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The article in the Diabetes & Metabolism Journal discusses the construction of a risk prediction model for Type 2 Diabetic Kidney Disease using deep learning technology. The study was conducted in China and focused on developing a model specifically for Chinese or Asian diabetes patients. The model identified the top 20 features with the highest weights for predicting DKD, emphasizing the importance of factors such as serum creatinine, cholesterol levels, disease duration, and age. The study highlights the challenges of data collection in the Chinese healthcare system and the need for continuous monitoring of key indicators for diabetic patients. [Extracted from the article]

Objective: In our study, we aimed to share the clinical experiences of our center regarding osteosarcoma cases, the most common primary malignant bone tumor in children and adolescents. Materials and Methods: With approval from the Clinical Research Ethics Committee of our center, the data of 59 pediatric patients who were followed up in our center with the diagnosis of osteosarcoma between 2007 and 2021 were evaluated retrospectively. Results: The mean time between the onset of symptoms and diagnosis was 3 months. Although not statistically significant, patients with a diagnostic delay of 3 months or less had a higher rate of recurrence and mortality. 59.3% of patients had metastatic disease, and the presence of metastases was associated with higher rates of recurrence and mortality. Significant number of patients had multiple surgical operations. Amputation as the first operation and the need for multiple surgeries were associated with higher mortality. Pathologically poor response to chemotherapy is associated with mortality. 42.4% of patients died, and the 5-year overall and disease-free survival rates were 47.5% and 30.5%, respectively. Survival rates were highest in non-metastatic and non-relapsed patients, and lowest in metastatic patients and patients with poor response to chemotherapy. Renal problems and cardiotoxicity were most frequently treatment-related complications. Conclusion: Significant improvements have been achieved in the survival and quality of life in osteosarcoma cases compared to previous years; however, there is still a long way to go, and more multicenter and multidisciplinary studies are needed on osteosarcoma. [ABSTRACT FROM AUTHOR]

Purpose: Automatic speech analysis (ASA) and automatic speech recognition systems are increasingly being used in the treatment of speech sound disorders (SSDs). When utilized as a home practice tool or in the absence of the clinician, the ASA system has the potential to facilitate treatment gains. However, the feedback accuracy of such systems varies, a factor that may impact these gains. The current research analyzes the feedback accuracy of a novel ASA algorithm (Amplio Learning Technologies), in comparison to clinician judgments. Method: A total of 3,584 consonant stimuli, produced by 395 American English-speaking children and adolescents with SSDs (age range: 4-18 years), were analyzed with respect to automatic classification of the ASA algorithm, clinician-ASA agreement, and interclinician agreement. Further analysis of results as related to phoneme acquisition categories (early-, middle-, and lateacquired phonemes) was conducted. Results: Agreement between clinicians and ASA classification for sounds produced accurately was above 80% for all phonemes, with some variation based on phoneme acquisition category (early, middle, late). This variation was also noted for ASA classification into acceptable, unacceptable, and unknown (which means no determination of phoneme accuracy) categories, as well as interclinician agreement. Clinician-ASA agreement was reduced for misarticulated sounds. Conclusions: The initial findings of Amplio's novel algorithm are promising for its potential use within the context of home practice, as it demonstrates high feedback accuracy for correctly produced sounds. Furthermore, complexity of sound influences consistency of perception, both by clinicians and by automated platforms, indicating variable performance of the ASA algorithm across phonemes. Taken together, the ASA algorithm may be effective in facilitating speech sound practice for children with SSDs, even in the absence of the clinician. [ABSTRACT FROM AUTHOR]

Radiographs, also known as plain films, are an important tool in medical imaging for diagnosing bone and joint abnormalities. They are often the first imaging study performed due to their accessibility, speed, and affordability. Radiographs can reveal abnormalities that may not be visible on other imaging modalities like MRI and are more specific in diagnosing bone neoplasms. While AI is being explored for radiographic interpretation, it is not yet capable of replacing radiologists. Radiographs are particularly useful in evaluating trauma, joint pain, and bone pain, as they can detect fractures, ligament injuries, and other abnormalities. However, radiologists must have knowledge of normal anatomy and injury mechanisms to interpret radiographs accurately. The article emphasizes the importance of radiographic interpretation and the limitations of other imaging modalities, providing examples of conditions that can be detected through radiographs. Ongoing training and the use of classic resources are highlighted to improve interpretive skills. [Extracted from the article]

The article "Phosducin-like 3 is a novel prognostic and onco-immunological biomarker in glioma: a multi-omics analysis with experimental verification" discusses the potential prognostic value of PDCL3 in glioma. The authors conducted Cox regression analyses and established a nomogram in the TCGA cohort to predict glioma prognosis. However, the study highlights the importance of adhering to the proportional hazards assumption in statistical analysis to ensure the accuracy of predictive models. The authors suggest including interaction terms and stratifying datasets to improve the robustness of the analysis. [Extracted from the article]

