Stratification Strategies Research Articles

The modulating effect of circulating carbohydrate antigen 125 on ST2 and long-term recurrent morbidity burden

Soluble ST2 (sST2) is released in response to vascular congestion, inflammation, and pro-fibrotic stimuli. In heart failure (HF), elevated levels of sST2 are associated with a higher risk of adverse clinical outcomes. Emerging evidence suggests that carbohydrate antigen 125 (CA125) may act as a ligand that modulates the inflammatory response. We hypothesized that CA125 might be modulating sST2 activity. In a cohort of 160 patients with acute (AHF) and renal dysfunction, we investigated whether the prognostic value of sST2 varies according to CA125 levels. The endpoints were: (a) total cardiovascular and renal hospitalizations and (b) all-cause mortality during follow-up. Cox regression analyses assessed the association between admission sST2 and endpoints across CA125 (≤ 35 vs. > 35 U/ml). This sub-study of the IMPROVE-HF trial shows that sST2 predicted the composite of cardiovascular or renal rehospitalizations when CA125 was elevated (> 35 U/ml) but not when CA125 ≤ 35 U/ml. These results highlight a potential biological interaction between sST2 and CA125, suggesting that CA125 status may refine the prognostic utility of sST2 in AHF. Clinically, these insights could guide personalized risk stratification and management strategies in this high-risk population.

Rhabdomyosarcoma Surgical Update.

Rhabdomyosarcoma (RMS) tumors arise from mesenchymal tissue and represent half of pediatric sarcomas, which in turn make up 7% of pediatric tumors. Advances in local control therapy of RMS have improved outcomes after surgical resection of the primary tumor, either before or after induction chemotherapy, even in the setting of metastatic disease. The utilization of diagnostic core needle and sentinel node biopsy techniques for lymph node staging are becoming more widely used. Over the past several years, refinement of prognostic factors with adoption of fusion status instead of histology, and optimized risk stratification schemas have been developed to assure appropriate therapy. There have been efforts between North American and European surgical oncology cooperative groups to standardize the care we provide, and yet there are still some philosophical differences to overcome.

Heart failure risk stratification using artificial intelligence applied to electrocardiogram images: a multinational study.

Current heart failure (HF) risk stratification strategies require comprehensive clinical evaluation. In this study, artificial intelligence (AI) applied to electrocardiogram (ECG) images was examined as a strategy to predict HF risk. Across multinational cohorts in the Yale New Haven Health System (YNHHS), UK Biobank (UKB), and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), individuals without baseline HF were followed for the first HF hospitalization. An AI-ECG model that defines cross-sectional left ventricular systolic dysfunction from 12-lead ECG images was used, and its association with incident HF was evaluated. Discrimination was assessed using Harrell's C-statistic. Pooled cohort equations to prevent HF (PCP-HF) were used as a comparator. Among 231 285 YNHHS patients, 4472 had primary HF hospitalizations over 4.5 years (inter-quartile range 2.5-6.6). In UKB and ELSA-Brasil, among 42 141 and 13 454 people, 46 and 31 developed HF over 3.1 (2.1-4.5) and 4.2 (3.7-4.5) years. A positive AI-ECG screen portended a 4- to 24-fold higher risk of new-onset HF [age-, sex-adjusted hazard ratio: YNHHS, 3.88 (95% confidence interval 3.63-4.14); UKB, 12.85 (6.87-24.02); ELSA-Brasil, 23.50 (11.09-49.81)]. The association was consistent after accounting for comorbidities and the competing risk of death. Higher probabilities were associated with progressively higher HF risk. Model discrimination was 0.718 in YNHHS, 0.769 in UKB, and 0.810 in ELSA-Brasil. In YNHHS and ELSA-Brasil, incorporating AI-ECG with PCP-HF yielded a significant improvement in discrimination over PCP-HF alone. An AI model applied to a single ECG image defined the risk of future HF, representing a digital biomarker for stratifying HF risk.

