Search Results (78)

Background/Objectives: Disparities in multiple myeloma (MM) survival occur based on factors like genetics, age, race, income level, and access to healthcare. The impact of age at diagnosis on MM survival is not fully understood and continues to draw research attention. This study explores the link between age at diagnosis and survival outcomes using data from the University of Arkansas Medical Sciences Myeloma Center Database (MMDB). Methods: Kaplan–Meier curves and Cox models were used to analyze the data. The log-transformed age variable strongly predicted survival. Results: The analysis found survival curves showing that patients in lower age brackets tend to have better survival profiles. Thus, for example, those in the oldest category (>70) showed the steepest decline, while the youngest age category (under 40) had better survival. Spline functions identified a non-linear relationship between age and survival. The likelihood ratio test, Wald test, and log-rank score test confirmed that the overall model was statistically significant, indicating that the spline-based approach effectively captured the relationship between age and survival. Further analysis using a stratified Cox model by age group showed significant risk differences. Patients aged 50–59, 60–69, and over 70 all had higher risks of death compared to younger patients, with those over 70 having a 3.3 times greater risk. Conclusions: In conclusion, the study confirmed that age at diagnosis has a significant association with survival outcomes for MM patients. Full article

Background: The rising prevalence of neurodegenerative conditions such as dementia underscores the impact of population aging. Consequently, long-term care needs have increased and are often met by family members through informal caregiving, thereby supporting formal care systems by reducing associated costs. These caregivers face physical and mental health challenges, raising concerns about their psychological well-being and prompting interest in both clinical and psychosocial research. Ryff’s eudaimonic model offers a robust framework for the assessment of psychological well-being; yet, in Romania, data on this population segment remain limited. Objective: This study aimed to compare the psychological well-being of Romanian dementia family caregivers with a reference population from the Romanian adaptation of the 54-item Ryff Psychological Well-Being Scale, and to explore how sociodemographic characteristics relate to relevant differences across well-being dimensions. Methods: A cross-sectional study was conducted among 70 Romanian family caregivers recruited from a single clinical hospital in Bucharest, Romania. Caregivers completed the 54-item Ryff Scale (Romanian adaptation), and scores were compared to reference values using one-sample t-tests with bootstrap confidence intervals. The most relevant dimension (purpose in life) was dichotomized and further examined in relation to sociodemographic and caregiving variables using Chi-squared and Fisher’s exact tests. Results: Caregivers reported significantly lower scores compared to the reference population in purpose in life (p < 0.001, d = −1.01), personal growth (p < 0.001, d = −0.91), and positive relations (p = 0.01, d = −0.30). The most pronounced deficit was observed in purpose in life, with 85.7% of caregivers scoring below the reference mean. This dimension was further examined in relation to caregiver characteristics. Retirement status showed a statistically significant association with Purpose in Life, with retired caregivers more likely to report lower scores (χ² (1) = 4.04, p = 0.04), supported by the likelihood ratio test (p = 0.01) and a linear trend (p = 0.05). Additional marginal associations were found for household income (p = 0.14) and whether the patient slept in a separate room (p = 0.15), suggesting possible links between caregiver well-being and economic or environmental conditions. Conclusions: The study findings highlight notable psychological vulnerabilities among Romanian dementia caregivers, particularly in purpose in life and personal growth. Associations with structural and contextual factors such as retirement status, income, and caregiving environment suggest that caregiver well-being is shaped by broader socioeconomic conditions. While the magnitude of these deficits may be underestimated due to elevated stress levels in the reference group, the findings underscore the need for targeted clinical, social, and policy-level interventions aimed at strengthening existential meaning and personal development in culturally specific settings. Full article