The water buffalo (Bubalus bubalis) is susceptible to bovine tuberculosis (TB), which receives increased attention in areas where buffalo breeding is prevalent, such as in Southern Italy, especially in the Campania region, where 70% of the buffalo stock is bred. Since 2012, TB testing in buffalo herds has been conducted using the Single Intradermal Test (SIT), with the Comparative Intradermal test (CIT) used in cases of inconclusive results. From 2012 to 2016, the interferongamma (IFN-γ) test was occasionally employed experimentally in herds with TB outbreaks to expedite eradication efforts. A local TB eradication program was implemented in officially TB-free buffalo herds between 2017 and 2019. This program involves initial screening with SIT, followed by confirmatory tests, including CIT and IFN-γ, for positive reactions. Since June 2019, the IFN-γ test has replaced the CIT in officially TB-free herds upon positive SIT reactions. Additionally, in suspected and confirmed TB-outbreak herds, the IFN-γ test was used at the discretion of the competent authority. Between 2017 and 2019, approximately 295,000 buffaloes in Campania were screened annually with in vivo tests provided by TB eradication programs. During this period, 32,040 animals from 855 herds were tested using the IFN-γ test and 4,895 tested positive. Since 2020, the use of IFN-γ testing has increased, and has become a prerequisite for the acquisition of TB-free status and is being systematically applied for TB outbreak-extinction procedures. The test was performed in all breeding buffaloes in cases of doubtful SIT results in TB-free herds and when TB lesions are detected at slaughter in animals from TB-free herds. This combined approach helped detect more TB outbreaks, and thereby led to a reduction in the TB prevalence and incidence rates. By 2022, the prevalence had decreased to 1.56%, and the incidence had decreased to 0.73%, after the increased use of the IFN-γ test. This study highlights the effectiveness of implemented strategies in reducing TB in this region. Overall, the data demonstrate the successful impact of TB eradication measures and surveillance activities in reducing bubaline TB prevalence and incidence in the Campania region. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to develop and validate prognostic models for predicting overall survival in individuals with gastric carcinoma, specifically focusing on both negative and positive lymphatic metastasis. Methods: A total of 1650 patients who underwent radical gastric surgery at Shanxi Cancer Hospital between May 2002 and December 2020 were included in the analysis. Multiple Cox Proportional Hazards analysis was performed to identify key variables associated with overall survival in both negative and positive lymphatic metastasis cases. Internal validation was conducted using bootstrapping to assess the prediction accuracy of the models. Calibration curves were used to demonstrate the accuracy and consistency of the predictions. The discriminative abilities of the prognostic models were evaluated and compared with the 8th edition of AJCC-TNM staging using Harrell’s Concordance index, decision curve analysis, and time-dependent receiver operating characteristic curves. Results: The nomogram for node-negative lymphatic metastasis included variables such as age, pT stage, and maximum tumor diameter. The C-index for this model in internal validation was 0.719, indicating better performance compared to the AJCC 8th edition TNM staging. The nomogram for node-positive lymphatic metastasis included variables such as gender, age, maximum tumor diameter, neural invasion, Lauren classification, and expression of Her-2, CK7, and CD56. The C-index for this model was 0.674, also outperforming the AJCC 8th edition TNM staging. Calibration curves, time-dependent receiver operating characteristic curves, and decision curve analysis for both nomograms demonstrated excellent prediction ability. Furthermore, significant differences in prognosis between low- and high-risk groups supported the models’ strong risk stratification performance. Conclusion: This study provides valuable risk stratification models for lymphatic metastasis in gastric carcinoma, encompassing both node-positive and negative cases. These models can help identify low-risk individuals who may not require further intervention, while high-risk individuals can benefit from targeted therapies aimed at addressing lymphatic metastasis. [ABSTRACT FROM AUTHOR]

Background: Binary classification models are frequently used to predict clinical deterioration, however they ignore information on the timing of events. An alternative is to apply time-to-event models, augmenting clinical workflows by ranking patients by predicted risks. This study examines how and why time-to-event modelling of vital signs data can help prioritise deterioration assessments using lift curves, and develops a prediction model to stratify acute care inpatients by risk of clinical deterioration. Methods: We developed and validated a Cox regression for time to in-hospital mortality. The model used time-varying covariates to estimate the risk of clinical deterioration. Adult inpatient medical records from 5 Australian hospitals between 1 January 2019 and 31 December 2020 were used for model development and validation. Model discrimination and calibration were assessed using internal–external cross validation. A discrete-time logistic regression model predicting death within 24 h with the same covariates was used as a comparator to the Cox regression model to estimate differences in predictive performance between the binary and time-to-event outcome modelling approaches. Results: Our data contained 150,342 admissions and 1016 deaths. Model discrimination was higher for Cox regression than for discrete-time logistic regression, with cross-validated AUCs of 0.96 and 0.93, respectively, for mortality predictions within 24 h, declining to 0.93 and 0.88, respectively, for mortality predictions within 1 week. Calibration plots showed that calibration varied by hospital, but this can be mitigated by ranking patients by predicted risks. Conclusion: Time-varying covariate Cox models can be powerful tools for triaging patients, which may lead to more efficient and effective care in time-poor environments when the times between observations are highly variable. [ABSTRACT FROM AUTHOR]

Background: Patients with early-stage breast cancer may have a higher risk of dying from other diseases, making a competing risks model more appropriate. Considering subdistribution hazard ratio, which is used often, limited to model assumptions and clinical interpretation, we aimed to quantify the effects of prognostic factors by an absolute indicator, the difference in restricted mean time lost (RMTL), which is more intuitive. Additionally, prognostic factors of breast cancer may have dynamic effects (time-varying effects) in long-term follow-up. However, existing competing risks regression models only provide a static view of covariate effects, leading to a distorted assessment of the prognostic factor. Methods: To address this issue, we proposed a dynamic effect RMTL regression that can explore the between-group cumulative difference in mean life lost over a period of time and obtain the real-time effect by the speed of accumulation, as well as personalized predictions on a time scale. Results: A simulation validated the accuracy of the coefficient estimates in the proposed regression. Applying this model to an older early-stage breast cancer cohort, it was found that 1) the protective effects of positive estrogen receptor and chemotherapy decreased over time; 2) the protective effect of breastconserving surgery increased over time; and 3) the deleterious effects of stage T2, stage N2, and histologic grade II cancer increased over time. Moreover, from the view of prediction, the mean C-index in external validation reached 0.78. Conclusion: Dynamic effect RMTL regression can analyze both dynamic cumulative effects and real-time effects of covariates, providing a more comprehensive prognosis and better prediction when competing risks exist. [ABSTRACT FROM AUTHOR]

