Kishokai Medical Corporation

As populations age worldwide, breast cancer mortality among older patients continues to rise despite therapeutic advances. This study investigates differences in treatment patterns and outcomes between older and younger patients with metastatic breast cancer. We analyzed clinical data from the Advanced Breast Cancer Database (ABCD) maintained by the Japanese Breast Cancer Research Group. The dataset included patients registered between June 1, 2020, and October 31, 2023, encompassing clinicopathologic information, treatment details, breast cancer specific survival (BCSS), and overall survival (OS). A total of 1629 patients were included. The frequency of chemotherapy and genomic testing decreased with age, yet patients in their 70s demonstrated treatment durations and survival outcomes comparable to those of younger patients. In contrast, patients aged ≥ 80years exhibited shorter duration of second-line therapy (adjusted HR:0.65, 95% CI: 0.43-1.04) and poorer OS (adjusted HR:0.62, 95% CI: 0.37-1.04) and BCSS (adjusted HR:0.66, 95% CI: 0.38-1.14), despite most deaths being attributable to breast cancer rather than non-cancer-related causes. This multicenter retrospective study demonstrates that patients in their 70s can achieve comparable benefits from systemic therapy to younger individuals, emphasizing the importance of not withholding treatment based solely on chronological age. Conversely, the limited effectiveness of later-line therapies in patients aged ≥ 80 highlights the need for individualized treatment strategies that balance efficacy, quality of life, and comorbidities through comprehensive geriatric assessment and shared decision-making.

Almost 10% of all pregnant women are diagnosed with placental location abnormalities (PLA), including placenta previa and low-lying placenta; however, most of PLA resolve as pregnancy process. Despite of placental migration, postpartum hemorrhage (PPH) is often experienced in those cases. The association between the timing of placental migration and the risk of PPH has remained unclear. The aim of this study is to investigate the relationship between the timing of placental migration and the PPH, and to establish a cutoff value to accurately predict the risk of PPH in cases who underwent the placental migration during course of pregnancy. This was a retrospective cohort study using electronic medical records in Osaka University Hospital (Japan). Patients diagnosed with PLA after 22 gestational weeks using transvaginal ultrasonography were eligible for inclusion. All patients delivered at our hospital between 2009 and 2022. Focusing on the cases in which placental migration (more than 2 cm away from the internal cervical os) were observed, the association between the timing of placental migration and the PPH was investigated only in vaginal delivery using the multivariate analyses with collecting covariates that could affect the PPH. Based on the results, receiver operating characteristic curves were generated to determine the optimal cutoff for the number of weeks of placental migration to predict PPH. One hundred and forty-five patients were diagnosed with PLA after 22 gestational weeks and delivered at our hospital between 2009 and 2022. Seventy-six after-placental migration cases with successful vaginal delivery were analyzed. The median gestational age of placental migration was 32 weeks, and the median amount of hemorrhage during delivery was 777 mL. PPH (500-1000 mL) occurred in 34 cases (44.7%), >1000 mL in 26 (34.2%). In the univariate analysis, a positive correlation was observed between the timing of placental migration and the amount of hemorrhage (r=0.365, P<.01). Furthermore, multivariate analysis showed that the timing of placental migration is the most strongly influential covariate (standardized partial regression coefficient: 0.31, P=.0036) for predicting the amount of hemorrhage. In addition, the timing of placental migration was a significant risk for PPH (more than 500 mL) (adjusted unit OR 1.26 [95% CI: 1.07-1.49]). The receiver operating characteristic curve indicated that the moderate cutoff of the timing of placental migration to predict the risk of PPH (more than 500 mL) was 29 gestational weeks. In comparison between the groups in which placental migration was confirmed before 29 gestational weeks (n=19) and after 30 gestational weeks (n=57), the incidences of PPH (more than 500 mL) were significantly higher in the group in which placental migration was confirmed after 30 gestational weeks (52.6% vs 87.7%, P=.0012). The timing of placental migration is positively correlated with the occurrence of PPH. In particular, cases in which placental migration is confirmed after 30 gestational weeks should be monitored carefully as high risk for PPH, as the risk of PPH is not eliminated.

