the model. Furthermore, we constructed a 5 hub-gene-signature prediction model for the effectiveness of infliximab in treating UC and deployed it on the web site. Finally, 5 hub gene-drug interaction networks were constructed. Conclusions: This research indicated that five hub genes related to ferroptosis might be potential markers in diagnosing and predicting infliximab sensitivity for UC. result: A total of 362 genes were found to be closely associated with UC . These genes were enriched in immune response, response to stress, oxidoreductase activity, glycerolipid metabolism, ferroptosis, etc. Five ferroptosis-related hub genes were identified through machine learning, including LCN2, QSOX1, MUC1, IDO1, and TRIB2. The mean auc of internal validation was 0.964 and 0.965 respectively, after using cross-validation and booststrap in the training set. In the external validation set, the AUC of the diagnostic model reached 0.858. RF model performs best in predicting infliximab effectiveness. In addition, we identified two ferroptosis subtypes. ClusterA mostly overlaps with the highrisk score group, with a hyperinflammatory phenotype. conclusion: This research indicated that five hub genes related to ferroptosis might be potential markers in diagnosing and predicting infliximab sensitivity for UC.

SCORE2 Screening Tool for Cardiovascular Risk Assessment in Psoriasis-A Case-Control Study.

Background: Psoriasis is a common, T-cell-mediated inflammatory and immune-mediated skin disease. Numerous studies confirmed that patients with psoriasis have a significant frequency of cardiovascular (CV) risk factors and CV diseases (CVDs). Risk stratification is helpful in light of the elevated risk of CVD in psoriasis patients. SCORE2 and SCORE2-OP, a new algorithm derived, calibrated and validated to predict the 10-year risk of first-onset CVD in European populations, enhances the identification of individuals at higher risk of developing CVD across Europe. Objective: Using the SCORE2 and SCORE2-OP scoring systems, the current study objective was to evaluate CV risk in Slovak psoriasis patients and the relationship between CV risk and psoriasis features in a real-world setting. Results: A case-control study was conducted involving 115 outpatients with plaque psoriasis and 66 age- and gender-matched controls with skin conditions other than psoriasis. Patients with psoriasis had significantly higher mean SCORE2 values. In the age group up to 50 years, more psoriasis patients were classified as moderate risk than controls (33.8% vs. 13.6%, p = 0.010); the high-risk category was dominated by psoriasis patients. Analysing the relationship between CV risk and selected variables, we determined, using linear regression, the dependence of the SCORE2 risk score on gender in the age group up to 50 years, on age in both age groups, on waist circumference (WC) in the category up to 50 years and on the duration and severity of psoriasis in both age groups using linear regression. For individuals older than 70, we estimated the SCORE2-OP risk score, with the average risk score being 19.5 ± 4.95. We did not observe controls with a high risk score. Psoriasis patients were more likely to be smokers and had significantly higher mean values for body mass index (BMI), WC, total cholesterol (TC), low-density lipoprotein (LDL) and systolic blood pressure (BP). Conclusions: Because CV risk factors and psoriasis are strongly related, the importance of CV risk stratification is growing, and initiating preventive lifestyle changes or therapeutic interventions in patients with psoriasis is warranted.

Prevalence of unhealthy behaviors and their associations with non-suicidal self-injury, suicidal ideation and suicide attempt among Chinese adolescents