Investigating lung cancer microenvironment from cell segmentation of pathological image and its application in prognostic stratification

Lung cancer, particularly adenocarcinoma, ranks high in morbidity and mortality rates worldwide, with a relatively low five-year survival rate. To achieve precise prognostic assessment and clinical intervention for patients, thereby enhancing their survival prospects, there is an urgent need for more accurate stratification schemes. Currently, the TNM staging system is predominantly used in clinical practice for prognostic evaluation, but its accuracy is constrained by the reliance on physician experience. Although biomarker discovery based on molecular pathology offers a new perspective for prognostic assessment, its dependence on expensive gene panel testing limits its widespread clinical application. Pathological images contain abundant diagnostic information, providing a new avenue for prognostic evaluation. In this study, we employed advanced Hover-Net technology to accurately quantify the abundance of epithelial cells, lymphocytes, macrophages, and neutrophils from pathological images, and delved into the clinical and biological significance of these cellular abundances. Our research findings reveal that, in contrast to patients classified as N0 stage, those belonging to the N1 stage demonstrated a marked elevation in the infiltration of epithelial cells, lymphocytes, macrophages, and neutrophils. Notably, the infiltration patterns of lymphocytes and neutrophils exhibited an inverse relationship with the activation status of numerous pivotal gene pathways, including the HALLMARK_HEME_METABOLISM pathway. Furthermore, our analysis distinguished FABP7 as a prognostic biomarker, exhibiting pronounced differential expression between patients with high and low levels of neutrophil infiltration, indicate that cellular abundance analysis based on pathological images can provide a more accurate and cost-effective prognostic evaluation, offering new strategies for the clinical management of lung adenocarcinoma.

Global trends and risk factors in gastric cancer: a comprehensive analysis of the Global Burden of Disease Study 2021 and multi-omics data.

Background: Gastric cancer (GC) remains a significant global health challenge. This study aimed to comprehensively analyze GC epidemiology and risk factors to inform prevention and intervention strategies. Methods: We analyzed the Global Burden of Disease Study 2021 data, conducted 16 different machine learning (ML) models of NHANES data, performed Mendelian randomization (MR) studies on disease phenotypes, dietary preferences, microbiome, blood-based markers, and integrated differential gene expression and expression quantitative trait loci (eQTL) data from multiple cohorts to identify factors associated with GC risk. Results: Global age-standardized disability-adjusted life year rates (ASDR) for GC declined from 886.24 to 358.42 per 100,000 population between 1990 and 2030, with significant regional disparities. Despite this decline, total disability-adjusted life years show a concerning upward trend from 2015, rising from approximately 22.9 million to a projected 24.3 million by 2030. The slope index of inequality shifted from 87 in 1990 to -184 in 2021, indicating a reversal in GC burden distribution, with higher ASDR now associated with lower socio-demographic index countries. The ML models analysis identified higher levels of clinical characteristics such as phosphorus, calcium, eosinophils percent, and triglycerides, as well as lower levels of iron and monocyte percent, may be associated with an increased risk of GC. MR analyses revealed causal associations between GC risk and disease phenotypes such as Helicobacter pylori infection, chronic gastritis, obesity, depression, and dietary preferences such as dairy and processed meats. Gut microbiome analysis showed associations with microbiome such as Phascolarctobacterium and Ruminococcaceae species. Blood-based markers analysis identified protective and risk effects for cortisol, glutamate, nicotinamide, Natural Killer %lymphocyte, CD4-CD8- T cell Absolute Count, Phosphatidylcholine (16:0_18:1), and Interleukin-1-alpha. Integrated genomic analysis identified 10 genes significantly associated with GC risk, with strong evidence for colocalization in genes such as CCR6 and PILRB. Conclusions: This systematic analysis reveals complex global trends in GC burden and identifies novel clinical, disease phenotypes, dietary preferences, microbial, blood-based, and genetic risk factors. These findings provide potential targets for improved risk stratification, prevention, and intervention strategies to reduce the global burden of GC.

Is Low-free Triiodothyronine (fT3) Associated with Increased Morbidity in Patients Admitted to Coronary Care Units?

The effects of thyroid hormone on patients hospitalized in coronary intensive care units are still controversial. We retrospectively examined thyroid hormone levels and their impact on cardiovascular morbidity in patients admitted to coronary intensive care units. A total of 208 (Female/Male; 47.1%/52.9%) patients without any history of thyroid disease were enrolled and screened. Patients with specific heart disease and existing thyroid hormone parameters were included in the study. Low triiodothyronine syndrome is characterized by reduced serum total or free T3 (fT3) concentrations in normal free T4 (fT4) and TSH levels. The common diagnosis of the patients in the coronary care unit is acute coronary syndrome (n=59, 28.2 %) and heart failure (n=46, 23.3%). Patients were divided into two groups according to left ventricular ejection fraction percentages (LVEF ≤39% vs LVEF ≥40%). Plasma fT3 levels were significantly correlated with low LVEF (≤39%) (p =0.002). fT3 (r=-0.183, p =0.013) and hospitalization etiology (r=-0.161, p =0.023) were also the most critical parameters affecting the length of hospitalization. Low fT3 was associated with reduced ejection fraction and prolonged hospitalization, which may lead to potential morbidities in HF patients, which may be useful in risk stratification and treatment strategies.