Encephalitozoon cuniculi is a microsporidian, domestic rabbits being the main host. The disease can be acute or subclinical, but treatment options are limited and usually with unrewarding results; therefore, diagnosis and prevention of encephalitozoonosis in rabbits are of the utmost importance. This study aims to obtain the first preliminary information of the prevalence of E. cuniculi in the north-western region of Romania. A total of 176 rabbits were clinically examined and 2 mL of blood was sampled from each. An enzyme-linked immunosorbent assay (ELISA) kit by Medicago (Medicago, Uppsala, Sweden) on the resulted blood serum was utilized. Statistical analysis of the results was conducted using the EpiInfo 2000 software (CDC, Atlanta, GA, USA). A total prevalence of 39.2% (69/176) was identified, with statistically significant differences in relation to the rabbits' clinical status, age, season of sampling, breeding system, body condition score and county of origin; the different family farms tested also had a statistically significant difference. This study gives the first preliminary information on this pathogen distribution on Romania's territory, but further studies need to be performed on larger regions to declare the prevalence in the country. [ABSTRACT FROM AUTHOR]

Background/Aim: The activation of phosphatidylinositol 3-kinase (PI3K)/Akt signaling pathway has been implicated in canine soft tissue sarcoma (STS) and may serve as a prognostic marker. This study investigated the correlation between PI3K/Akt activation in tumor cells and tumorinfiltrating lymphocytes (TILs). Materials and Methods: A total of 59 STS samples were labeled via immunohistochemistry to calculate the density of TILs, including CD3+ T cells, CD8+ T cells, CD20+ B cells, and FOXP3+ regulatory T cells. Results: Forty-eight samples (81.3%) had intra-tumoral TILs with a high density of CD3+ T cells (mean: 283.3 cells/mm²) and CD8+ T cells (mean: 134.8 cells/mm²). Conversely, CD20+ B cells (mean: 73.6 cells/mm²) and FOXP3+ regulatory T cells (mean: 9.2 cells/mm²) were scarce. The abundance of CD3+/CD8+, CD3+/CD20+, and CD8+/CD20+ TILs were highly correlated in multivariate analyses (r=0.895, 0.946, and 0.856, respectively). Nonetheless, TIL density was unrelated to clinicopathological parameters (sex, age, tumor location, breed) and tumor grade. The abundance of CD8+ T cells was positively correlated with the activation of PI3K/Akt, indicating that samples with high levels of phospho-Akt and phospho-S6 tend to have a higher CD8+ T cell density (p=0.0032 and 0.0218, respectively). Furthermore, TIL density was correlated with the Ki-67 index, a tumor proliferation and growth marker. Samples with a high Ki-67 index had a significantly higher abundance of CD3+ T cells, CD8+ T cells, and CD20+ B cells (p=0.0392, 0.0254, 0.0380, respectively). Conclusion: PI3K/Akt pathway activation may influence the infiltration of CD8+ T cells within the tumor microenvironment in canine STS. Prospective studies involving a higher number of cases are warranted to confirm these findings. [ABSTRACT FROM AUTHOR]

BACKGROUND: The effective treatment of breast cancer in elderly patients remains a major challenge. OBJECTIVE: To construct a nomogram affecting the overall survival of triple-negative breast cancer (TNBC) and establish a survival risk prediction model. METHODS: A total of 5317 TPBC patients with negative expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) who were diagnosed and received systematic treatment from 2010 to 2015 were collected from the American Cancer Surveillance, Epidemiology and End Results (SEER) database. They were randomly divided into training set (n = 3721) and validation set (n = 1596). Univariate and multivariate Cox regression analysis were used to identify prognostic features, and a nomogram was established to predict the probability of 1-year, 3-year and 5-year OS and BCSS. We used consistency index (C-index), calibration curve, area under the curve (AUC) and decision curve analysis (DCA) to evaluate the predictive performance and clinical utility of the nomogram. RESULTS: The C-indices of the nomograms for OS and BCSS in the training cohort were 0.797 and 0.825, respectively, whereas those in the validation cohort were 0.795 and 0.818, respectively. The receiver operating characteristic (ROC) curves had higher sensitivity at all specificity values as compared with the Tumor Node Metastasis (TNM) system. The calibration plot revealed a satisfactory relationship between survival rates and predicted outcomes in both the training and validation cohorts. DCA demonstrated that the nomogram had clinical utility when compared with the TNM staging system. CONCLUSION: This study provides information on population-based clinical characteristics and prognostic factors for patients with triple-negative breast cancer, and constructs a reliable and accurate prognostic nomogram. [ABSTRACT FROM AUTHOR]

Simple Summary: Colorectal cancer is a common illness. It can spread to the liver in about a quarter of people with colorectal cancer, known as metastases. Previously, people with liver metastases did not survive for long. Thankfully, this is changing. As we understand more about the underlying causes and genetics of the disease, we can tailor treatments to patients on a more individual basis. Treatments like chemotherapy have made a difference in patients' survival, and now newer treatments like immunotherapy can have even greater benefits. Surgery is also changing, with more advanced techniques allowing for better recovery for patients and more aggressive surgery. It is important for surgeons to consider a large number of individual factors when making decisions with patients about their treatment—this is what we mean by "precision surgery". The incidence of colorectal cancer and colorectal liver metastases (CRLM) is increasing globally due to an interaction of environmental and genetic factors. A minority of patients with CRLM have surgically resectable disease, but for those who have resection as part of multimodal therapy for their disease, long-term survival has been shown. Precision surgery—the idea of careful patient selection and targeting of surgical intervention, such that treatments shown to be proven to benefit on a population level are the optimal treatment for each individual patient—is the new paradigm of care. Key to this is the understanding of tumour molecular biology and clinically relevant mutations, such as KRAS, BRAF, and microsatellite instability (MSI), which can predict poorer overall outcomes and a poorer response to systemic therapy. The emergence of immunotherapy and hepatic artery infusion (HAI) pumps show potential to convert previously unresectable disease to resectable disease, in addition to established systemic and locoregional therapies, but the surgeon must be wary of poor-quality livers and the spectre of post-hepatectomy liver failure (PHLF). Volume modulation, a cornerstone of hepatic surgery for a generation, has been given a shot in the arm with the advent of liver venous depletion (LVD) ensuring significantly more hypertrophy of the future liver remnant (FLR). The optimal timing of liver resection for those patients with synchronous disease is yet to be truly established, but evidence would suggest that those patients requiring complex colorectal surgery and major liver resection are best served with a staged approach. In the operating room, parenchyma-preserving minimally invasive surgery (MIS) can dramatically reduce the surgical insult to the patient and lead to better perioperative outcomes, with quicker return to function. [ABSTRACT FROM AUTHOR]