Background: Globally, uncorrected refractive errors are recognized as the primary cause of visual impairment and blindness. According to a report by the World Health Organization (WHO), providing spectacle lenses at an affordable cost remains a significant challenge, particularly for underprivileged populations in developing countries. This challenge contributes to the low compliance with spectacle wear worldwide. However, the benefits of wearing spectacles are influenced by the perceptions of the population regarding spectacle use. Methods: A quantitative, cross-sectional survey-based study was conducted at a superior educative center in Oman, the University of Buraimi. Participants were recruited from the four major colleges, namely, the College of Health Sciences (COHS), College of Business (COB), College of Engineering (COE), and College of Law (COL), and the Center for Foundation Studies (CFS). This study was conducted over the period from 18 December 2022 to 18 December 2023. Essential data were collected using an electronic questionnaire facilitated by the Google platform. The initial section of the questionnaire outlines this study’s objectives and its benefits to the community. The digital survey comprises three sections: the first section addresses the sociodemographic profile of the participants; the second section explores perceptions related to spectacles; and the third section examines visual symptoms associated with spectacle wear. In this study, a pre-tested survey was administered following consultation with a panel of three subject matter experts who reviewed the clarity and content validity of the test items. Data analyses were performed using descriptive statistics, and linear regression was applied to assess the effect of socioeconomic profile on perceptions of spectacles. Additionally, data entry, processing, and analysis were conducted using SPSS 25 software. The overall mean score for spectacle-related visual symptoms was 2.51 ± 0.75, indicating a moderate level of symptom occurrence. Results: A total of 415 participants (N = 415) were included in this study, comprising 133 males (32.0%) and 282 females (68.0%). The most prominent symptoms related to spectacle perception were “light sensitivity” and “eye pain”, with mean values of 3.03 ± 1.30 and 3.04 ± 1.25, respectively. Additionally, 249 participants (60%) reported moderate concern regarding spectacle-related visual symptoms. Among female participants, 118 (41.8%) exhibited little concern about visual symptoms associated with spectacle wear, whereas this was observed in 25.6% of male participants. Descriptive statistics indicated the mean perceived spectacle-related disadvantages score measured on a scale of 0 to 4 was 2.88 ± 1.16 (57.69% ± 23.15% in percentages), reflecting a moderate perception of such disadvantages. The linear regression model demonstrated statistical significance, as indicated by the likelihood ratio chi-square = 199.194 (df = 15, p < 0.001). The most significant predictor was study major (χ² = 72.922, p < 0.001). Conclusions: The present study indicates that undergraduate students generally exhibit a low perception of the disadvantages associated with wearing spectacles. Randomized sampling should be preferred in future studies to the convenience sampling technique. The most frequently reported visual symptoms include “light sensitivity and eye pain” among spectacle wearers. Therefore, it is imperative to implement health education programs and foundational studies across colleges to address these issues among undergraduate university students. Full article

Background and Objectives: Although numerous studies have explored various predictors of positive airway pressure (PAP) adherence, the potential impact of objective sleep scoring data obtained during PAP titration on adherence has not been thoroughly investigated. The objective of this study was to evaluate the association between objective sleep parameters obtained from PAP titration, including sleep efficiency (SE), wake after sleep onset (WASO), and sleep latency (SL), and short-term PAP adherence in individuals with obstructive sleep apnea (OSA). Materials and Methods: A total of 227 individuals with a confirmed diagnosis of OSA underwent overnight PAP titration and were subsequently divided into adherence and non-adherence groups. Baseline demographic characteristics, clinical data, diagnostic polysomnography results, and PAP titration data were obtained for all subjects. Paired sample t-tests were utilized to assess differences in sleep parameters between diagnostic polysomnography and PAP titration within each group. Binomial logistic regression was used to evaluate the predictive value of changes in SE, WASO, and SL for PAP adherence and to determine optimal cut-off values. A χ² analysis was conducted to assess the relationship between categorical improvements in SE and WASO and adherence to PAP therapy. Results: Among the study cohort, 176 (77.5%) participants were classified as adherent, while 51 (22.5%) participants were classified as non-adherent. SE during PAP titration (83.3 ± 12.6%) was significantly higher compared to baseline polysomnography (80.9 ± 12.4%, p = 0.020), and WASO was significantly reduced (63.9 ± 58.9 min vs. 77.7 ± 67.2 min, p = 0.016). No significant difference was observed in SL between the two groups. Logistic regression analysis indicated that increased SE (odds ratio [OR]: 1.025, p = 0.039) and decreased WASO (OR: 0.994, p = 0.027) both served as significant predictors of PAP adherence, but the overall predictive ability of these indicators was modest (area under the curve 0.60 for SE; 0.62 for WASO). The optimal thresholds distinguishing adherence were ΔSE ≥ 2.39% and ΔWASO < −1.5 min. Participants who exhibited improvements in SE (χ² = 5.296, p = 0.021) and WASO (χ² = 6.877, p = 0.009) demonstrated a significantly higher likelihood of adhering to PAP therapy. Conclusions: The findings demonstrate that objective increases in sleep quality, specifically elevated SE and decreased WASO during initial PAP titration, are significantly associated with short-term PAP adherence among patients with OSA. Full article

