Risk Categories Research Articles

A Novel Score to Predict Individual Risk for Future Alzheimer’s Disease: A Longitudinal Study of the ADNI Cohort

Background: Identifying high-risk individuals with mild cognitive impairment (MCI) who are likely to progress to Alzheimer’s disease (AD) is crucial for early intervention. Objective: This study aimed to develop and validate a novel clinical score for personalized estimation of MCI-to-AD conversion. Methods: The data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study were analyzed. Two-thirds of the MCI patients were randomly assigned to a training cohort (n = 478), and the remaining one-third formed the validation cohort (n = 239). Multivariable logistic regression was performed to identify factors associated with MCI-to-AD progression within 4 years. A prediction score was developed based on the regression coefficients derived from the logistic model and tested in the validation cohort. Results: A lipidomics-signature was obtained that showed a significant association with disease progression. The MCI conversion scoring system (ranged from 0 to 14 points), consisting of the lipidomics-signature and five other significant variables (Apolipoprotein ɛ4, Rey Auditory Verbal Learning Test immediate and delayed recall, Alzheimer’s Disease Assessment Scale delayed recall test, Functional Activities Questionnaire, and cortical thickness of the AD signature), was constructed. Higher conversion scores were associated with a higher proportion of patients converting to AD. The scoring system demonstrated good discrimination and calibration in both the training cohort (AUC = 0.879, p of Hosmer-Lemeshow test = 0.597) and the validation cohort (AUC = 0.915, p of Hosmer-Lemeshow test = 0.991). The risk classification achieved excellent sensitivity (0.84) and specificity (0.75). Conclusions: The MCI-to-AD conversion score is a reliable tool for predicting the risk of disease progression in individuals with MCI.

Comparing Cardiovascular Risk Classification of U.S. Adults According to Pooled Cohort Equations and PREVENT Equations: Cross-Sectional Analysis of the National Health and Nutrition Examination Survey.

Comparing Cardiovascular Risk Classification of U.S. Adults According to Pooled Cohort Equations and PREVENT Equations: Cross-Sectional Analysis of the National Health and Nutrition Examination Survey.

Comparison of disease and risk classifications of AML before and after incorporation of NGS analysis of bone marrow samples.

Mutation profiling by next-generation sequencing (NGS) has facilitated understanding of the molecular pathogenesis of acute myeloid leukemia (AML), and has been incorporated into the new disease classification (International Consensus Classification; ICC) and risk classification (European LeukemiaNet [ELN] 2022; ELN2022). We compared disease subtypes between the previous disease classification (4th edition of the WHO classification; WHO-4) and the ICC in 91 patients with AML diagnosed at our institution. We also compared disease risk classifications using the previous risk classification (ELN2017) and the ELN2022. Targeted sequencing of bone marrow samples was conducted at Kyoto University. We found that entities under AML with recurrent genetic abnormalities were well-established, with almost no change from the WHO-4 to the ICC. In contrast, 16.7% of cases of AML, not otherwise specified in the WHO-4 were reclassified into AML with mutated TP53, and 36.7% were reclassified into AML with myelodysplasia-related gene mutations or cytogenetic abnormalities per the ICC. Meanwhile, the ELN2017 and ELN2022 showed no difference in concordance indexes in multivariate Cox regression analysis for progression-free and overall survival. The superiority of the ELN2022 over the ELN2017 could not be confirmed in our single-center retrospective study, and further investigation including multicenter prospective studies is needed.