BackgroundUnhealthy lifestyle behaviors among adolescents have emerged as a significant public health concern worldwide, however, there is little investigation on the impact of unhealthy behaviors on non-suicidal self-injury (NSSI), suicidal ideation (SI) and suicide attempt (SA). This study aimed to investigate the prevalence of seven unhealthy behaviors as well as their associations with NSSI, SI and SA, and to explore whether the aforementioned associations differ across sex.MethodsA total of 74,152 adolescents were included in this study via a multi-stage, stratified cluster, random sampling method in 2021. Information about unhealthy behaviors (insufficient physical activity, current smoking, current drinking, excessive screen time, long homework time, insufficient sleep and unhealthy BMI), NSSI, SI, SA and other demographics was collected. Sampling weights were used to estimate the prevalence, and the weighted logistic regression models were performed. Stratified analyses by sex and sensitive analyses were conducted.ResultsOverview, the weighted prevalence of adolescents had more than five unhealthy behaviors were 5.2%, with boys showing a higher prevalence than girls (6.5% vs.3.8%). Current smoking, current drinking, excessive screen use, long homework time, insufficient sleep, and unhealthy BMI were significantly associated with NSSI, SI and SA. Moreover, adolescents with high lifestyle risk scores were associated with an increased risk of NSSI (5–7 vs. 0: OR 6.38, 95% CI 5.24–7.77), SI (5–7 vs. 0: OR 7.67, 95% CI 6.35–9.25), and SA (5–7 vs. 0: OR 9.57, 95% CI 6.95–13.17). Significant sex differences were found in the associations of unhealthy behaviors with NSSI, SI and SA.ConclusionUnhealthy behaviors are quite common among Chinese adolescents. Adolescents with multiple unhealthy behaviors are associated with increased risks of NSSI, SI, and SA. The implementation of school and family-based interventions to promote healthy lifestyles is recommended as a preventive measure against self-injurious behavior and suicidality in adolescents.

Evaluating Cardiovascular Risks: The Platelet Lymphocyte Ratio and the Neutrophil Lymphocyte Ratio As High-Risk Heart Score Predictors in Non-ST Elevation Myocardial Infarction (NSTEMI) and Unstable Angina Patients.

Introduction Acute coronary syndromes (ACS), encompassing non-ST elevation myocardial infarction (NSTEMI) and unstable angina (UA), present significant challenges in risk assessment and management, particularly in resource-constrained environments like India. The burden of cardiovascular diseases in such regions necessitates cost-effective and readily accessible tools for risk stratification. Previous research has emphasized the role of inflammatory markers in coronary artery disease (CAD), prompting investigations into simple and affordable biomarkers for risk assessment. Platelet lymphocyte ratio (PLR) and neutrophil lymphocyte ratio (NLR) have emerged as potential biomarkers for thrombotic activity in cardiac illnesses, offering simplicity, accessibility, and cost-effectiveness in risk assessmentmaking them particularly valuable in resource-poor settings like India, where advanced diagnostic tools may be limited. Objective This study aims to evaluate the effectiveness of PLR and NLR as predictors of high-risk HEART(history, ECG, age, risk factors, and troponin) scores in patients with NSTEMI and UA. Methods A prospective cross-sectional study was conducted at the Saveetha Medical College and Hospitals in Chennai, India, from March 2021 to September 2022. The study included 288 adults diagnosed with NSTEMIor UA, aged 18 years and above. The inclusion criteria comprised patients with confirmed diagnoses of NSTEMI or UA based on clinical symptoms, electrocardiographic findings, and cardiac biomarker elevation. The exclusion criteria encompassed patients with active infections, acute traumatic injuries, end-stage renal disease, malignant neoplasms, and ST-elevation myocardial infarction (STEMI). In addition to the HEART score, PLR, and NLR were computed to assess the prognosis of patients admitted to the Saveetha Medical College and Hospitals. Results The statistical analysis revealed significant correlations between PLR, NLR, and HEART score risk categories. The Pearson's correlation coefficient indicated strong associations between PLR/NLR values and HEART score risk groups, suggesting their potential as predictive markers for adverse clinical outcomes. Additionally, analysis of variance (ANOVA) demonstrated significant differences in PLR/NLR values across different HEART score risk categories, further highlighting their relevance in risk stratification. The effect sizes for these correlations were moderate to large, indicating clinically meaningful associations between PLR/NLR and cardiovascular risk. Conclusion In cases of NSTEMI and UA, PLR and NLR show potential as simple and inexpensive indicators of high-risk patients. By leveraging these inexpensive biomarkers, healthcare providers can enhance risk assessment and prognostication in patients presenting with ACS, facilitating timely interventions and tailored management strategies.

Bioinformatics Identification and Experimental Validation of a Prognostic Model for the Survival of Lung Squamous Cell Carcinoma Patients.