Background: Osteoarthritis (OA) is a prevalent chronic degenerative disorder, with coxarthrosis (hip OA) and gonarthrosis (knee OA) representing its most significant clinical manifestations. While diagnosis typically relies on imaging, such methods can be resource-intensive and insensitive to early disease trajectories. Objective: This study aims to achieve the differential diagnosis of coxarthrosis and gonarthrosis using solely routine preoperative clinical and laboratory data, benchmarking state-of-the-art machine learning algorithms. Methods: A retrospective analysis was conducted on 893 patients (617 with knee OA, 276 with hip OA) from a clinical hospital in Almaty, Kazakhstan. The study evaluated a diverse portfolio of models, including gradient boosting decision trees (LightGBM, XGBoost, CatBoost), deep learning architectures (RealMLP, TabDPT, TabM), and the pretrained tabular foundation model RealTabPFN v2.5. Results: The RealTabPFN v2.5 (Tuned) model achieved superior performance, recording a mean ROC–AUC of 0.9831, accuracy of 0.9485, and an F1-score of 0.9474. SHAP interpretability analysis identified heart rate (66.2%) and age (18.1%) as the dominant predictors driving the model’s decision-making process. Conclusion: Pretrained tabular foundation models demonstrate exceptional capability in distinguishing OA subtypes using limited clinical datasets, outperforming traditional ensemble methods. This approach offers a practical, high-performance triage tool for primary clinical assessment in resource-constrained settings.

Esophageal squamous cell carcinoma (ESCC) remains a leading cause of cancer-related mortality, with early detection being challenging. Although endoscopic screening can aid in diagnosis, its invasiveness and cost limit widespread compliance. To address this, we developed and validated a non-invasive diagnostic panel based on urinary exosomal microRNAs (miRNAs) for early ESCC detection. Urine samples were prospectively collected from ESCC patients and healthy controls across five institutions, and exosomal miRNA profiles were obtained using small RNA sequencing. A diagnostic panel was constructed using machine learning with recursive feature elimination in a proof-of-concept (POC) cohort comprising 99 ESCC and 93 control samples, and its performance was evaluated by five-fold cross-validation. This panel was subsequently tested in a blinded validation cohort of 50 ESCC and 61 control samples. In the POC cohort, the multi-miRNA panel achieved an area under the curve (AUC) of 0.90. In the validation cohort, the AUC was 0.85 (95% CI: 0.77-0.92), with 84% sensitivity and 66% specificity. The panel showed high sensitivity across disease stages-100% for Stage 0, 91% for Stage I, and 73% for Stages II-IV-and its performance was not significantly affected by sex, body mass index, alcohol use, or smoking. Furthermore, in early-stage cases, the diagnostic score significantly declined after treatment (p = 0.026). These findings suggest that the urinary exosomal miRNA panel may offer a practical screening approach for the early detection of ESCC.

Background: Addressing obesity in childhood may alleviate disease risk in later life. Using real-world data from a school health obesity screening program, we examined the percentage of overweight (POW) by sex, grade, blood test results, and lifestyle factors to inform programmatic improvements.Materials and methods: We analyzed data from lifestyle-related disease prevention examinations conducted in Setagaya Ward for children and adolescents between 2015 and 2019 (n = 571). Schoolchildren were categorized into three groups based on POW at the school health exam and change in POW at follow-up. Descriptive analyses were performed to identify factors associated with these outcomes.Results: Comparing the percentage of students in the decreased POW group, 72.3% (115/159) of junior high school students experienced a decrease, compared with 49.5% (204/412) of elementary school students. There was a tendency for no change in POW or increased POW among schoolchildren with higher aspartate aminotransferase, alanine aminotransferase, and total cholesterol. Sleep time tended to be longer in the lower POW group and shorter in the POW 50 group. Television viewing time on weekdays and holidays was shorter in the lower POW groups.Conclusions: Higher obesity percentages were observed among boys and among children in higher grades. Given the associations with lifestyle factors as well, it may be essential to integrate more targeted health guidance in the screening program.