An Improved Adaptive Neuro-fuzzy Inference Framework for Lung Cancer Detection and Prediction on Internet of Medical Things Platform

It has become increasingly difficult for medical practitioners to recognize illness in recent years due to the emergence of new diseases from their myriad causes on a daily basis. Due in large part to inadequate diagnostic and monitoring infrastructure, a substantial amount of illness and death are associated with lung cancer (LC). The aim of the paper is to find lung cancer early and help patients receive curative treatment. Quitting smoking or never starting is the best way to mitigate the potential for disease-related death. As a result, cutting-edge detection and monitoring technologies must be developed to enable rapid, accurate, and timely diagnosis. Fuzzy logic (FL) is one of the best approaches to modeling complex and uncertain systems; therefore, it helps us deal with these challenges. Fuzzy expert system for lung cancer [FES-LC] detection and prediction on Internet of medical things (IoMT) is employed to overcome the challenges. Hence, an enhanced adaptive neuro-fuzzy inference framework [ANF-IF] is proposed in the current research. The cloud-based application of an adaptive neuro-fuzzy inference system yields four risk categories: not at risk, slightly at risk, moderately at risk, and severely at risk. New methods and theoretical frameworks have made it possible to diagnose LC in its earliest stages with the help of magnetic nanoparticles (MNPs), which allow researchers to overcome the limitations of conventionally slow diagnostic efficiency. The proposed system exhibits a precision of 93.4%, accuracy of 95.1%, specificity of 90.6%, sensitivity of 92.8%, false positive rate of 0.22%, false negative ratio of 0.18%, and classification accuracy of 98.2%. The proposed method outperforms all methods and provides better lung cancer detection accuracy than others.

Phonocardiogram Signal Analysis Based Premature Cardiac Influence Detection using Resnet50 CNN for Public Health Protection

Phonocardiogram (PCG) signal analysis plays a crucial role in the early detection of cardiac abnormalities, which is essential for public health protection. The premature disease prediction is tedious because the feature analysis takes place dimensionality problems which leads poor accuracy. The prevailing ensemble learning models’ methods doesn’t concentrate disease margin facts and properties during classification produce higher false rate because for adjusting feature margins gets lower accuracy. To resolve this problem, we propose a efficient Fuzzy c-means feature modality based Resnet50-RNN to detect premature cardiac influence detection for improving public health. The research proposes a method for premature cardiac influence detection using a ResNet50 Convolutional Neural Network (CNN) model for early prediction of heart disease. To address the issue of imbalanced data, Synthetic Minority Oversampling Technique (SMOTE) is employed for preprocessing. The Cardiac Disease Influence Rate (CDIR) is then used to identify the maximum deficiency-affected feature margins. Fuzzy c-means is utilized to select the mutual features associated with the heart disease influence rate. The ResNet50 CNN model is employed for classification, enabling the prediction of disease margins by risk category. The proposed system effectively identifies the disease based on the disease-affected scaling margin, leading to early disease impact prediction with higher accuracy, specificity, F1-measure, and lower false rates compared to other existing systems. The implementation also demonstrates reduced time complexity.

The abundance and analytical characterization of microplastics in the surface water of Haryana, India.

Microplastic (MP) contamination has become a serious environmental concern that affects terrestrial environments, aquatic ecosystems, and human health. The current study assesses the presence, abundance, and morphology of MPs present in the surface water of Rohtak district, Haryana, India, which is rapidly undergoing industrialization. While the morphological studies of MPs were conducted through stereo microscopy and field emission-scanning electron microscopy (FE-SEM), the elemental composition of polymers was analyzed through attenuated total reflectance-Fourier transform infrared (ATR-FTIR). The results revealed that the surface water was significantly contaminated by polyethylene, polypropylene, and polystyrene. Moreover, the abundance of MPs was found to be 16-28 particles/L with an average value of 23 particles/L. Most of the MPs had fibrous morphology with the specifics being, fibers (43.9%), fragments (23.7%), films (17%), and pellets (15.4%). The MPs exhibited a size range of 0.61-4.87 mm, with an average size measured at 2.03 ± 0.04 mm. Also, the MP pollution load index values for the surface water bodies were found to be below 10, indicating a low risk category. Though currently designated as "low risk," it is important that mitigation strategies be brought over at this juncture to further prevent the deterioration of quality of water. Thus, this study not only intends to bring forth the impact of human activities, industrial waste, open waste dumping, and inadequate municipal waste management practices on increasing MP concentration but also highlights the sustainable alternatives and strategies to address this emerging pollutant in urban water systems. For further prevention, the implementation of stringent regulations and on-site plastic waste segregation is a critical component in preventing the disposal of plastic waste in surface water bodies. RESEARCH HIGHLIGHTS: The abundance of MPs was found to be 16-28 particles/L, with an average value of 23 particles/L. The surface water bodies in Rohtak district fall into the hazard categories of low risk with values less than 10. The overall MP concentration in water, across all five areas, based on color was in order: white/transparent (39.1%), black (15%), gray (9.1%), green (8.7%), blue (7.8%), red (7.8%), orange (6.3%), and yellow (6.1%). The dominant polymers were polyethylene (PE) (42%) and polypropylene (41%) as determined by FTIR spectroscopy.