Background/Objectives: Inflammation-based markers have emerged as potential prognostic tools in hepatocellular carcinoma (HCC), but comparative data with classical prognostic factors in untreated HCC are limited. This study aimed to evaluate and compare the prognostic performance of inflammatory and conventional markers using Harrell’s concordance index (C-index). Methods: This retrospective study included 250 patients with untreated HCC. Prognostic variables included age, BCLC stage, Child–Pugh classification, Milan criteria, MELD score, AFP, albumin, Charlson comorbidity index, and the inflammation-based markers neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), Systemic Inflammation Response Index (SIRI), and Systemic Immune-inflammation Index (SIII). Survival was analyzed using Cox regression. Predictive performance was assessed using the C-index, Akaike Information Criterion (AIC), and likelihood ratio tests. Results: Among the classical markers, BCLC showed the highest predictive performance (C-index: 0.717), while NLR ranked highest among the inflammatory markers (C-index: 0.640), above the MELD score and Milan criteria. In multivariate analysis, NLR ≥ 2.3 remained an independent predictor of overall survival (HR: 1.787; 95% CI: 1.264–2.527; p < 0.001), along with BCLC stage, albumin, Charlson index, and Milan criteria. Including NLR in the model modestly improved the C-index (from 0.781 to 0.794) but significantly improved model fit (Δ–2LL = 10.75; p = 0.001; lower AIC). Conclusions: NLR is an accessible, cost-effective, and independent prognostic marker for overall survival in untreated HCC. It shows discriminative power comparable to or greater than most conventional predictors and may complement classical stratification tools for HCC. Full article

Crossover trials are specifically designed to evaluate treatment effects within individual participants through within-subject comparisons. In a standard AB/BA crossover trial, participants are randomly allocated to one of two treatment sequences: either the AB sequence (where patients receive treatment A first and then cross over to treatment B after a washout period) or the BA sequence (where patients receive B first and then cross over to A after a washout period). Asymptotic and approximate unconditional test procedures, based on two Wald-type statistics, the likelihood ratio statistic, and the score test statistic for the odds ratio (OR), are developed to evaluate the equality of treatment effects in this trial design. Additionally, confidence intervals for OR are constructed, accompanied by an approximate sample size calculation methodology to control the interval width at a pre-specified precision. Empirical analyses demonstrate that asymptotic test procedures exhibit robust performance in moderate to large sample sizes, though they occasionally yield unsatisfactory type I error rates when the sample size is small. In such cases, approximate unconditional test procedures emerge as a rigorous alternative. All proposed confidence intervals achieve satisfactory coverage probabilities, and the approximate sample size estimation method demonstrates high accuracy, as evidenced by empirical coverage probabilities aligning closely with pre-specified confidence levels under estimated sample sizes. To validate practical utility, two real examples are used to illustrate the proposed methodologies. Full article