Lung squamous cell carcinoma (LUSC) kills more than four million people yearly. Creating more trustworthy tumor molecular markers for LUSC early detection, diagnosis, prognosis, and customized treatment is essential. Cuproptosis, a novel form of cell death, opened up a new field of study for searching for trustworthy tumor indicators. Our goal was to build a risk model to assess drug sensitivity, monitor immune function, and predict prognosis in LUSC patients. The 19 cuproptosis-related genes were found in the literature, and patient genomic and clinical information was collected using the Cancer Genomic Atlas (TCGA) database. The LUSC patients were grouped using unsupervised clustering techniques, and 7626 differentially expressed genes were identified. Using univariate COX analysis, LASSO regression analysis, and multivariate COX analysis, a prognostic model for LUSC patients was developed. The tumor immune escape was evaluated using the Tumor Immune Dysfunction and Exclusion (TIDE) method. The R packages 'pRRophetic,' 'ggpubr,' and 'ggplot2' were utilized to examine drug sensitivity. For modeling, a 6-cuproptosis-based gene signature was found. Patients with high-risk LUSC had significantly worse survival rates than those with low-risk conditions. The possibility of tumor immunological escape was increased in patients with higher risk scores due to more immune cell inactivation. For patients with high-risk LUSC, we discovered seven potent potential drugs (AZD6482, CHIR.99021, CMK, Embelin, FTI.277, Imatinib, and Pazopanib). In conclusion, the cuproptosis-based genes predictive risk model can be utilized to predict outcomes, track immune function, and evaluate medication sensitivity in LUSC patients.

The N6-methyladenosine methylation landscape stratifies breast cancer into two subtypes with distinct immunological characteristics.

N6-methyladenosine (m6A) methylation modification affects the tumorigenesis and metastasis of breast cancer (BC). This study investigated the association between m6A regulator-mediated methylation modification patterns and characterization of the tumour microenvironment in BC, as well as their prognostic importance. Public gene expression data and clinical annotations were collected from The Cancer Genome Atlas (TCGA) database, the Gene Expression Omnibus website and the METABRIC program. We analysed the genetic expression, gene-gene interactions, gene mutations and copy number variations using R software. The data were screened for risk genes using the Cox risk regression model, and we developed an algorithm for risk score and its predictive value. Compared to adjacent normal tissue, we identified 16 differentially expressed m6A regulators in BC, including six writers and 10 readers. Under unsupervised clustering, two distinguished modification patterns were identified, cluster C1 and C2. Compared to m6A cluster C2, cluster C1 was found to be more involved in immune-related pathways, with a relatively higher immune score and stromal score (P < 0.05). Patients were divided into two groups based on their risk scores for survival analysis. The patients in the high-risk score group had significantly worse overall survival than patients in the low-risk score group, (P < 0.0001). The TCGA database validation revealed the same prognostic tendency. In summary, our study showed distinct m6A regulator modification patterns contribute to the immunological heterogeneity and diversity of BC. The development of m6A gene signatures and the m6A score aid in the prognostic prediction of patients with BC.

End of induction [18F]FDG PET is prognostic for progression-free survival and overall survival in follicular lymphoma patients enrolled in the FOLL12 trial.