Abstract P188: Prevalence of AHA Pediatric Risk Categories in Youth with Hypertension Disorders: a SUPERHERO Analysis

Background: Cardiovascular (CV) risk factors in childhood contribute to the development of CV disease (CVD) later in life. In higher risk groups of youth, increased risk of CV events begins early in adulthood. The American Heart Association (AHA) 2019 CV Risk Reduction in High-Risk Pediatric Patients scientific statement uses medical diagnoses and CV health factors to classify patients into High, Moderate, and At-risk categories. The prevalence of these risk categories in youth with hypertension (HTN) disorders is unknown. Methods: Cross-sectional analysis of baseline electronic health record data from youth referred for HTN disorders in the multisite retrospective SUPERHERO Registry. Inclusion criteria were age <19 years and index subspecialty clinic visit for a HTN disorder by ICD-10 codes from 1/1/2015–12/31/2023. Exclusion criteria were kidney failure on dialysis, kidney transplantation, or pregnancy by ICD-10 codes. We report prevalence of AHA Pediatric Risk Category (High, Moderate, At-risk). We used clinic BP and 2017 AAP Clinical Practice Guidelines to define HTN, clinic BMI percentile to define obesity, and ICD-10 codes to define other risk category medical diagnoses. We report frequencies and proportions in this descriptive analysis. Results: Of 9356 participants, 3544 (37.9%) were female and 5464 (58.4%) were ≥13 years. At the index visit, 5563 participants (63.5%) were hypertensive. A total of 634 participants (6.8%) were classified as High risk, 6100 participants (65.2%) as Moderate risk, and 1034 participants (11.1%) were in the At-risk group. There were 1588 participants (17.0%) not classified into a risk category with available data. Conclusions: In a large cohort of youth with HTN disorders, we found that over 80% of participants were in an AHA pediatric risk category with 63.5% of participants having either primary or secondary HTN. Our findings suggest that if only HTN is used to identify youth at early CV risk, we will miss youth who may benefit from early CV health factor intervention. Next steps include confirming our findings using laboratory and prescription data in defining risk categories and investigating the association of AHA pediatric risk category with target organ injury using laboratory and echocardiogram data.

Abstract P409: Cardiovascular Health Assessment and Intervention by AHA Pediatric Risk Category in Youth with Hypertension Disorders: a SUPERHERO Analysis