Haemoglobin for Fall Risk Screening in Gynaecological and Obstetric Wards: Retrospective Survey and Delphi Validation.

The objective of this study is to ascertain the suitability of haemoglobin as a screening factor for falls among obstetrics and gynaecology inpatients and to formulate a stratified scheme for assessing fall risk based on haemoglobin. A retrospective analysis and Delphi surveys were employed for this investigation. Initially, a retrospective survey analysed falls among obstetrics and gynaecology inpatients in two hospitals from January 1, 2020, to July 10, 2022. Descriptive statistics, receiver operating characteristic (ROC) curve analysis, Youden index, sensitivity and specificity were utilised for data examination. The conclusions drawn were subsequently validated by Delphi surveys, featuring 21 experts participating in five rounds of consultation. The Kappa value and the coefficient of variation (CV) were employed to assess expert advice. The area under the Receiver Operating Characteristic curve (AUC) of haemoglobin was 0.762 ± 0.030, 95% CI (0.703, 0.821). The highest Youden index was 0.425, with sensitivity at 0.705 and specificity at 0.720 when haemoglobin was 107.5 g/L. Two consensuses were reached by experts: anaemia was important in causing falls in obstetrics and gynaecology wards, and haemoglobin should be employed as a screening factor for falls. The stratification of anaemia was developed as follows: ≥ 110; 90-109; 60-89; and < 60 g/L. Approval for the final results was unanimous among all experts. The Kappa value (K*) was 1, and the CV of expert advice ranged from 0.092 to 0.219. Haemoglobin could potentially be used as a predictor of fall risk in Gynaecological and Obstetric Wards. The recommended stratified scheme for anaemia in fall risk assessment is as follows: ≥ 110; 90-109; 60-89; and < 60 g/L. What problem did the study address? The study revealed a relationship between falls and haemoglobin in obstetrics and gynaecology inpatients. It also proposed a stratification scheme for assessing fall risk based on haemoglobin levels. What were the main findings? Haemoglobin has a good performance on fall risk prediction in Gynaecological and Obstetric Wards. The stratified scheme of anaemia for fall risk assessment was suggested as follows: ≥ 110; 90-109; 60-89; and < 60 g/L. Where and on whom will the research have an impact? Nurses and inpatients in obstetrics and gynaecology wards will be affected by the results of this study, and it provided a reference for fall prevention. This study has adhered to relevant EQUATOR guidelines and named the reporting method. No Patient or Public Contribution.

BASIC AND CLINICAL ASPECTS OF VASCULAR AGING

Abstract Vascular aging (VA) is an important pathophysiological contributor to the aging process. In response to China’s aging population, a hierarchical “Standardized Vascular Aging Management Center (VMC)” network, with Tongji Hospital in Wuhan as the central hub, was established in 2023 to offer comprehensive vascular aging (VA) management nationwide. This initiative encompasses assessment, stratification, and intervention strategies for VA, a key factor in the aging of human organs and systems and a common denominator in the chronic diseases of aging. Our research delves into the cellular and molecular dynamics of VA, examining the effectiveness of pharmaceutical interventions against vascular stiffness and investigating cellular aging mechanisms such as metabolic changes, ferroptosis, mitochondrial dysfunction, and senescence-associated secretory phenotype (SASP), alongside key factors like SOX9, Nrf2, and FGF21. Furthermore, we are launching a national cohort study and conducting randomized trials on novel drugs to bridge clinical and basic research findings. This integrated approach aims to detect early VA signs, enabling timely interventions to mitigate chronic elderly diseases, foster healthy aging, and effectively tackle the implications of an aging demographic. By developing an integrated VA research and application platform that facilitates seamless translation between basic and clinical settings, we aim to identify early signs of VA and implement appropriate interventions to delay and manage this process. Ultimately, our efforts aim to reduce chronic disease in the elderly, promote healthy aging and more effectively address the challenges of an aging society.