To evaluate the reliability of the Deauville score (DS) in therapy response assessment and to define the prognostic value of the metabolic response of end of induction (EOI) [18F]FDG PET (PET) in follicular lymphoma patients. Adult patients with untreated grade 1-3a FL/ stage II-IV enrolled in the multicentre, prospective, phase III FOLL12 trial (NCT02063685) were randomized to receive standard immunochemotherapy followed by rituximab maintenance (standard arm) versus standard immunochemotherapy followed by response-adapted post-induction management (experimental arm). Baseline and EOI PET were mandatory for the study. All PET scans were centralized on the WIDEN® platform and classified according to DS in a blind independent central review. DS1-3 was considered negative (CMR), whereas DS4-5 was considered positive (not CMR). The primary endpoint was PFS. The main secondary endpoint was overall survival (OS). Overall, 807 follicular lymphoma patients-52% women, 89% stage III-IV disease, 40% with a high-risk FLIPI-2 score (3-5)-were enrolled in the study; 729 (90.4%) baseline and EOI PET were available for the analysis. EOI PET was positive (DS4-5) in 88/729 (12.1%) cases. Overall inter-reviewer agreement on PET pos/neg result was 0.92, while agreement on positive and negative cases was 0.77 and 0.94, respectively. The median follow-up was 69months; 247 events were registered in the 5-yr follow-up, with a 5-yr PFS of 67% (95%CI: 63%-70%). The 5-yr PFS rate for PET neg (DS1-3) and PET pos (DS4-5) patients was 71% (95%CI: 67%-75%) and 36% (95%CI: 25%-46%), respectively, with HR 3.49 (95%CI: 2.57-4.72). Five-year PFS was worse as DS increased, with 74% (70%-78%), 58% (48%-67%; HR 1.71; p = 0.001)] and 36% (25%-46%; HR 3.88; p < 0.001) in DS1-2, DS3 and DS4-5, respectively. EOI PET maintained its prognostic value in both the standard and experimental arms. In the whole population, 5-yr OS was 94% (95%CI: 92%-96%), with 96% (95%CI: 94-97) and 82% (95%CI: 72%-89%) in EOI PET negative (DS1-3) and positive (DS4-5), respectively (HR 4.48; p < 0.001). When DS was associated with FLIPI-2, patients with DS3 or DS1-2 with high FLIPI-2 (3-5) experienced worse OS than patients with DS1-2 and low FLIPI-2 (1-2) (p = 0.003). This study shows that DS is a reliable prognostic tool to evaluate EOI PET in follicular lymphoma patients, with prognostic value maintained both in the standard and experimental arms, making metabolic imaging a robust tool to assess response in FL. Moreover, although preliminary, this study provides further information on DS3 patients, who are considered as CMR but show a less favourable PFS than DS1-2 patients.

HEART + score: integrating carotid ultrasound to chest pain assessment in the emergency department.

The HEART score is a clinical decision tool that stratifies patients into categories of low, moderate, and high-risk of major adverse cardiac events in the emergency department (ED) but cannot identify underlying cardiovascular disease in patients without prior history. The presence of atherosclerosis can easily be detected at the bedside using carotid ultrasound. Plaque quantification is well established, and plaque composition can be assessed using ultrasound grayscale pixel distribution analysis. This study aimed to determine whether carotid plaque burden and/or composition correlated with risk of events and could improve the sensitivity of the HEART score in risk stratifying ED patients with chest pain. The HEART score was calculated based on history, electrocardiogram, age, risk factors, and initial troponin in patients presenting to the ED with chest pain (n = 321). Focused carotid ultrasound was performed, and maximum plaque height and total plaque area were used to determine plaque burden (quantity). Plaque composition (% blood, fat, muscle, fibrous, calcium-like tissue) was assessed by pixel distribution analysis. Carotid plaque height and area increased with HEART score (p < 0.0001). Carotid plaque % fibrous and % calcium also increased with HEART score. The HEART score had a higher area under the curve (AUC = 0.84) in predicting 30-day events compared to the plaque variables alone (AUCs < 0.70). Integrating plaque quantity into the HEART score slightly increased test sensitivity (62-69%) for 30-day events and reclassified 11 moderate-risk participants to high-risk (score 7-10). Plaque burden with advanced composition features (fibrous and calcium) was associated with increased HEART score. Integrating plaque assessment into the HEART score identified subclinical atherosclerosis in moderate-risk patients.

Simplified Risk Stratification Model for Patients With Waldenström Macroglobulinemia.