Breast cancer remains a formidable global health challenge, exacting a heavy toll on women's lives and necessitating advanced diagnostic methodologies. This study delves into the domain with an innovative perspective, addressing pertinent limitations in current approaches. Despite significant progress, the prevalence of misclassifications and inadequate diagnostic accuracy persists as a critical concern. Current methods often rely on isolated classification algorithms, leading to suboptimal outcomes and insufficient reliability. To overcome these shortcomings, this research introduces an ensemble learning (voting) framework that reimagines the diagnostic process. This approach leverages a consortium of distinguished convolutional neural network architectures, including DenseNet169, EfficientNetB4, and Xception, collectively enhancing diagnostic precision. By embracing this holistic methodology, the study strives to bridge the existing gap between diagnostic efficiency and clinical reliability. Through meticulous optimization, the proposed model presents a promising trajectory toward significantly elevating the accuracy of breast cancer diagnosis. This study is conducted using the Breast Cancer Histopathological Database (BreakHis) dataset, encompassing diverse magnification factors (40X, 100X, 200X, and 400X), ultimately showcasing a remarkable 98% accuracy in classifying breast cancer images. The findings herald a paradigm shift in diagnostic accuracy, underscoring the potential to revolutionize breast cancer management and bolster the confidence of medical practitioners in their decision-making processes. [ABSTRACT FROM AUTHOR]

Breast cancer poses a global health challenge, yet the influence of ethnicity on the tumor microenvironment (TME) remains understudied. In this investigation, we examined immune cell infiltration in 230 breast cancer samples, emphasizing diverse ethnic populations. Leveraging tissue microarrays (TMAs) and core samples, we applied multiplex immunofluorescence (mIF) to dissect immune cell subtypes across TME regions. Our analysis revealed distinct immune cell distribution patterns, particularly enriched in aggressive molecular subtypes triple-negative and HER2-positive tumors. We observed significant correlations between immune cell abundance and key clinicopathological parameters, including tumor size, lymph node involvement, and patient overall survival. Notably, immune cell location within different TME regions showed varying correlations with clinicopathologic parameters. Additionally, ethnicities exhibited diverse distributions of cells, with certain ethnicities showing higher abundance compared to others. In TMA samples, patients of Chinese and Caribbean origin displayed significantly lower numbers of B cells, TAMs, and FOXP3-positive cells. These findings highlight the intricate interplay between immune cells and breast cancer progression, with implications for personalized treatment strategies. Moving forward, integrating advanced imaging techniques, and exploring immune cell heterogeneity in diverse ethnic cohorts can uncover novel immune signatures and guide tailored immunotherapeutic interventions, ultimately improving breast cancer management. [ABSTRACT FROM AUTHOR]

Background: Immunotherapeutic approaches, including immune checkpoint inhibitor (ICI) therapy, are increasingly recognized for their potential. Despite notable successes, patient responses to these treatments vary significantly. The absence of reliable predictive and prognostic biomarkers hampers the ability to foresee outcomes. This meta-analysis aims to evaluate the predictive significance of circulating myeloid-derived suppressor cells (MDSC) in patients with solid tumors undergoing ICI therapy, focusing on progression-free survival (PFS) and overall survival (OS). Methods: A comprehensive literature search was performed across PubMed and EMBASE from January 2007 to November 2023, utilizing keywords related to MDSC and ICI. We extracted hazard ratios (HRs) and 95% confidence intervals (CIs) directly from the publications or calculated them based on the reported data. A hazard ratio greater than 1 indicated a beneficial effect of low MDSC levels. We assessed heterogeneity and effect size through subgroup analyses. Results: Our search yielded 4,023 articles, of which 17 studies involving 1,035 patients were included. The analysis revealed that patients with lower levels of circulating MDSC experienced significantly improved OS (HR=2.13 [95% CI 1.51-2.99]) and PFS (HR=1.87 [95% CI 1.29-2.72]) in response to ICI therapy. Notably, heterogeneity across these outcomes was primarily attributed to differences in polymorphonuclear MDSC (PMN-MDSC) subpopulations and varying cutoff methodologies used in the studies. The monocytic MDSC (M-MDSC) subpopulation emerged as a consistent and significant prognostic marker across various subgroup analyses, including ethnicity, tumor type, ICI target, sample size, and cutoff methodology. Conclusions: Our findings suggest that standardized assessment of MDSC, particularly M-MDSC, should be integral to ICI therapy strategies. These cells hold the promise of identifying patients at risk of poor response to ICI therapy, enabling tailored treatment approaches. Further research focusing on the standardization of markers and validation of cutoff methods is crucial for integrating MDSC into clinical practice. [ABSTRACT FROM AUTHOR]