Background: Early intervention for modifiable cardiovascular (CV) health factors may decrease incidence of CV disease later in life, though whether youth at higher risk are more likely to have CV assessment and intervention is unknown. Our objective was to determine CV health initial assessment and intervention including echocardiogram (ECHO) order, anti-hypertensive medication prescription, and dietician referral by participant risk category from the 2019 American Heart Association (AHA) CV Risk Reduction in High-Risk Pediatric Patients scientific statement in a large cohort of youth with hypertension (HTN) disorders. Methods: Cross-sectional analysis of baseline data from the SUPERHERO Registry, a multisite retrospective cohort of youth referred for HTN disorders. Inclusion criteria were age <19 years and HTN disorder identified by ICD-10 codes from 1/1/2015–12/31/2023 at index visit to a subspecialty clinic. Exclusion criteria were kidney replacement therapy by dialysis or transplant or pregnancy by ICD-10 codes. Exposure was AHA Pediatric Risk Category (High, Moderate, At-risk). We used clinic BP by U.S. guidelines, clinic BMI percentile to define obesity, and ICD-10 codes to define other risk category medical diagnoses. Outcomes were ECHO order, anti-hypertensive medication prescription, and dietician referral. We used unadjusted generalized linear models. Results: Of 9356 participants, 1034 (11.1%), 6100 (65.2%), and 634 (6.8%) participants were categorized as High, Moderate, and At-risk groups. Overall, 3053 (32.6%) of participants had an ECHO order, 943 (16.4%) had anti-hypertensive medication prescribed, and 661 (7.1%) had a dietician referral. With At-risk group as reference, participants in High or Moderate risk groups were more likely to have an anti-hypertensive medication prescription (RR 3.12; 95% CL 2.23 to 4.36, RR 1.38; 95% CL 1.02 to 1.85). Participants in the Moderate risk group were more likely to have an ECHO order (RR 1.24; 95% CL 1.06 to 1.44). No difference between risk groups was seen for dietician referral. Conclusions: Among a large cohort of youth with HTN disorders, we found that higher risk groups were more likely to have an anti-hypertensive medication prescribed compared to lower risk group. The overall proportion of participants with medication prescriptions, ECHO orders, or dietician referrals were low. Next steps include investigating the association of risk category with target organ injury.

Evidence-based guidelines for the interpretation of the 9-item Concise Health Risk Tracking - Self-Report (CHRT-SR9) measure of suicidal risk.

The 9-item Concise Health Risk Tracking - Self-Report (CHRT-SR9) is a widely used patient-reported outcome measure of suicidal risk. The goal of this article is to provide an evidence-based interpretation of the CHRT-SR9 total score in terms of four clinically actionable categories of suicidal risk (none, mild, moderate, and severe). Data from two large programs involving adolescents and adults were combined in this paper. In these studies, the CHRT-SR9 was anchored against an independent measure of suicidal risk, the suicide item (Item #9) in the Patient Health Questionnaire (PHQ-9), with categories 0 (none), 1 (mild), 2 (moderate), and 3 (severe). In the combined data (n = 1945), we calculated the cumulative percentage of data across these four categories and the percentile score of the CHRT-SR9 total score that corresponded to these percentages; from this, we developed ranges of the CHRT-SR9 total score that corresponded to the four categories of Item #9 of PHQ-9. We also calculated similar ranges for two broad subscales of the CHRT-SR9 total score; Propensity and Suicidal Thoughts. To assess the robustness of our findings, we repeated the analysis at another timepoint across studies. Findings indicated that the CHRT-SR9 total score (range: 0-36) can be categorized as none (0-14), mild (15-21), moderate (22-26), and severe (27-36). Similar categories were calculated for the Propensity and Suicidal Thoughts subscales. The findings were the same when repeated at another timepoint. This categorization of the CHRT-SR9 total score can place patients into clinically meaningful and actionable categories of suicidal risk.

Posterior assessment of occupational risks associated with work hardness based on workers’ subjective perception of their health

Work hardness causes health impairments in workers of some occupations. Posterior assessment should be considered priority one in health risk analysis instead of relying solely on results obtained by prior assessment based on descriptions of working condition. This paper presents the results obtained by posterior occupational risk (OR) assessment associated with work hardness; the assessment is based on analyzing workers’ subjective perception of their health (workers employed at a bearing production were used as an example). A survey was accomplished within this study followed by analyzing subjective perception of one’s health. It gave an opportunity to accomplish quantitative posterior OR assessment (that considered both likelihood of diseases and their severity) at the group and individual levels. Work hardness creates unacceptable group health risks associated with diseases of the musculoskeletal system and connective tissue (1.93•10-2–2.56•10-2), nervous system (4.03•10-2–6.77•10-2), genitourinary system (2.04•10-2–2.7•10-2) and cardio-vascular system (1.47•10-2–1.69•10-2). Such indicators as ‘weight of constantly lifted cargo and cargo moved by hand’ (35–58 %) and ‘uncomfortable working posture / working upright’ (29–54 %) make major contributions to the integral risk. Risk categories were adjusted at the individual level (considering parameters of the relationship that describe how likelihood of disease is influenced by work hardness, age and working records). This allowed establishing that OR was predominantly caused by diseases of the musculoskeletal system and connective tissue (‘medium risk’ for 19–83 % of the workers and ‘high risk’ for 75–81 %), nervous system (‘high risk’ for 84–85 % and ‘extremely high risk’ for 15–16 % of the workers) and genitourinary system (‘moderate risk’ for 1 %, ‘medium risk’ for 8 %, and ‘high risk’ for 87 %). Occupational health risk assessment allowed identifying priority indicators of work hardness (‘weight of constantly lifted cargo and cargo moved by hand’ and ‘uncomfortable working posture / working upright’) and establishing proper scope of relevant prevention activities at the group and individual level.