Peripheral artery disease (PAD) is associated with an elevated risk of major adverse cardiovascular events (MACE). Despite this, few reliable biomarkers exist to identify patients at heightened risk of MACE. Growth differentiation factor 15 (GDF15), a stress-responsive cytokine implicated in inflammation, atherosclerosis, and thrombosis, has been broadly studied in cardiovascular disease but remains underexplored in PAD. This study aimed to evaluate the prognostic utility of GDF15 for predicting 2-year MACE in PAD patients using explainable statistical and machine learning approaches. We conducted a prospective analysis of 1192 individuals (454 with PAD and 738 without PAD). At study entry, patient plasma GDF15 concentrations were measured using a validated multiplex immunoassay. The cohort was followed for two years to monitor the occurrence of MACE, defined as stroke, myocardial infarction, or death. Baseline GDF15 levels were compared between PAD and non-PAD participants using the Mann–Whitney U test. A machine learning model based on extreme gradient boosting (XGBoost) was trained to predict 2-year MACE using 10-fold cross-validation, incorporating GDF15 and clinical variables including age, sex, comorbidities (hypertension, diabetes, dyslipidemia, congestive heart failure, coronary artery disease, and previous stroke or transient ischemic attack), smoking history, and cardioprotective medication use. The model’s primary evaluation metric was the F1 score, a validated measurement of the harmonic mean of the precision and recall values of the prediction model. Secondary model performance metrics included precision, recall, positive likelihood ratio (LR+), and negative likelihood ratio (LR-). A prediction probability histogram and Shapley additive explanations (SHAP) analysis were used to assess model discrimination and interpretability. The mean participant age was 70 ± SD 11 years, with 32% (n = 386) female representation. Median plasma GDF15 levels were significantly higher in PAD patients compared to the levels in non-PAD patients (1.29 [IQR 0.77–2.22] vs. 0.99 [IQR 0.61–1.63] pg/mL; p < 0.001). During the 2-year follow-up period, 219 individuals (18.4%) experienced MACE. The XGBoost model demonstrated strong predictive performance for 2-year MACE (F1 score = 0.83; precision = 82.0%; recall = 83.7%; LR+ = 1.88; LR− = 0.83). The prediction histogram revealed distinct stratification between those who did vs. did not experience 2-year MACE. SHAP analysis identified GDF15 as the most influential predictive feature, surpassing traditional clinical predictors such as age, cardiovascular history, and smoking status. This study highlights GDF15 as a strong prognostic biomarker for 2-year MACE in patients with PAD. When combined with clinical variables in an interpretable machine learning model, GDF15 supports the early identification of patients at high risk for systemic cardiovascular events, facilitating personalized treatment strategies including multidisciplinary specialist referrals and aggressive cardiovascular risk reduction therapy. This biomarker-guided approach offers a promising pathway for improving cardiovascular outcomes in the PAD population through precision risk stratification. Full article

Recently, there has been a rise in skin cancer cases, for which early detection is highly relevant, as it increases the likelihood of a cure. In this context, this work presents a benchmarking study of standard Convolutional Neural Network (CNN) architectures for automated skin lesion classification. A total of 38 CNN architectures from ten families (ConvNeXt, DenseNet, EfficientNet, Inception, InceptionResNet, MobileNet, NASNet, ResNet, VGG, and Xception) were evaluated using transfer learning on the HAM10000 dataset for seven-class skin lesion classification, namely, actinic keratoses, basal cell carcinoma, benign keratosis-like lesions, dermatofibroma, melanoma, melanocytic nevi, and vascular lesions. The comparative analysis used standardized training conditions, with all models utilizing frozen pre-trained weights. Cross-database validation was then conducted using the ISIC 2019 dataset to assess generalizability across different data distributions. The ConvNeXtXLarge architecture achieved the best performance, despite having one of the lowest performance-to-number-of-parameters ratios, with 87.62% overall accuracy and 76.15% F1 score on the test set, demonstrating competitive results within the established performance range of existing HAM10000-based studies. A proof-of-concept multiplatform mobile application was also implemented using a client–server architecture with encrypted image transmission, demonstrating the viability of integrating high-performing models into healthcare screening tools. Full article

Paired data often arise in medical studies, with a correlation between responses of paired organs or parts. Under an intra-correlated model, this paper proposes a generalized linear model to investigate probable confounding factors of the individual response rates in paired data. The main link functions include logistic, log–log, complementary log–log, probit, and double exponential. The estimators of model parameters are calculated through the Newton–Raphson, quadratic lower bound, and Fisher bounded algorithms. Then, three tests (i.e., likelihood ratio test, Wald-type test, and score test) are constructed to analyze whether covariates significantly affect the response rate. Finally, the proposed methods are illustrated by numerical simulation and visual impairment data from Iran. Full article