Patients with Waldenström macroglobulinemia (WM) have disparate outcomes. Newer therapies have emerged since the development of International Prognostic Scoring System, and MYD88L265P mutation is now frequently assessed at diagnosis, warranting reexamination of the prognostic parameters. We reviewed records of 889 treatment-naïve patients with active WM, consecutively seen between January 01, 1996, and December 31, 2017, to identify clinical predictors of overall survival (OS) in univariate analyses. Patients with complete data for the parameters significant on the univariate analyses (n = 341) were included in a multivariable analysis to derive a prognostic model, subsequently validated in a multi-institutional cohort. In the derivation cohort (n = 341), age (hazard ratio [HR], 1.9 [95% CI, 1.2 to 2.1]; P = .0009), serum lactate dehydrogenase (LDH) above upper limit of normal (HR, 2.3 [95% CI, 1.3 to 4.5]; P = .007), and serum albumin <3.5 g/dL (HR, 1.5 [95% CI, 0.99 to 2.3]; P = .056) were independently prognostic. By assigning a score of 1 point each to albumin <3.5 g/dL (HR, 1.5) and age 66-75 years (HR 1.4) and 2 points for age >75 years (HR, 2.6) or elevated LDH (HR, 2.3), four groups with distinct outcomes were observed on the basis of the composite scores. Five-year OS was 93% for the low-risk (score 0), 82% for low-intermediate risk (score 1), 69% for intermediate-risk (score 2), and 55% for the high-risk (score ≥3; P < .0001) groups. In the validation cohort (N = 335), the model maintained its prognostic value, with a 5-year OS of 93%, 90%, 75%, and 57% for the four groups, respectively (P < .0001). Modified Staging System for WM (MSS-WM), utilizing age, albumin, and LDH is a simple, clinically useful, and externally validated prognostic model that reliably risk-stratifies patients with symptomatic WM into four groups with distinct prognosis.

Clinically relevant immune subtypes based on alternative splicing landscape of immune-related genes for lung cancer advanced PPPM approach.

Alternative splicing (AS) occurs in the process of gene post-transcriptional process, which is very important for the correct synthesis and function of protein. The change of AS pattern may lead to the change of expression level or function of lung cancer-related genes, and then affect the occurrence and development of lung cancers. The specific AS pattern might be used as a biomarker for early warning and prognostic assessment of a cancer in the framework of predictive, preventive, and personalized medicine (PPPM; 3PM). AS events of immune-related genes (IRGs) were closely associated with tumor progression and immunotherapy. We hypothesize that IRG-AS events are significantly different in lung adenocarcinomas (LUADs) vs. controls or in lung squamous cell carcinomas (LUSCs) vs. controls. IRG-AS alteration profiling was identified to construct IRG-differentially expressed AS (IRG-DEAS) signature models. Study on the selective AS events of specific IRGs in lung cancer patients might be of great significance for further exploring the pathogenesis of lung cancer, realizing early detection and effective monitoring of lung cancer, finding new therapeutic targets, overcoming drug resistance, and developing more effective therapeutic strategies, and better used for the prediction, diagnosis, prevention, and personalized medicine of lung cancer. The transcriptomic, clinical, and AS data of LUADs and LUSCs were downloaded from TCGA and its SpliceSeq databases. IRG-DEAS events were identified in LUAD and LUSC, followed by their functional characteristics, and overall survival (OS) analyses. OS-related IRG-DEAS prognostic models were constructed for LUAD and LUSC with Lasso regression, which were used to classify LUADs and LUSCs into low- and high-risk score groups. Furthermore, the immune cell distribution, immune-related scores, drug sensitivity, mutation status, and GSEA/GSVA status were analyzed between low- and high-risk score groups. Also, low- and high-immunity clusters and AS factor (SF)-OS-related-AS co-expression network and verification of cell function of CELF6 were analyzed in LUAD and LUSC. Comprehensive analysis of transcriptomic, clinical, and AS data of LUADs and LUSCs identified IRG-AS events in LUAD (n = 1607) and LUSC (n = 1656), including OS-related IRG-AS events in LUAD (n = 127) and LUSC (n = 105). A total of 66 IRG-DEAS events in LUAD and 89 IRG-DEAS events in LUSC were identified compared to controls. The overlapping analysis between IRG-DEASs and OS-related IRG-AS events revealed 14 OS-related IRG-DEAS events for LUAD and 16 OS-related IRG-DEAS events for LUSC, which were used to identify and optimize a 12-OS-related-IRG-DEAS signature prognostic model for LUAD and an 11-OS-related-IRG-DEAS signature prognostic model for LUSC. These two prognostic models effectively divided LUAD or LUSC samples into low- and high-risk score groups that were closely associated with OS, clinical characteristics, and tumor immune microenvironment, with significant gene sets and pathways enriched in the two groups. Moreover, weighted gene co-expression network (WGCNA) and nonnegative matrix factorization method (NMF) analyses identified four OS-relevant subtypes of LUAD and six OS-relevant subtypes of LUSC, and ssGSEA identified five immunity-relevant subtypes of LUAD and five immunity-relevant subtypes of LUSC. Interestingly, splicing factors-OS-related-AS network revealed hub molecule CELF6 was significantly related to the malignant phenotype in lung cancer cells. This study established two reliable IRG-DEAS signature prognostic models and constructed interesting splicing factor-splicing event networks in LUAD and LUSC, which can be used to construct clinically relevant immune subtypes, patient stratification, prognostic prediction, and personalized medical services in the PPPM practice. The online version contains supplementary material available at 10.1007/s13167-024-00366-4.