Simple Summary: Risk assessment in early breast cancer is critical for clinical decisions, but defining risk categories poses a significant challenge. The integration of conventional histopathology and biomarkers with artificial intelligence (AI) techniques, including machine learning and deep learning, has the potential to offer more precise information. AI applications extend beyond detection to histological subtyping, grading, and molecular feature identification. The successful integration of AI into clinical practice requires collaboration between histopathologists, molecular pathologists, computational pathologists, and oncologists to optimize patient outcomes. Effective risk assessment in early breast cancer is essential for informed clinical decision-making, yet consensus on defining risk categories remains challenging. This paper explores evolving approaches in risk stratification, encompassing histopathological, immunohistochemical, and molecular biomarkers alongside cutting-edge artificial intelligence (AI) techniques. Leveraging machine learning, deep learning, and convolutional neural networks, AI is reshaping predictive algorithms for recurrence risk, thereby revolutionizing diagnostic accuracy and treatment planning. Beyond detection, AI applications extend to histological subtyping, grading, lymph node assessment, and molecular feature identification, fostering personalized therapy decisions. With rising cancer rates, it is crucial to implement AI to accelerate breakthroughs in clinical practice, benefiting both patients and healthcare providers. However, it is important to recognize that while AI offers powerful automation and analysis tools, it lacks the nuanced understanding, clinical context, and ethical considerations inherent to human pathologists in patient care. Hence, the successful integration of AI into clinical practice demands collaborative efforts between medical experts and computational pathologists to optimize patient outcomes. [ABSTRACT FROM AUTHOR]

Background and Aims: Around 750,000 patients per year will be cured of HCV infection until 2030. Those with compensated advanced chronic liver disease remain at risk for hepatic decompensation and de novo HCC. Algorithms have been developed to stratify risk early after cure; however, data on long-term outcomes and the prognostic utility of these risk stratification algorithms at later time points are lacking., Approach and Results: We retrospectively analyzed a cohort of 2335 patients with compensated advanced chronic liver disease (liver stiffness measurement≥10 kPa) who achieved HCV-cure by interferon-free therapies from 15 European centers (median age 60.2±11.9 y, 21.1% obesity, 21.2% diabetes).During a median follow-up of 6 years, first hepatic decompensation occurred in 84 patients (3.6%, incidence rate: 0.74%/y, cumulative incidence at 6 y: 3.2%); 183 (7.8%) patients developed de novo HCC (incidence rate: 1.60%/y, cumulative incidence at 6 y: 8.3%), with both risks being strictly linear over time.Baveno VII criteria to exclude (FU-liver stiffness measurement <12 kPa and follow-up platelet count >150 g/L) or rule-in (FU-liver stiffness measurement ≥25 kPa) clinically significant portal hypertension (CSPH) stratified the risk of hepatic decompensation with proportional hazards. Estimated probability of CSPH discriminated patients developing versus not developing hepatic decompensation in the gray zone (ie, patients meeting none of the above criteria).Published HCC risk stratification algorithms identified high-incidence and low-incidence groups; however, the size of the latter group varied substantially (9.9%-69.1%). A granular "HCC-sustained virologic response" model was developed to inform an individual patient's HCC risk after HCV-cure., Conclusions: In patients with compensated advanced chronic liver disease, the risks of hepatic decompensation and HCC remain constant after HCV-cure, even in the long term (>3 y). One-time post-treatment risk stratification based on noninvasive criteria provides important prognostic information that is maintained during long-term follow-up, as the hazards remain proportional over time., (Copyright © 2024 American Association for the Study of Liver Diseases.)

Clinical research has historically failed to include representative levels of historically underrepresented populations and these inequities continue to persist. Ensuring representativeness in clinical trials is crucial for patients to receive clinically appropriate treatment and have equitable access to novel therapies; enhancing the generalizability of study results; and reducing the need for post-marketing commitments focused on underrepresented groups. As demonstrated by recent legislation and guidance documents, regulatory agencies have shown an increased interest in understanding how novel therapies will impact the patient population that will receive them. Despite these efforts, a systematic approach to measure and optimize representativeness remains underdeveloped. Here, we introduce the novel Population Optimization, Representativeness Evaluation, and Fine-tuning Framework, designed to quantify and enhance representativeness. Our framework includes methods for evaluating overall and subgroup representativeness, identifying drivers of non-representativeness, and optimizing eligibility criteria to achieve representative populations. We demonstrate our framework by selecting patients who met the eligibility criteria for nine oncology clinical trials from a nationwide electronic health record-derived de-identified database and quantifying the representativeness of each trial's eligible population. This framework addresses gaps in current literature by providing a comprehensive, data-driven approach to enhance the representativeness of clinical trials, thereby supporting regulatory and internal decision-making processes. This framework is adaptable to various disease indications and can be extended to evaluate enrolled study samples, ensuring that clinical trials are representative., (© 2024 The Author(s). Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Background: Nested case–control (NCC) designs are efficient for developing and validating prediction models that use expensive or difficult-to-obtain predictors, especially when the outcome is rare. Previous research has focused on how to develop prediction models in this sampling design, but little attention has been given to model validation in this context. We therefore aimed to systematically characterize the key elements for the correct evaluation of the performance of prediction models in NCC data. Methods: We proposed how to correctly evaluate prediction models in NCC data, by adjusting performance metrics with sampling weights to account for the NCC sampling. We included in this study the C-index, threshold-based metrics, Observed-to-expected events ratio (O/E ratio), calibration slope, and decision curve analysis. We illustrated the proposed metrics with a validation of the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA version 5) in data from the population-based Rotterdam study. We compared the metrics obtained in the full cohort with those obtained in NCC datasets sampled from the Rotterdam study, with and without a matched design. Results: Performance metrics without weight adjustment were biased: the unweighted C-index in NCC datasets was 0.61 (0.58–0.63) for the unmatched design, while the C-index in the full cohort and the weighted C-index in the NCC datasets were similar: 0.65 (0.62–0.69) and 0.65 (0.61–0.69), respectively. The unweighted O/E ratio was 18.38 (17.67–19.06) in the NCC datasets, while it was 1.69 (1.42–1.93) in the full cohort and its weighted version in the NCC datasets was 1.68 (1.53–1.84). Similarly, weighted adjustments of threshold-based metrics and net benefit for decision curves were unbiased estimates of the corresponding metrics in the full cohort, while the corresponding unweighted metrics were biased. In the matched design, the bias of the unweighted metrics was larger, but it could also be compensated by the weight adjustment. Conclusions: Nested case–control studies are an efficient solution for evaluating the performance of prediction models that use expensive or difficult-to-obtain biomarkers, especially when the outcome is rare, but the performance metrics need to be adjusted to the sampling procedure. [ABSTRACT FROM AUTHOR]