This paper develops tests for hypotheses concerning subvectors of parameters in models defined by moment conditions. It is well known that conventional tests such as Wald, Likelihood-ratio and Score tests tend to over-reject when the identification is weak. To prevent uncontrolled size distortion and introduce refined finite-sample performance, we extend the projection-based test to a modified version of the score test using implied probabilities obtained by information theoretic criteria. Our test is performed in two steps, where the first step reduces the space of parameter candidates, while the second one involves the modified score test mentioned earlier. We derive the asymptotic properties of this procedure for the entire class of Generalized Empirical Likelihood implied probabilities. Simulations show that the test has very good finite-sample size and power. Finally, we apply our approach to the veteran earnings and find a negative impact of the veteran status. Full article

Background/Objectives: This study aimed to investigate the predictive power of integrated longitudinal amyloid positron emission tomography (PET) and brain magnetic resonance imaging (MRI) data for determining the likelihood of conversion to Alzheimer’s disease (AD) in patients with mild cognitive impairment (MCI). Methods: We included 180 patients with MCI from the Alzheimer’s Disease Neuroimaging Initiative, with baseline and 2-year follow-up scans obtained using F-18 florbetapir PET and MRI. Patients were categorized as converters (progressing to AD) or nonconverters based on a 6-year follow-up. Quantitative analyses included the calculation of amyloid burden using the standardized uptake value ratio (SUVR), brain amyloid smoothing scores (BASSs), brain atrophy indices (BAIs), and their integration into shape features. Longitudinal changes and receiver operating characteristic analyses assessed the predictive power of these biomarkers. Results: Among 180 patients with MCI, 76 (42.2%) were converters, who exhibited significantly higher baseline and 2-year follow-up values for SUVR, BASS, BAI, and shape features than nonconverters (p < 0.001). Shape features demonstrated the highest predictive accuracy for conversion, with areas under the curve of 0.891 at baseline and 0.898 at 2 years. Percent change analyses revealed significant increases in brain atrophy; amyloid deposition changes showed a paradoxical decrease in converters. Additionally, strong associations were observed between longitudinal changes in shape features and neuropsychological test results. Conclusions: The integration of amyloid PET and MRI biomarkers enhances the prediction of AD progression in patients with MCI. These findings support the potential of combined imaging approaches for early diagnosis and targeted interventions in AD. Full article

Background: Although nutritional status plays a critical role in maintaining muscle strength, limited evidence exists regarding its association with dynapenia. Objectives: We aimed to investigate the association between different nutritional statuses and dynapenia among Taiwanese older adults, and assessed whether age modifies this relationship. Methods: In this study, we enrolled individuals aged 65 years and older living in community settings through convenience sampling from 2020 to 2021, following a cross-sectional design. The Mini-Nutritional Assessment Short Form (MNA-SF) was used to assess whether the participants were at nutritional risk. Standardized assessments measured muscle strength (handgrip measurement), physical performance (6 m walking test), and muscle mass (bioelectrical impedance analysis) to confirm dynapenia classifications. The interaction terms were tested using likelihood ratio tests to examine for dynapenia between nutritional status and age. For overall sample and subgroup analyses, binary logistic regression was employed. Results: Among 211 participants (mean age: 80.7 ± 7.1 years), after adjusting for potential confounders, those at nutritional risk (OR: 3.11; 95% CI: 1.31–7.36) were positively associated with dynapenia, whereas higher MNA-SF scores (OR: 0.73; 95% CI: 0.57–0.93) were negatively associated. Interactions regarding dynapenia were observed between nutritional status and age group (p = 0.014), with nutritional risk significantly associated with dynapenia only in the old–old group (≥75 years) (OR = 4.11, 95% CI: 1.39–12.15). Conclusions: Age is a potential moderator of nutritional status and dynapenia among older populations. Nutritional status appeared to be more profound in the old–old group in terms of the risk of dynapenia. These findings offer insights for monitoring nutritional status and implementing targeted interventions to prevent dynapenia in those aged over 75 years. Future studies using prospective designs should explore the underlying mechanisms linking nutritional status to dynapenia and assess the effectiveness of nutritional interventions in preventing muscle strength decline. Full article