#1484 Development of a relapse risk score in patients with ANCA-associated vasculitis treated with cyclophosphamide induction

Abstract Background and Aims Cyclophosphamide (CYC), together with rituximab, is the mainstay for induction therapy in ANCA-associated vasculitis (AAV) [1]. The risk factors influencing the likelihood of relapse in individuals undergoing CYC induction are still unclear. This study aims to score the more robust predictors of relapse in these patients, thereby building a clinically useful tool. Method Patients' characteristics were pooled from three cohorts from Italy, Ireland, and Spain. Eligibility criteria were a diagnosis of GPA, MPA, or EGPA, age &amp;gt;18 years, induction treatment with CYC [either as intravenous therapy (IV) and/or oral], and at least 12 months of follow-up. Baseline assessment included clinical data, laboratory testing, and assessment of manifestations of GPA, MPA, and EGPA in each organ system according to the Birmingham Vasculitis Activity Score (BVAS). Relapse was defined as the presence of ≥1 new vasculitis manifestation after a remission lasting at least 3 months; remission was defined as no disease activity (BVAS=0) irrespective of the glucocorticoid use. Time-to-remission and relapse-free survival probabilities were estimated using the Kaplan-Meier method. A multivariate Cox analysis, including the statistically significant factors at a previous univariate analysis, was employed to develop a practical prognostic score, defined as “Relapse Evaluation And Cyclophosphamide Treatment (REACT) score”, in which each independent predictor was assigned a number of weighted points proportional to its β regression coefficient. Results The score development cohort comprised 505 patients. 223 patients (44.2%) had MPA, 217 (43.0%) GPA, and 65 (12.9%) EGPA. 183 patients (36.2%) experienced a relapse, with a median time to relapse of 33 months (IQR: 13-61). A multivariate Cox regression analysis proved that PR3-ANCA (HR: 1, 30, 95% CI 1, 01-1, 87), IV CYC (HR: 1.78, 95% CI 1.31-2.41), cardiovascular involvement (HR: 1.82, 95% CI 1.01-3.25), arthralgias/arthritis (HR: 1.46 95% CI 1.08-1.98) and the absence of rapidly progressive glomerulonephritis (HR: 1.37, 95% CI 1.02-1.85) were all independent risk factors of relapse. These variables were used to build the REACT score, with each item receiving 1 point except for CV involvement and IV CYC, each receiving 2 points. We then identified three risk categories according to the score of each patient (Fig. 1A). We identified 138 (27%) patients with low risk of relapse (score 0-1), 252 (49%) with an intermediate risk (score 2-3), and 115 patients (22%) with a high risk (score 4-7). These three groups showed different relapse probabilities on Kaplan-Meier analysis (pairwise comparisons between the groups were all statistically significant) (Fig. 1B). Conclusion The REACT score can be employed at diagnosis to predict the risk of relapse in patients with AAV treated with cyclophosphamide induction. Its value needs to be confirmed in external cohorts.

#2559 “Remote software technology to assist clinical decision in vascular access surveillance: single UK centre experience”