This study investigates breast cancer survival rates between 2000 and 2022 in northern Israel, focusing on ethnicity, socioeconomic status, age at diagnosis, and the Charlson Comorbidity Index. Analyzing data from Clalit Health Services, we studied 8,431 breast cancer patients (6,395 Jewish, 2,036 Arab). We compared five- and ten-year survival rates across different demographics. Ethnicity showed a minor impact on survival (OR 1.12, 95% CI: 0.93 - 1.35). Socioeconomic status had a significant effect, with a higher level of improving survival (OR 2.50, 95% CI: 2.04 - 3.08). Age was crucial; women 18-39 had better survival than 60-100, but no significant difference was found between the 18-39 and 40-59 age groups [OR (CI 0.90 - 1.53, p = 0.231)]. For the Charlson Comorbidity Index, women with scores of 3-10 showed lower survival compared to scores of 0 and 1-2. There was a notable improvement in fiveyear survival rates among patients aged 18-59 diagnosed from 2009-2018 (90.7%) compared to 2000-2008 (86.9%) (p = 0.0046), but not in patients aged 60-100. The study highlights that socioeconomic status, age, and comorbidity scores are significant in determining survival rates for breast cancer. The improvement in survival rates for younger patients diagnosed more recently reflects advancements in treatment and care. This research provides valuable insights into the factors affecting breast cancer survival rates, underscoring the role of socioeconomic status, age, and comorbidities while also highlighting the progress in breast cancer treatment over recent years. [ABSTRACT FROM AUTHOR]

* OBJECTIVE: To provide an updated overview of available prognostic models for people with chronic low back pain (LBP) in primary care. * DESIGN: Prognosis systematic review * LITERATURE SEARCH: We searched for relevant studies on MEDLINE, Embase, Web of Science, and CINAHL databases (up to July 13, 2022), and performed citation tracking in Web of Science. * STUDY SELECTION CRITERIA: We included observational (cohort or nested case-control) studies and randomized controlled trials that developed or validated prognostic models for adults with chronic LBP in primary care. The outcomes of interest were physical functioning, pain intensity, and health-related quality of life at any follow-up time-point. * DATA SYNTHESIS: Data were extracted using the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS), and the Prediction model Risk of Bias Assessment Tool (PROBAST) tool was used to evaluate the risk of bias of the models. Due to the number of studies retrieved and the heterogeneity, we reported the results descriptively. * RESULTS: Ten studies (out of 5593 hits screened) with 34 models met our inclusion criteria, of which six are development studies and four are external validation studies. Five studies reported the area under the curve of the models (ranging from 0.48 to 0.84), whereas no study reported calibration indices. The most promising model is the Örebro Musculoskeletal Pain Screening Questionnaire Short-Form. * CONCLUSIONS: Given the high risk of bias and lack of external validation, we cannot recommend that clinicians use prognostic models for patients with chronic LBP in primary care settings. [ABSTRACT FROM AUTHOR]

Background: Many papers exploring the role of resectioning metastases in colorectal cancer (CRC) have focused mainly on liver and lung sites, showing improved survival compared with non-resectional therapies. However, data about exceptional metastatic sites such as splenic metastases (SMs) are scarce. This paper aims to assess the role and effectiveness of splenectomy in the case of isolated metachronous SM of CRC origin. Methods: The patients' data were extracted after a comprehensive literature search through public databases for articles reporting patients with splenectomies for isolated metachronous SM of CRC origin. Potential predictors of survival were explored, along with demographic, diagnostic, pathology, and treatment data for each patient. Results: A total of 83 patients with splenectomies for isolated metachronous SM of CRC origin were identified. The primary CRC was at an advanced stage (Duke's C—70.3%) and on the left colon (45.5%) for most patients, while the median interval between CRC resection and SM was 24 months. The median overall survival after splenectomy was 84 months, and patients younger than 62 years presented statistically significantly worse overall survival rates than those ≥62 years old (p = 0.011). There was no significant impact on the long-term outcomes for factors including primary tumor location or adjuvant chemotherapy (p values ≥ 0.070, ns). Laparoscopic splenectomy was increasingly used in the last 20 years from 2002 (33.3% vs. 0%, p < 0.001). Conclusions: Splenectomy is the optimal treatment for patients with isolated metachronous SM of CRC, with the laparoscopic approach being increasingly used and having the potential to become a standard of care. Encouraging long-term survival rates were reported in the context of a multidisciplinary approach. Younger ages are associated with worse survival. Perioperative chemotherapy in the context of a patient diagnosed with SM of CRC origin appears to be a reasonable option, although the present study failed to show any significant impact on long-term survival. [ABSTRACT FROM AUTHOR]