How many Data Deficient amphibians are threatened? IUCN Red List assessments for amphibian species previously classed as Data Deficient

At the time of our research in 2022, 16.4% of amphibian species on the IUCN Red List were assessed as Data Deficient (DD). There is minimal funding allocated to the research and reassessment of DD taxa, this prevents them from being prioritised for conservation. We identified 656 non-DD amphibian species that were previously assessed as DD and used their subsequent assessment trajectories to predict the extinction risk of remaining DD taxa. Assuming similarity of the distribution of these taxa between extinction risk categories to those of currently DD species, we compared this dataset with the risk category distribution of assessed amphibians that had never been assessed as DD. Previously DD amphibians, when compared to those that were never DD, were found to be more threatened (52.1% vs. 39.6%) and less likely to be non-threatened (22.4% vs. 60.0%). When explored further at the level of Order, more previously DD amphibians in the Order Gymnophiona were reassessed as ‘Near Threatened’, more Caudata ‘Critically Endangered’ with fewer ‘Least Concern’, and more Anura ‘Vulnerable’ and ‘Endangered’ with fewer ‘Least Concern’ than counterparts that were never assessed as DD. Based on these previously-DD amphibian data, we estimated that around half (49.6%, n = 592) of currently DD amphibians are likely threatened by extinction. Our approach arrives at similar conclusions to authors using other approaches and bolsters the argument that conservationists and funding organisations should implement recommendations to address concerns for DD amphibians, especially DD Caudata.

Correlation Between the Expression of DNA Damage Repair Protein OGG1 and Ubiquitination Pathway Protein STUB1 in Pediatric Neuroblastoma.

Neuroblastoma, a pediatric malignancy, is significantly influenced by genetic factors. Prior research indicates that the OGG1 rs1052133 G > C polymorphism correlates with a decreased risk of neuroblastoma. We analyzed 57 neuroblastoma and 21 adrenal samples, using immunohistochemistry to measure OGG1 and STUB1 expression levels. We conducted a survival analysis to explore relationship between the expressions and neuroblastoma prognosis. Notably higher OGG1 expression and significantly lower STUB1 expression in neuroblastoma. OGG1 levels were significantly correlated with patient age, tumor location, histological grade, Shimada classification, INSS stage, and risk category. A negative association was observed between OGG1 and STUB1 expressions. Higher OGG1 expression was linked to reduced PFS and OS. Lower STUB1 expression was associated with unfavorable PFS. Additionally, OGG1 expression and risk category emerged as independent predictors of prognosis. OGG1 potentially functions as an oncogene in NB, with its activity possibly modulated by STUB1 through the ubiquitination pathway.