Investigating the association between labor pain and cessation of breastfeeding

Mothers encounter several challenges to sustain breastfeeding until the recommended 6 months of age. There is limited evidence on the impact of women’s labor pain experiences upon cessation of breastfeeding. We aimed to investigate the association between women’s labor pain experiences, intrapartum interventions, and pre-birth psychological vulnerabilities and cessation of breastfeeding. This was a secondary analysis of a clinical trial conducted in a tertiary hospital in Singapore between June 2017 and July 2021. Data were obtained from participants, electronic records and surveys administered before delivery, and postpartum 6–10 weeks. A total of 624 (76.8%) women were still breastfeeding at postpartum 6–10 weeks as compared to 189 (23.2%) that had discontinued breastfeeding. Multivariable regression analysis identified lower education level (aOR 3.88, 95% CI 2.57–5.85, p < 0.0001), having diabetes (aOR, 95% CI 1.21–5.44, p = 0.0141), presence of obstetric complications (aOR 1.57, 95% CI 1.00–2.46, p = 0.0494), artificial rupture of membrane (ARM) and oxytocin induction (aOR 2.07, 95% CI 1.22–3.50, p = 0.0068), lower age (aOR 0.92, 95% CI 0.88–0.97, p = 0.0010) and higher A-LPQ birth pain score (aOR 1.02, 95% CI 1.01–1.04, p = 0.0064) as independent associations with cessation of breastfeeding at postpartum 6–10 weeks, with AUC of the model being 0.72 (95% CI 0.68–0.77). Higher pain experienced during labor is associated with cessation of breastfeeding among several other intrapartum interventions and psychological vulnerabilities. Using risk stratification strategy, breastfeeding support services could be provided to women to optimize successful breastfeeding in the postpartum period.Trial registration: This study was registered on Clinicaltrials.gov NCT03167905 on 30/05/2017.

Machine learning based radiomics model to predict radiotherapy induced cardiotoxicity in breast cancer.

Cardiotoxicity is one of the major concerns in breast cancer treatment, significantly affecting patient outcomes. To improve the likelihood of favorable outcomes for breast cancer survivors, it is essential to carefully balance the potential advantages of treatment methods with the risks of harm to healthy tissues, including the heart. There is currently a lack of comprehensive, data-driven evidence on effective risk stratification strategies. The aim of this study is to investigate the prediction of cardiotoxicity using machine learning methods combined with radiomics, clinical, and dosimetric features. A cohort of 83 left-sided breast cancer patients without a history of cardiac disease was examined. Two- and three-dimensional echocardiography were performed before and after 6 months of treatment to evaluate cardiotoxicity. Cardiac dose-volume histograms, demographic data, echocardiographic parameters, and ultrasound imaging radiomics features were collected for all patients. Toxicity modeling was developed with three feature selection methods and five classifiers in four separate groups (Dosimetric, Dosimetric+Demographic, Dosimetric+Demographic+Clinical, and Dosimetric+Demographic+Clinical+Imaging). The prediction performance of the models was validated using five-fold cross-validation and evaluated by AUCs. 58% of patients showed cardiotoxicity 6 months after treatment. Mean left ventricular ejection fraction and Global longitudinal strain decreased significantly compared to pre-treatment (p-value<0.001). After feature selection and prediction modeling, the Dosimetric, Dosimetric+Demographic, Dosimetric+Demographic+Clinical, Dosimetric+Demographic+Clinical+Imaging models showed prediction performance (AUC) up to 73%, 75%, 85%, and 97%, respectively. Incorporating clinical and imaging features along with dose descriptors are beneficial for predicting cardiotoxicity after radiotherapy.