Simple Summary: Bladder cancer is the sixth most common cancer in the world. With 73 years, bladder cancer has the highest age-at-diagnosis of all cancers. While the surgical removal of the bladder remains the standard-of-care treatment for advanced muscle-invasive disease, around half of patients still metastasize. Then, platinum-based chemotherapy is recommended as the first-line treatment. However, only about half of those patients are eligible to receive chemotherapy, and novel immune-checkpoint inhibitors are restricted to biomarker (PD-L1)-positive patients. In our study, we demonstrate that PD-L1-positive patients show slower progression. However, there is no benefit in overall survival, emphasizing the need for novel and more reliable biomarkers in the future. Background: Our study endeavors to elucidate the clinical implications of PD-L1 positivity in individuals afflicted with advanced urothelial carcinoma of the bladder (UCB). Methods: Patients with advanced UCB were prospectively enrolled following a radical cystectomy (RC) performed within January 2017 to December 2022 at our tertiary referral center. The clinical outcome, defined as the progression-free survival (PFS) and overall survival (OS) on systemic treatment, was analyzed using an χ2-test, Mann–Whitney U-test, the Kaplan–Meier method, and a log-rank test. Results: A total of 648 patients were included following an RC performed within January 2017 to December 2022. Their PD-L1 status was analyzed with the primary PD-L1-specific antibody (clone SP263, Ventana) and defined both by the CPS and IC-score in 282 patients (43.5%) with a high risk (pT3–pT4 and/or lymph node involvement) or metastatic UCB. While the median PFS was significantly prolonged 5-fold in PD-L1+ patients, we found no difference in OS, regardless of PD-L1 status, or treatment regimen. Conclusions: While PD-L1 positivity indicates prolonged PFS, the presence of PD-L1 does not influence OS rates, suggesting its limited usefulness as a prognostic biomarker in bladder cancer. However, the positive correlation between an PD-L1 status and a sustained response to ICI treatments indicates its potential role as a predictive biomarker. Further research is required to understand how the predictive value of PD-L1 positivity may extend to the use of ICIs in combination with antibody-drug conjugates. [ABSTRACT FROM AUTHOR]

Tumor-infiltrating lymphocytes (TILs) are pivotal in the immune response against breast cancer (BC), with their prognostic and predictive significance varying across BC subtypes. In triple-negative BC (TNBC), higher TIL levels correlate with improved prognosis and treatment response, guiding therapeutic strategies and potentially offering avenues for treatment de-escalation. In metastatic TNBC, TILs identify patients with enhanced immunotherapy response. HER2+ BC, similar to TNBC, exhibits positive correlations between TILs and treatment response, especially in neoadjuvant settings. Luminal BC generally has low TILs, with limited prognostic impact. Single hormone receptor-positive BCs show distinct TIL associations, emphasizing subtype-specific considerations. TILs in ductal carcinoma in situ (DCIS) display ambiguous prognostic significance, necessitating further investigation. Standardizing TIL assessment methods is crucial for unlocking their full potential as biomarkers, guiding treatment decisions, and enhancing patient care in BC. [ABSTRACT FROM AUTHOR]

Similar to invasive breast cancer, ductal carcinoma in situ is also going through a phase of changes not only from a technical but also a conceptual standpoint. From prescribing radiotherapy to everyone to personalized approaches, including radiotherapy omission, there is still a lack of a comprehensive framework to guide radiation oncologists in decision making. Many pieces of the puzzle are finding their place as high-quality data mature and are disseminated, but very often, the interpretation of risk factors and the perception of risk remain very highly subjective. Sharing the therapeutic choice with patients requires effective communication for an understanding of risks and benefits, facilitating an informed decision that does not increase anxiety and concerns about prognosis. The purpose of this narrative review is to summarize the current state of knowledge to highlight the tools available to radiation oncologists for managing DCIS, with an outlook on future developments. [ABSTRACT FROM AUTHOR]

Wildlife can carry pathogenic organisms, including viruses, bacteria, parasites, and fungi, which can spread to humans and cause mild to serious illnesses and even death. Spreading through animal feces, these pathogens significantly contributes to the global burden of human diseases. Therefore, the present study investigated the prevalence of zoonotic bacterial pathogens, such as Salmonella spp., Escherichia coli, and Shiga toxin-producing E. coli (STEC), in animal feces. Between September 2015 and August 2017, 699 wildlife fecal samples were collected from various agricultural production regions and mountainous areas in South Korea. Fecal samples were collected from wild mammals (85.26%, 596/699) and birds (14.73%, 103/699). Salmonella spp. and E. coli were present in 3% (21/699) and 45.63% (319/699) of the samples, respectively. Moreover, virulence genes stx1 and both stx1 and stx2 were detected in 13.30% (93/699) and 0.72% (5/699) of the samples, respectively. The 21 Salmonella spp. were detected in badgers (n = 5), leopard cats (n = 7), wild boars (n = 2), and magpies (n = 7); STEC was detected in roe deer, water deer, mice, and wild boars. Through phylogenetic and gene-network analyses, the Salmonella spp. isolates (n = 21 laboratory isolates, at least one isolate from each Salmonella-positive animal fecal sample, and n = 6 widely prevalent reference Salmonella serovars) were grouped into two major lineages: S. enterica subsp. enterica and S. enterica subsp. diarizonae. Similarly, 93 E. coli isolates belonged to stx1, including three major lineages (groups 1–3), and stx1 and stx2 detected groups. To the best of our knowledge, this is the first report of a wild leopard cat serving as a reservoir for Salmonella spp. in South Korea. The research findings can help manage the potential risk of wildlife contamination and improve precautionary measures to protect public health. [ABSTRACT FROM AUTHOR]

Background Low-impact genetic variants identified in population-based genetic studies are not routinely measured as part of clinical genetic testing in familial breast cancer (BC). We studied the consequences of integrating an established Polygenic Risk Score (PRS) (BCAC 313, PRS313) into clinical sequencing of women with familial BC in Sweden. Methods We developed an add-on sequencing panel to capture 313 risk variants in addition to the clinical screening of hereditary BC genes. Index patients with no pathogenic variant from 87 families, and 1000 population controls, were included in comparative PRS calculations. Including detailed family history, sequencing results and tumour pathology information, we used BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) V.6 to estimate contralateral and lifetime risks without and with PRS313. Results Women with BC but no pathogenic variants in hereditary BC genes have a higher PRS313 compared with population controls (mean+0.78 SD, p<3e-9). Implementing PRS313 in the clinical risk estimation before their BC diagnosis would have changed the recommended follow-up in 24%-45% of women. Conclusions Our results show the potential impact of incorporating PRS313 directly in the clinical genomic investigation of women with familial BC. [ABSTRACT FROM AUTHOR]