Апостериорная оценка профессионального риска, связанного с тяжестью трудового процесса, на основе анализа субъективного восприятия работниками своего здоровья

Work hardness causes health impairments in workers of some occupations. Posterior assessment should be considered priority one in health risk analysis instead of relying solely on results obtained by prior assessment based on descriptions of working condition. This paper presents the results obtained by posterior occupational risk (OR) assessment associated with work hardness; the assessment is based on analyzing workers’ subjective perception of their health (workers employed at a bearing production were used as an example). A survey was accomplished within this study followed by analyzing subjective perception of one’s health. It gave an opportunity to accomplish quantitative posterior OR assessment (that considered both likelihood of diseases and their severity) at the group and individual levels. Work hardness creates unacceptable group health risks associated with diseases of the musculoskeletal system and connective tissue (1.93•10-2–2.56•10-2), nervous system (4.03•10-2–6.77•10-2), genitourinary system (2.04•10-2–2.7•10-2) and cardio-vascular system (1.47•10-2–1.69•10-2). Such indicators as ‘weight of constantly lifted cargo and cargo moved by hand’ (35–58 %) and ‘uncomfortable working posture / working upright’ (29–54 %) make major contributions to the integral risk. Risk categories were adjusted at the individual level (considering parameters of the relationship that describe how likelihood of disease is influenced by work hardness, age and working records). This allowed establishing that OR was predominantly caused by diseases of the musculoskeletal system and connective tissue (‘medium risk’ for 19–83 % of the workers and ‘high risk’ for 75–81 %), nervous system (‘high risk’ for 84–85 % and ‘extremely high risk’ for 15–16 % of the workers) and genitourinary system (‘moderate risk’ for 1 %, ‘medium risk’ for 8 %, and ‘high risk’ for 87 %). Occupational health risk assessment allowed identifying priority indicators of work hardness (‘weight of constantly lifted cargo and cargo moved by hand’ and ‘uncomfortable working posture / working upright’) and establishing proper scope of relevant prevention activities at the group and individual level.

P124 CARDIOVASCULAR RISK RE-CLASSIFICATION BY IMPLEMENTING CAROTID ULTRASONOGRAPHY IN PRIMARY CARE

Background and Objective: The accurate assessment of the total cardiovascular risk (CVR) using risk calculation algorithms in individuals with CVR factors in the primary prevention setting is essential for optimal management decisions, including drug treatment initiation and treatment goals. The aim of this study was to evaluate the contribution of ultrasonographic identification of asymptomatic carotid atherosclerosis in the re-classification of the CVR assessed with the reference SCORE2/2-OP algorithm. Methods: In individuals aged ≥40 years without established cardiovascular disease, the 10-year CVR was calculated using the SCORE2/2-OP algorithm (3 risk categories: low/moderate, high, and very high). Carotid ultrasound study was applied using a portable handheld device (Lumify, Philips) to classify CVR as follows: (i) low/moderate (absence of atherosclerotic plaque), (i) high (atherosclerotic plaque with <50% stenosis), (iii) very high (atherosclerotic plaque with ≥50% stenosis). Results: Data from 332 participants were analysed [age 59±7.5 years, men 41%, current smokers 26%, body mass index 28±5 kg/m2, office blood pressure 125±15/77±10 mmHg (systolic/diastolic), LDL-cholesterol 111±33 mg/dl]. Based on SCORE2/2-OP, 49/46/5% participants were categorised as of low/moderate, high, and very high CVR, respectively. Based on carotid ultrasound, the rates were 39/59/2%, respectively. 44% of individuals categorized as of low/moderate CVR based on SCORE2/2-OP were re-classified into a higher CVR category based on carotid ultrasound. The agreement between the 2 methods (ultrasound versus algorithms) in categorizing low/moderate and high CVR was 67% (kappa 0.35, P<0.001) and 61% (kappa 0.23, P<0.001), respectively. Among 204 participants categorized as of high/very high CVR according to carotid ultrasound, only 15 (7%) had LDL-cholesterol levels <70 mg/dl. Conclusions: These findings suggest that carotid ultrasonography using a portable handheld device may significantly contribute to assess CVR more accurately in primary care, especially in individuals classified as of low/moderate CVR using reference algorithms.

New risk classification adapting SCAI shock stages to patients with pulmonary embolism (RISA-PE).