Exploring the silent epidemic: investigating the hidden burden of normal weight obesity in type 2 Diabetes Mellitus in India - a cross-sectional study

ObjectiveThis study aimed to determine the prevalence of Normal Weight Obesity (NWO) and evaluate its association with cardiometabolic risk factors among patients with Type 2 Diabetes Mellitus (T2DM) in Gujarat, India.MethodsThis cross-sectional study included 432 adults with T2DM attending a Non-Communicable Disease clinic. Anthropometric measurements, body composition analysis using bioelectrical impedance, and clinical parameters were assessed. NWO was defined as normal BMI (18.5–24.9 kg/m²) with high body fat percentage (≥ 25% for men, ≥ 32% for women). Cardiometabolic risk factors, including blood glucose, blood pressure, and lipid profile, were evaluated. Statistical analyses included descriptive statistics, correlation analysis, and multivariate logistic regression.ResultsThe prevalence of NWO was 33% among the study population. Significant discordance was observed between BMI classification and body fat percentage, with 91% of males and 51.8% of females with normal BMI having obese levels of body fat. Individuals with NWO demonstrated higher cardiometabolic risk profiles compared to non-obese counterparts, including elevated random blood glucose levels (290 ± 110 mg/dL vs. 180 ± 80 mg/dL, p < 0.001), higher systolic (148.8 ± 25.4 mmHg vs. 122.5 ± 19.5 mmHg, p < 0.001) and diastolic blood pressure (98.5 ± 55.6 mmHg vs. 78.6 ± 36.6 mmHg, p < 0.001), and increased prevalence of hypertension (61% vs. 15%, p < 0.001). A moderate positive correlation was found between body fat percentage and random blood sugar levels (r = 0.504, p < 0.001). Multivariate analysis identified age, duration of diabetes, blood glucose levels, and blood pressure as independent factors associated with NWO.ConclusionThe high prevalence of NWO and its significant association with adverse cardiometabolic risk factors in T2DM patients underscores the limitations of using BMI alone for obesity assessment. These findings highlight the need for incorporating body composition analysis in routine clinical practice to improve risk stratification and management strategies in T2DM patients, particularly in the Asian Indian population.

PSA Density and Lesion Volume: Key Factors in Avoiding Unnecessary Biopsies for PI-RADS 3 Lesions.

The use of multiparametric magnetic resonance imaging (MRI) to guide prostate biopsies has improved cancer detection rates, particularly for high-grade tumors. However, despite guidelines recommending biopsies for lesions with a Prostate Imaging-Reporting and Data System (PI-RADS) score ≥ 3, the clinical significance of PI-RADS 3 lesions remains uncertain. This uncertainty, coupled with the cost and potential complications of biopsies, underscores the need for more accurate risk stratification strategies to avoid unnecessary procedures. Prostate-specific antigen density (PSAD) and index lesion volume are emerging as potential contributors to improve risk assessment. This was a retrospective analysis of patients who had undergone an MRI-guided transrectal ultrasound (TRUS) prostate biopsy at a tertiary care institution. Patients with PI-RADS 3 lesions were included, and data on demographics, prostate-specific antigens (PSA), PSAD, lesion diameter, and pathology results were collected. The relationships between PSAD, lesion volume, and pathology outcomes were statistically analyzed. Of the 213 patients included, 40 were diagnosed with prostate cancer. PSAD and PSAD x lesion diameter were significantly higher in the patients diagnosed with prostate cancer than those with benign lesions. Among the prostate cancer patients, clinically significant prostate cancer (csPCa) had a higher mean PSAD value than clinically insignificant prostate cancer (cisPCa). ROC analysis found PSAD x lesion diameter to have the highest discriminatory power for detecting csPCa. MRI-guided biopsies offer targeted sampling but the clinical significance of PI-RADS 3 lesions remains uncertain. Index lesion volume and PSAD are promising adjunctive markers for risk assessment. Combining these factors could facilitate the avoidance of unnecessary biopsies and improve the detection of csPCa. Incorporating PSAD and index lesion volume into biopsy decision-making may enhance risk stratification, particularly for PI-RADS 3 lesions. Further research is needed to validate these findings and enhance the risk assessment strategies used in making decisions regarding prostate biopsy.

The Overlooked Risk of Venous Thromboembolism in Psychiatric Patients: Epidemiology, Pathophysiology, and Implications for Clinical Care.

Psychiatric patients face a significantly shorter life expectancy than the general population due to a complex interplay of medical, behavioral, and social factors. Venous thromboembolism (VTE), encompassing both pulmonary embolism and deep vein thrombosis, is an underrecognized yet critical contributor to morbidity and mortality in this population. Evidence suggests a two to three times higher prevalence of VTE in psychiatric patients compared to the general population, with incidence rates up to 4.5 per 1,000 person-years. This elevated risk is attributed to a hypercoagulable-hypofibrinolytic state. It is influenced by metabolic abnormalities, pro-inflammatory pathways, antipsychotic medications, and genetic factors. Health care biases and reduced treatment compliance further exacerbate the burden. This review explores the epidemiology, pathophysiology, and mechanistic underpinnings of VTE in psychiatric populations, emphasizing the role of metabolic syndrome and antipsychotic therapy. To mitigate mortality and enhance outcomes for these high-risk individuals, it is imperative to address this issue through improved risk stratification and preventive strategies.