Abstract Background and Aims Optimal arteriovenous access monitoring and surveillance aims for early detection of dysfunctional access, enabling pre-emptive referral for angioplasty or surgery to prevent access loss or thrombosis. Here we compared the addition of remote software surveillance to standard clinical care in our units. Method From January–December 2023 we conducted a 12-month prospective study of maintenance hemodialysis (HD) patients. We used Vasc-Alert software technology to assist clinical decision making for vascular access (VA) surveillance in 2 out of 5 HD units. In these units, vascular access risk score was calculated using Vasc-Alert software platform from routinely collected data from the dialysis procedure as previously described [1]. Patients with high Vasc-Alert access risk score (≥7) underwent clinical assessment and were referred for fistulogram if they met the relevant KDOQI criteria [2]. The following variables were collected from all 5 HD units: baseline permanent VA prevalence, subsequent VA events (stenosis or thrombosis), access abandonment (i.e. unsalvageable access loss), complication free days (CFD)-extended over one year (defined as days without serious vascular access events, radiological or surgical intervention, VA infection, hospitalisation or use of central venous catheter). Data was collected on patients who were pre-emptively referred for diagnostic fistulogram ± angioplasty but thrombosed while awaiting intervention. Median time interval from the date of fistulogram request till the date of confirmed thrombosed access was calculated. Comparison between HD units with Vasc-Alert use (Group 1) or without (Group 2) was performed using appropriate statistical tests depending on the type and distribution of the data. Survival analysis of post-intervention primary patency rate was conducted at 3 and 6 months defined as the time from the index procedure until the next access thrombosis or reintervention [3]. Results There were 81 (53.6%) patients with permanent VA in group 1and 201 (59.3%) patients in group 2at the start of the study. We recorded 23 (28.4%) episodes of stenosis and 6 (7.4%) episodes of thrombosis in Group 1 and 40 (19.9%) episodes of stenosis and 21 (10.4%) episodes of thrombosis in Group 2 (p value 0.121 and 0.432, respectively). In Group 2, 11 patients (5.5%) developed repeated stenosis and 2 patients (1%) repeated thrombosis. In Group 1, 5 /6 (83%) cases preemptively referred for diagnostic fistulogram ± angioplasty developed thrombosis whilst awaiting elective intervention, compared with 4/21 (19%) in group 2 (p value = 0.008) (Fig. 1). The median time interval from the date of fistulogram request till date of thrombosed VA was 26 days with Interquartile range (IQR 25-75%) of 21-34 days. Group 1 had better post-intervention primary patency rate of VA (Fig. 2) and longer CFD-extended compared to group 2 (p values &amp;lt; 0.001 and 0.002 respectively) (Table 1). Conclusion Our study shows that integrating Vasc-Alert technology into the VA surveillance program was associated with improved early detection of high-risk access, higher primary patency rates and CFD-extended. Additionally, our data emphasizes the need to enhance interventional radiology capacity for timely access intervention, to realise the true potential of Vasc-Alert technology in prevent access thrombosis.

#1450 Polygenic risk score of native IgA nephropathy predicts risk of post-transplant disease recurrence