Objective: To investigate the clinical characteristics associated with the presence of LSV at birth. Design: Prospective 1:1 case–control study. Setting: Two tertiary neonatal units in Athens, Greece. Patients: Premature neonates (≤36 weeks gestational age) who underwent cerebral ultrasound within the first 3 weeks of life, where LSV was detected. Main outcome measure: Associations between LSV and clinical characteristics at birth. Both unmatched and matched analyses stratifying the study population by gestational week were conducted. Two-sided p-values were computed using the likelihood ratio test. Results: This study included 166 participants (83 cases and 83 controls). Neonates with LSV exhibited more concurrent cerebral findings, notably periventricular echogenicity. LSV was correlated with higher z-scores for head circumference and body length. LSV was not associated with congenital CMV. Conclusions: This study indicated a relationship between LSV and increased head circumference and body length. Further research is warranted to explore LSV’s pathophysiological mechanisms. Full article

Objective: The objective of this study was to assess clinical decision-making associated with the use of a multi-analyte blood biomarker (BBM) test among patients presenting with signs or symptoms of mild cognitive impairment or dementia. Methods: The Quality Improvement PrecivityAD2 (QUIP II) Clinician Survey (NCT06025877) study evaluated the clinical utility of the PrecivityAD2™ blood test in a prospective, single cohort of 203 patients presenting with symptoms of Alzheimer’s disease (AD) or other causes of cognitive decline across 12 memory specialists. The PrecivityAD2 blood test (C2N Diagnostics, St. Louis, MO) combines the plasma Aβ42/Aβ40 ratio and the p-tau217/np-tau217 ratio (%p-tau217) measurements in a statistical algorithm to yield an Amyloid Probability Score 2 (APS2) that informs on the likelihood of brain amyloid plaques. After receiving the BBM test results, clinicians completed surveys on management strategies for each patient. Results: Patients had a median age of 74, 53% were female, and 28% were traditionally under-represented in Black, Hispanic, and Asian groups. The composite primary endpoint, defined as a change in AD diagnostic certainty, drug therapy, or additional brain amyloid evaluation pre- and post-BBM testing, was 75% (p < 0.0001 versus the pre-specified threshold of 20% clinically meaningful change). Anti-AD medication orders decreased among negative APS2 patients and increased among positive APS2 patients (p < 0.0001). Additional brain amyloid testing decreased among negative APS2 patients (p < 0.0001). Conclusions: This blood biomarker test can help memory specialists guide patients to anti-AD therapies as well as rule out AD to allow for other diagnostic considerations. Full article

Background and Objectives: The HALP (Haemoglobin, Albumin, Lymphocyte and Platelet) score is used to predict the prognosis of different types of cancer. This study aimed to investigate the role of the HALP score in predicting pathological response in early-stage gastric cancer patients. Materials and Methods: This retrospective cohort study was conducted on 118 patients diagnosed with early-stage gastric cancer and subjected to perioperative (FLOT) treatment between 2018 and 2023. The role of the HALP score in predicting the pathological response to perioperative treatment in patients was investigated. Results: The mean age of the 118 patients included in the study was 61.3 ± 11.1 (min = 23; max = 86). In the ROC analysis, the optimum cut-off value for the HALP score in pathological response classification was found to be 28.9 (AUC = 0.710, sensitivity = 56.7%, specificity = 80%, PPV = 86.79%, NPV = 46.15%). The pathological response rate was 69% in all patients, 87% in patients with a HALP score ≥ 28.9, and 52% in patients with a HALP score < 28.9 (p < 0.001). The probability of pathological response is 6.5 times higher in patients with a HALP score ≥ 28.9. In the Fagan nomogram, when the HALP score was ≥28.9, our pathological response probability estimate (post-test response probability) was found to increase to 64.8% (Positive Likelihood Ratio = 3, Negative Likelihood Ratio = 0.53). In patients with HALP scores ≥ 28.9 and <28.9, progression rates were 16.7% and 47.8%, respectively (p < 0.001), and median survival times were 45.4 and 30.6 months (p < 0.001). Conclusions: The HALP score is a useful and easily accessible score for determining pathological responses in patients with locally advanced gastric cancer. Full article