Genetic Association of Juvenile Idiopathic Arthritis With Adult Rheumatic Disease

Patients with juvenile idiopathic arthritis (JIA) may develop adult rheumatic diseases later in life, and prolonged or recurrent disease activity is often associated with substantial disability; therefore, it is important to identify patients with JIA at high risk of developing adult rheumatic diseases and provide specialized attention and preventive care to them. To elucidate the full extent of the genetic association of JIA with adult rheumatic diseases, to improve treatment strategies and patient outcomes for patients at high risk of developing long-term rheumatic diseases. In this genetic association study of 4 disease genome-wide association study (GWAS) cohorts from 2013 to 2024 (JIA, rheumatoid arthritis [RA], systemic lupus erythematosus [SLE], and systemic sclerosis [SSc]), patients in the JIA cohort were recruited from the US, Australia, and Norway (with a UK cohort included in the meta-analyzed cohort), while patients in the other 3 cohorts were recruited from US and Western European countries. All analyses were conducted between September 2023 and April 2024. Genetic associations. Genetic correlations and shared genomic loci between JIA and adult rheumatic diseases. Genetic correlation analyses and cross-trait meta-analysis were conducted on the JIA cohort and the summary statistics of the GWASs from adult rheumatic diseases (RA, SLE, and SSc). Mendelian randomization analyses were also conducted. This study included 33 207 patients across the 4 cohorts, with 4550 patients in the meta-analyzed JIA cohort (JIA cohort: 1485 patients with arthritis onset before 16 years; 1017 female [68.5%]; 10 352 controls; UK cohort: 3305 patients with JIA; 9196 controls), 143 61 patients in the RA cohort, 5201 patients in the SLE cohort; and 9095 patients in the SSc cohort. After the GWAS result of the JIA cohort was meta-analyzed with the UK JIA cohort, there was a total of 4550 JIA cases and 18 446 controls. The analysis revealed a significant global correlation between JIA and adult rheumatic diseases, with 84 regions harboring signals associated with multiple diseases. Cross-trait analyses uncovered novel disease loci and 20 loci associated with JIA and adult diseases. Mendelian randomization analysis revealed the significant association of 11 proteins with rheumatic disorders. Both shared, organ-specific, and disease-specific critical cell types were highlighted. In this genetic association study, there was significant genetic overlap between JIA and adult rheumatic diseases. These findings may help to refine JIA classification, risk stratification, and therapeutic strategy of repurposing adult disease drugs for pediatric patients with similar mechanisms.

Clinical management of patients with cavernous malformations of the central nervous system: an update and recommendations for clinical practice

Cerebral cavernous malformations are benign vascular anomalies of the central nervous system (CNS). The clinical presentation of a cavernoma depends on its location. The majority of patients with cavernomas are asymptomatic. The most common symptoms include epileptic seizures, focal neurological deficits and/or headaches. The clinical management of cavernomas is challenging because numerous factors influence decision-making. These factors include the risk stratification of cavernoma-related hemorrhage, weighing the risks of surgical intervention against the natural course of the cavernoma and the clinical presentation. This article presents current guidelines and recommendations for clinical practice, based on the latest research findings and expert opinions. The article focuses on diagnostic approaches, risk stratification, therapeutic management and follow-up strategies.