Pulmonary embolism (PE) treatment is based on risk stratification according to European Society of Cardiology (ESC) guidelines. However, emerging therapies in acute PE may require a more granular risk classification. Therefore, the objective of the present study was to propose a new RIsk claSsification Adapting the SCAI shock stages to right ventricular failure due to acute PE (RISA-PE). This registry included consecutive intermediate-high risk (IHR) or high-risk (HR)-PE patients selected for catheter-directed interventions (CDI) from 2018 to 2023 in 15 Spanish centers (NCT06348459). Patients were grouped according to RISA-PE classification as A (right ventricular dysfunction and troponin elevation); B (A + serum lactate >2 mmol/L OR shock index ≥1); C (persistent hypotension); D (obstructive shock); and E (cardiac arrest). In-hospital adverse events were assessed to evaluate RISA-PE performance. A total of 334 patients were included (age 62.1±15.2 years, 55.7% males). The incidence of in-hospital all-cause death was progressively higher with increasing RISA-PE stage (1.2%, 6.4%, 19.0%, 25.6%, and 57.7% for stages A, B, C, D, and E, respectively, P value for linear trend<0.001). However, using the ESC classification, there was an abrupt difference between IHR- and HR-PE patients regarding mortality (4.3% vs. 29.3%, P<0.001). The incidence of in-hospital major bleeding and acute kidney injury followed a similar pattern. The user-friendly RISA-PE classification may improve the granularity in stratifying PE patients' risk and warrants evaluation in larger studies with different therapeutic approaches in order to detect its utility as a decision-making scale.

400.1: Appropriate risk classification and low-dose rituximab can help prevent antibody-associated rejection in ABO-compatible kidney transplants.

400.1: Appropriate risk classification and low-dose rituximab can help prevent antibody-associated rejection in ABO-compatible kidney transplants.

Oncological outcomes after radical prostatectomy of localized prostate cancer: stratified by magnetic resonance imaging and risk classification

BackgroundWe investigated whether combining T2-weighted magnetic resonance imaging (MRI) findings and clinical risk categories improves upon established prognostic indicators of oncological outcomes in prostate cancer. MethodsPatients who underwent radical prostatectomy, but not preoperative hormone therapy, radiotherapy, or chemotherapy, for localized prostate cancer at Seoul National University Bundang Hospital from October 2007 to April 2016 were included. MRIs were classified according to the Prostate Imaging-Reporting and Data System (PI-RADS). Patients were divided into the following five groups: 1, no focal suspicious lesion; 2, organ-confined suspicious lesion PI-RADS ≤3; 3, organ-confined suspicious lesion PI-RADS 4 or 5; 4, suspicious lesion with extraprostatic extension (EPE), no seminal vesicle invasion (SVI); 5, suspicious lesion with EPE and SVI. Risk classified according to the National Comprehensive Cancer Network (NCCN) and MRI findings were combined to analyze survival curves for biochemical recurrence (BCR)-free and metastasis-free survival. The area under a time-dependent receiver operating characteristic was analyzed for event prediction after 5 years. ResultsWe analyzed 1,290 patients. In multivariate Cox regression models, PI-RADS ≥4 (hazard ratio [HR] 2.33, P < 0.001), EPE (HR 1.46, P = 0.027), SVI (HR 5.03, P < 0.001) and NCCN high-risk (HR 2.33, 95% CI 1.66-3.26, P < 0.001) were associated with BCR. For metastasis, EPE (HR 2.33, P = 0.047), SVI (HR 13.08, P < 0.001) and NCCN high-risk (HR 2.78, P = 0.026) were independent risk factors. Depending on MRI group, BCR-free survival significantly decreased in NCCN intermediate-risk (P = 0.001) and high-risk (P < 0.001) groups, and metastasis-free survival decreased in the intermediate-risk group (P = 0.39) and significantly decreased in the high-risk (P < 0.001) group. Adding MRI group to NCCN risk classification significantly improved the predictive accuracy for BCR in comparison with NCCN risk classification alone (P = 0.042), but not for metastasis (P = 0.012). ConclusionCombining prostate MRI with NCCN risk classification improves the prediction value of BCR following radical prostatectomy for localized prostate cancer.