Home parenteral nutrition (HPN) is increasingly prescribed for patients with advanced cancer. This therapy improves free-fat mass, quality of life and survival, but it is not free from complications, especially catheter-related bloodstream infections (CRBSIs). The use of commercial multichamber bags in HPN has not been extensively explored in oncologic patients and their association with complications is not well known. In this prospective cohort study, we included 130 patients with advanced cancer and HPN. We compared the effects of individual compounded bags (n = 87) vs. commercial multichamber bags (n = 43) on complications. There were no differences in any complication, including thrombosis (p > 0.05). There were 0.28 episodes of CRBSI per 1000 catheter days in the individual compounded bag group and 0.21 in the multichamber bag group (p > 0.05). A total of 34 patients were weaned off HPN, 22 with individual bags and 12 with multichamber bags (p = 0.749). Regarding survival when on HPN, the group with individual bags showed a median of 98 days (95% CI of 49–147), whereas those with multichamber bags showed a median of 88 days (95% CI of 43–133 (p = 0.913)). In conclusion, commercial multichamber bags for HPN in patients with advanced cancer are non-inferior when compared to individual compounded bags in terms of complications. [ABSTRACT FROM AUTHOR]

Background: Contralateral breast cancer (CBC) is the most common second primary cancer diagnosed in breast cancer survivors, yet the understanding of the genetic susceptibility of CBC, particularly with respect to common variants, remains incomplete. This study aimed to investigate the genetic basis of CBC to better understand this malignancy. Findings: We performed a genome-wide association analysis in the Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study of women with first breast cancer diagnosed at age < 55 years including 1161 with CBC who served as cases and 1668 with unilateral breast cancer (UBC) who served as controls. We observed two loci (rs59657211, 9q32, SLC31A2/FAM225A and rs3815096, 6p22.1, TRIM31) with suggestive genome-wide significant associations (P < 1 × 10–6). We also found an increased risk of CBC associated with a breast cancer-specific polygenic risk score (PRS) comprised of 239 known breast cancer susceptibility single nucleotide polymorphisms (SNPs) (rate ratio per 1-SD change: 1.25; 95% confidence interval 1.14–1.36, P < 0.0001). The protective effect of chemotherapy on CBC risk was statistically significant only among patients with an elevated PRS (Pheterogeneity = 0.04). The AUC that included the PRS and known breast cancer risk factors was significantly elevated. Conclusions: The present GWAS identified two previously unreported loci with suggestive genome-wide significance. We also confirm that an elevated risk of CBC is associated with a comprehensive breast cancer susceptibility PRS that is independent of known breast cancer risk factors. These findings advance our understanding of genetic risk factors involved in CBC etiology. [ABSTRACT FROM AUTHOR]

Objective: To perform an external validation of the Dat'AIDS score for predicting 5‐year overall mortality among people with HIV (PWH) aged 60 years or older. Methods: This was a multi‐centre prospective cohort study at all sites participating in the Swiss HIV Cohort Study (SHCS). We calculated the Dat'AIDS score in PWH aged 60 years or older at their first visit between 1 January 2015 and 1 January 2020. People living with HIV‐2 and those whose Dat'AIDS score could not be calculated were excluded. Patients were followed until 1 January 2020. The primary endpoint was all‐cause mortality. Vital status was collected throughout the study period. We obtained population and score descriptive statistics and assessed the score's discrimination and calibration. Results: We included 2205 participants (82% male) of median [interquartile range (IQR)] age 62.0 (60.3–67.0) years, mostly with viraemia <50 copies/mL (92.7%). Median follow‐up time was 15.9 years and median (IQR) CD4 cell count at enrolment was 586 (420–782) cells/μL. In all, 152 deaths were recorded during a total follow‐up period of 7147 patient‐years. The median (IQR) observed Dat'AIDS score was 3 (0–8). Discriminative capacities were good as the C‐statistic was 0.73 (95% CI: 0.69–0.77) and consistent across all subgroups. Comparison of observed and expected survival probabilities showed good calibration. Conclusions: External validation of the Dat'AIDS score in patients aged 60 years or older showed that it could be a useful tool not only for research purposes, but also to identify older patients at a higher mortality risk and to tailor the most appropriate interventions. [ABSTRACT FROM AUTHOR]

This systematic review article analysed and evaluated the current literature on sustainable educational technology in higher-education institutions (HEI). University stakeholders aspire to have any educational technologies employed be sustainable beyond short-term solutions. Identifying these sustainable factors requires reviews of recent studies, particularly with the insightful experience of the recent pandemic. Unfortunately, systematic reviews on sustainability were few and focused more on specific modalities. Hence, this present study reviewed past studies (published between 2015 and 2021) to identify the types of educational technology or modality being studied on the aspects of sustainability, the topic of interests that contribute to the challenges in online learning, and the themes and subthemes that are critical to the sustainable use of online education. Guided by the preferred reporting items for systematic reviews and metaanalyses (PRISMA) to review five journal databases (Scopus, ProQuest, Web of Science (WoS), Emerald and Google Scholar), 44 articles were analysed systematically. Four themes emerged from the analysis: technology related, teaching and learning, ethical aspects, and instructional support, as well as 12 subthemes. A conceptual framework was proposed, and other recommendations were discussed at the end of the paper for future research. [ABSTRACT FROM AUTHOR]