Advances in Cardio-Oncology: The Emerging Role of Sglt2 Inhibitors in Cardioprotection

&amp;lt;i&amp;gt;Background: &amp;lt;/i&amp;gt;The cardiotoxic effects of anti-tumor therapies represent a critical concern in oncology, as they compromise patient survival and quality of life by inducing cardiovascular diseases. With an increasing number of cancer patients undergoing treatments such as chemotherapy and radiation, the incidence of cardiotoxicity has surged. These adverse effects underscore the necessity of early detection, risk stratification, and preventive strategies tailored to mitigate cardiotoxicity and improve patient outcomes. &amp;lt;i&amp;gt;Objective: &amp;lt;/i&amp;gt;This meta-analysis aims to systematically evaluate the effectiveness of various interventions designed to prevent or reduce cardiotoxicity associated with anti-tumor therapies. By synthesizing evidence from existing studies, we seek to identify the most effective measures, providing a comprehensive overview of the current landscape in cardioprotective strategies. &amp;lt;i&amp;gt;Methods: &amp;lt;/i&amp;gt;We conducted a comprehensive literature search, including peer-reviewed studies that investigated preventive strategies for cardiotoxicity in patients undergoing anti-tumor therapy. Inclusion criteria were studies evaluating pharmacological and non-pharmacological interventions and their effects on cardiac function and patient outcomes. Data were extracted and analyzed to assess the impact of interventions on cardiotoxicity incidence, cardiac biomarkers, and clinical endpoints. &amp;lt;i&amp;gt;Main Findings: &amp;lt;/i&amp;gt;Our analysis demonstrates a range of effective cardioprotective interventions, particularly focusing on beta-blockers, ACE inhibitors, and lifestyle modifications. Beta-blockers were found to reduce the incidence of left ventricular dysfunction, while ACE inhibitors showed promise in improving cardiac biomarkers. Additionally, lifestyle interventions, including exercise and dietary modifications, contributed to overall cardiovascular health, though further research is needed to define optimal protocols. &amp;lt;i&amp;gt;Conclusion: &amp;lt;/i&amp;gt;Preventive strategies play a pivotal role in managing cardiotoxicity in cancer patients undergoing anti-tumor therapies. Pharmacological interventions, especially beta-blockers and ACE inhibitors, show significant potential in mitigating cardiac damage, while lifestyle interventions offer supplementary benefits. Our findings underscore the importance of an integrative approach, combining pharmacological and lifestyle modifications to protect cardiac function. Future research should focus on personalized cardioprotective protocols to optimize outcomes for cancer patients, ensuring that cardiovascular health is maintained alongside effective anti-tumor treatment.

Artificial Intelligence-Driven Advances in Coronary Calcium Scoring: Expanding Preventive Cardiology.

Coronary artery disease (CAD) remains a leading global cause of morbidity and mortality, underscoring the need for effective cardiovascular risk stratification and preventive strategies. Coronary artery calcium (CAC) scoring, traditionally performed using electrocardiogram (ECG)-gated cardiac computed tomography (CT) scans, has been widely validated as a robust tool for assessing cardiovascular risk. However, its application has been largely limited to high-risk populations due to the costs, technical requirements, and limited accessibility of cardiac CT scans. Recent advancements in artificial intelligence (AI) have introduced transformative opportunities to extend CAC detection to noncardiac CT scans, such as those performed for lung cancer screening, enabling broader and more accessible cardiovascular screening. This review provides a comprehensive analysis of AI-driven CAC detection, examining various types of AI models for CAC detection, like convolutional neural networks (CNNs) and U-Net architectures, and exploring the clinical, operational, and ethical implications of incorporating these technologies into routine practice. Technical challenges, including imaging variability, data privacy, and model bias, are discussed alongside essential areas for further research, such as standardization and validation across diverse populations. By leveraging widely available imaging data, AI-enabled CAC detection has the potential to advance preventive cardiology, supporting earlier risk identification, optimizing healthcare resources, and improving patient outcomes.

Aminotransferase-to-lymphocyte ratio as a valuable prognostic marker for patients with stage I-III colorectal cancer: a retrospective study.