Probability Threshold Optimization for Classification of COVID-19 Patients with Higher Mortality Risk: A Case Study from the North-Eastern Region in North Macedonia

Research goal: The goal of this research is to identify, compare and demonstrate some available methodological approaches which are sufficient to draw the optimal probability threshold, particularly in the case of classification of infected patients with increased risk of dying from COVID-19. The presented methodologies generate identical results if the purpose of classification is to maximize the prognosis accuracy from the point of sensitivity. Sample: As part of the whole population, the sample counts 1013 patients from the north-eastern region of the Republic of North Macedonia. Methodology: The general methodological frame used to calculate and forecast the probabilities of death outcome from COVID-19 is the binary logistic regression. In extension, we applied the rules of maximum sum and maximum product as well as the so-called Youden Index for the purpose of optimization of the probability threshold. The principals of the ROC curve in addition with the Index of Union was also helpful for the same purpose. Prognosis accuracy was evaluated through the status of patient according to the rules of “golden standard” in which sensitivity, specificity and the general accuracy of prognosis play a crucial role. Results: Accordingly, the results from the research indicate that the optimal probability threshold or “cut-off” point that provides maximal accuracy, particularly from the perspective of sensitivity in the prognosis is 0,1. In that point, the coefficient of sensitivity (the percentage of true positively predicted death cases in respect to all death cases from the sample) is measured 85,71%. Conclusion: The applied methodological approaches offer scientifically sound foundations in the context of mortality risk evaluation and classification of COVID-19 patients. Then targeted patients will be subject of precaution with strict measures, protocols and more aggressive treatment in order to minimize the chances of death outcome.

Identification of novel M2 macrophage-related molecule ATP6V1E1 and its biological role in hepatocellular carcinoma based on machine learning algorithms.

Hepatocellular carcinoma (HCC) remains the most prevalent form of primary liver cancer, characterized by late detection and suboptimal response to current therapies. The tumour microenvironment, especially the role of M2 macrophages, is pivotal in the progression and prognosis of HCC. We applied the machine learning algorithm-CIBERSORT, to quantify cellular compositions within the HCC TME, focusing on M2 macrophages. Gene expression profiles were analysed to identify key molecules, with ATP6V1E1 as a primary focus. We employed Gene Set Enrichment Analysis (GSEA) and Kaplan-Meier survival analysis to investigate the molecular pathways and prognostic significance of ATP6V1E1. A prognostic model was developed using multivariate Cox regression analysis based on ATP6V1E1-related molecules, and functional impacts were assessed through cell proliferation assays. M2 macrophages were the dominant cell type in the HCC TME, significantly correlating with adverse survival outcomes. ATP6V1E1 was robustly associated with advanced disease stages and poor prognostic features such as vascular invasion and elevated alpha-fetoprotein levels. GSEA linked high ATP6V1E1 expression to critical oncogenic pathways, including immunosuppression and angiogenesis, and reduced activity in metabolic processes like bile acid and fatty acid metabolism. The prognostic model stratified HCC patients into distinct risk categories, showing high predictive accuracy (1-year AUC = 0.775, 3-year AUC = 0.709 and 5-year AUC = 0.791). Invitro assays demonstrated that ATP6V1E1 knockdown markedly inhibited the proliferation of HCC cells. The study underscores the significance of M2 macrophages and ATP6V1E1 in HCC, highlighting their potential as therapeutic and prognostic targets.

243P Prognosis of patients with hormone receptor-positive/HER2-negative early breast cancer according to monarchE and NATALEE trials risk categories: Patient-level analysis of Mammella InterGruppo (MIG) and Gruppo Italiano Mammella (GIM) randomised trials

243P Prognosis of patients with hormone receptor-positive/HER2-negative early breast cancer according to monarchE and NATALEE trials risk categories: Patient-level analysis of Mammella InterGruppo (MIG) and Gruppo Italiano Mammella (GIM) randomised trials