Abstract Background and Aims IgA nephropathy (IgAN) is a polygenic immune-mediated progressive glomerular disease. Recent GWAS reported that high genome-wide polygenic risk score (IgAN GPS), including 1 249 077 variants mapping to systemic immune pathways, was associated with risk of end stage kidney disease (ESKD). Post transplant (KTx) IgAN recurrence occurs in 30% of cases and it is a major cause of graft loss. Pathogenesis and predictors of IgAN recurrence are still not well defined. Herein, we studied the role of native IgAN GPS and clinical factors in predicting post-KTx IgAN recurrence and graft failure in a large cohort of KTx recipients. Method Four thousand one hundred eighty six KTx recipients from 6 sites were genome wide genotyped and imputed against multi-ancestry reference panels, retrieving &amp;gt;10 million variants. In each recipient, native IgAN GPS was computed and standard-normalized (i.e. expressed in units of standard deviations from the mean distribution in matched controls). Native kidney disease diagnosis, clinical parameters, and post-KTx outcome data were retrieved retrospectively from clinical charts. The IgAN GPS was tested as predictor of native IgAN in the entire KTx cohort in a logistic regression model adjusted for sex, age, recruitment site, and first 5 PCs. IgAN GPS was tested as predictor of age at transplantation (proxy for age at ESKD) among KTx recipients with native IgAN in a linear regression model adjusted for sex, recruitment site, and first 5 PCs. In recipients with native IgAN, recipient and donor parameters were individually tested as predictors for time to IgAN recurrence and time to graft failure in Cox proportional hazards models adjusted for recruitment site and first 5 PCs. Predictors with P-value &amp;lt; .1 were included in the multivariable models. Recipient IgAN GPS was added to the clinical models and tested for prediction of time-to IgAN recurrence, and, among KTx recipients with IgAN recurrence, of time-to subsequent graft failure. Results Three hundred sixty nine KTx recipients were affected by native IgAN, 271 were of male sex, median age at transplantation was 45 years, and 149 received a living donor KTx. Over a median follow-up time of 46 months, 96 IgAN recurrence events occurred, and, among KTx recipients with recurrent IgAN, 27 subsequent graft failure events occurred after 100 months post KTx. IgAN GPS significantly predicted native IgAN cases among all KTx recipients (OR [95% CI]: 1.95 [1.76,2.16], p = 5.60E-07, AUROC 0.73), and lower age at transplantation among recipients with native IgAN (beta [s.e.]: −1.11[0.55], p = 0.04). Clinical model for IgAN recurrence included age, sex, year of transplant, HLA mismatch, recruitment site, and first 5 PCs; clinical model for graft failure included age, sex, year of transplant, HLA mismatch, type of donation, donor age, sex, rejection events, recruitment site, and first 5 PCs. At the multivariable analysis, IgAN GPS, lower age at transplantation, lower HLA mismatch, and higher year of transplant were independently associated with time to IgAN recurrence (Fig. 1a). Among KTx recipients with recurrent IgAN, higher IgAN GPS predicted time-to graft failure independently from clinical factors (Fig. 1b), but not in non-recurrent cases. Conclusion In the KTx setting, IgAN GPS was an independent predictor of IgAN recurrence, suggesting shared genetic susceptibility between native and recurrent IgAN. In addition, associations of IgAN GPS with lower age at transplantation, and with graft failure among recurrent IgAN cases, suggest that IgAN GPS may be predictive of a more aggressive native as well as recurrent disease. Associations with lower HLA mismatch advocate donor-recipient genetic similarities as potential additional predictors of IgAN recurrence. These data, which need external validation, may provide potential new insights into the pathobiology and prediction of recurrent IgAN.

The Accumulative Effect of Multiple Postnatal Risk Factors with the Risk of Being Overweight/Obese in Late Childhood.

Most past studies focused on the associations of prenatal risk factors with the risks of childhood overweight/obesity. Instead, more postnatal risk factors are modifiable, with less knowledge of their cumulative effects on childhood obesity. We analyzed data of 1869 children in an Australian birth cohort. Key postnatal risk factors included: maternal and paternal overweight/obesity during the child's infancy, tobacco exposure, low family socioeconomic score, breastfeeding duration < 6 months, early introduction of solid foods, and rapid weight gain during infancy. The risk score was the sum of the number of risk factors. The primary outcome is overweight/obesity in late childhood (11-12 years); secondary outcomes are high-fat mass index (FMI), body fat percentage (BF%), and waist-to-height ratio (WHtR). Poisson regression models were used in the analyses. Children with higher risk scores had higher risks of overweight/obesity (p-for-trends < 0.001). After adjusting covariates, compared with those with 0-1 risk factors, children with 4-6 risk factors had 4.30 (95% confidence interval: 2.98, 6.21) times higher risk of being overweight/obesity; the relative risks for high FMI, BF%, and WHtR were 7.31 (3.97, 13.45), 4.41 (3.00, 6.50), and 6.52 (3.33, 12.74), respectively. Our findings highlighted that multiple postnatal risk factors were associated with increased risks of being overweight/obesity in late childhood.

On the Development of a Threat Driven Model for Campus Network

Technology as the foundation of almost every aspect of our lives has come to stay and moving with the trend is now the order of the day. Educational institutions are not left out in the advancement struggle. The use of these technologies in educational institutes comes with its attendant evil including but not limited to ransomware attack, denial of service attack, phishing attack, malware attack and the likes. This research therefore, aims to model the different attack types common to campus network. The traffic used for modelling the attack was collected from universities in the western part of Nigeria and the STRIDE and DREAD models were employed. The analysis showed that DoS (fail to auth to VPN to lock out user accounts) had the highest risk score (43) while DoS (complex search queries, CPU exhaustion) had the lowest score (26).