There are no population-based studies on the prognostic value of the preoperative aminotransferase-to-lymphocyte ratio (AALR) in predicting recurrence and survival in patients with colorectal cancer (CRC) who have undergone curative resection. This study explored the relationship between AALR and prognosis of CRC patients, specifically stage III CRC. Restricted Cubic Splines were used to evaluate the relationship between AALR and outcomes. The survival curve was generated using the Kaplan-Meier method and the log-rank test. COX regression analysis was used to identify the independent prognostic factors of CRC patients. Logistic regression analysis was used to assess the independent risk factors affecting sarcopenia and postoperative complications. Concordance index and calibration curves were used to evaluate the discriminative ability of the prognostic nomograms. Finally, according to a ratio of 7:3, the total population was randomized into two cohorts to validate the practicability of the prognostic nomograms. In total, 1304 stage I-III CRC were enrolled in this study. There was a significant positive correlation between AALR and PFS/OS in CRC patients. The PFS/OS ratio of the high AALR group was significantly lower than that of the low AALR group. In the subgroup analysis, we found that the AALR significantly stratified the prognosis of patients with stage III CRC. A high AALR was still independently associated with poor PFS (HR = 1.335, 95% CI =1.075-1.657, p=0.009) and OS (HR = 1.382, 95% CI =1.139-1.677, p=0.001) in CRC patients. Variables with a value ≤ 0.05 in multivariable analysis were incorporated into the construction of prognostic nomograms for predicting 1-5 years PFS/OS of CRC patients. The results of the concordance index and calibration curves confirmed that these prognostic nomograms had a good prediction accuracy. In addition, we demonstrated the good predictive performance of these nomograms in a randomized internal validation cohort. AALR is an effective prognostic marker for predicting long-term outcomes and could provide a valuable reference for sarcopenia and postoperative complications in CRC patients. AALR-based nomograms have good predictive accuracy and can help to develop individualized risk stratification, follow-up, and treatment strategies for CRC patients.

Role of metabolic syndrome and lifestyle factors in endometrial cancer risk and prevention

Introduction: The incidence of endometrial cancer, the sixth most common cancer among women, has been rising, especially in developed countries, possibly due to the obesity and diabetes pandemic. The aim of this review is to investigate the connection between metabolic syndrome, its individual components and endometrial cancer risk and to explore the role of lifestyle factors in endometrial cancer prevention. Materials and methods: For this review, we included studies regarding endometrial cancer and metabolic syndrome, obesity, diabetes and hyperglycemia, hypertension, dyslipidemia and several lifestyle factors, from 1994 to 2024. State of knowledge: This paper reviews existing literature on the relationship between metabolic syndrome and endometrial cancer, highlighting the significant role of central obesity, hyperglycemia and diabetes, dyslipidemia, and hypertension as risk factors. Evidence consistently demonstrates that individuals with metabolic syndrome, and its components individually, are at a heightened risk of developing endometrial cancer compared to those without metabolic abnormalities. Biological mechanisms linking metabolic syndrome’s components to endometrial cancer involve complex interplays between metabolic, hormonal or inflammatory factors and signalling pathways. Lifestyle interventions focusing on weight management, physical activity, and eating habits play an important role in reducing endometrial cancer risk and improving overall health outcomes. Conclusion: An understanding of the relationship between metabolic syndrome and endometrial cancer is crucial for improving risk stratification, early detection, and prevention strategies. Addressing metabolic abnormalities and promoting healthy lifestyle behaviours are essential actions against the rising incidence and burden of endometrial cancer.

The IL-1β inhibitor canakinumab in previously treated lower-risk myelodysplastic syndromes: a phase 2 clinical trial

In myelodysplastic syndromes (MDS), the IL-1β pathway is upregulated, and previous studies using mouse models of founder MDS mutations demonstrated that it enhances hematopoietic stem and progenitor cells’ (HSPCs’) aberrant differentiation towards the myeloid lineage at the expense of erythropoiesis. To evaluate whether targeting the IL-1β signaling pathway can rescue ineffective erythropoiesis in patients with MDS, we designed a phase 2 non-randomized single-arm clinical trial (NCT04239157) to assess the safety profile and efficacy of the IL-1β inhibitor canakinumab in previously treated lower-risk MDS patients. We enrolled 25 patients with a median age of 74 years; 60% were male, 16% had lower-risk MDS, 84% had intermediate-1 risk MDS according to the International Prognostic Scoring System score, and 80% failed hypomethylating agent therapy. The study met the primary endpoint of defining the clinical activity of canakinumab, and the secondary objective of determining the safety profile, including the rate of transfusion independence, the duration of response, progression-free survival, leukemia-free survival, and overall survival. The overall response rate was 17.4%, with all responses including hematological improvement. Sequential post-hoc prospective single-cell RNA sequencing analyses of HSPCs and bone marrow mononuclear cells at different time points during therapy showed that canakinumab’s on-target effects in hematopoietic populations expressing the IL-1β receptor decreased the TNF-mediated inflammatory signaling pathway but rescued ineffective erythropoiesis only in the context of lower genetic complexity. This study demonstrates that better stratification strategies could target lower-risk MDS patients more effectively.