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Background: Lymph node status is an important factor in determining preoperative treatment strategies for stage T1b-T2 esophageal cancer (EC). Thus, the aim of this study was to investigate the risk factors for lymph node metastasis (LNM) in T1b-T2 EC and to establish and validate a risk-scoring model to guide the selection of optimal treatment options.
Methods: Patients who underwent upfront surgery for pT1b-T2 EC between January 2016 and December 2022 were analyzed. On the basis of the independent risk factors determined by multivariate logistic regression analysis, a risk-scoring model for the prediction of LNM was constructed and then validated. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminant ability of the model.
Results: The incidence of LNM was 33.5% (214/638) in our cohort, 33.4% (169/506) in the primary cohort and 34.1% (45/132) in the validation cohort. Multivariate analysis confirmed that primary site, tumor grade, tumor size, depth, and lymphovascular invasion were independent risk factors for LNM (all P < 0.05), and patients were grouped based on these factors. A 7-point risk-scoring model based on these variables had good predictive accuracy in both the primary cohort (AUC, 0.749; 95% confidence interval 0.709-0.786) and the validation cohort (AUC, 0.738; 95% confidence interval 0.655-0.811).
Conclusion: A novel risk-scoring model for lymph node metastasis was established to guide the optimal treatment of patients with T1b-T2 EC.
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http://dx.doi.org/10.1007/s00464-023-10565-1 | DOI Listing |
Am J Prev Cardiol
September 2025
Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, No. 167, North Lishi Road, Xicheng District, Beijing 100037, China.
Background: The Framingham Risk Score for Cardiovascular Disease (FRSCVD), based on the Framingham Heart Study, serves as a foundation for many prediction models. However, its applicability in predicting the long-term prognosis of patients experiencing myocardial infarction with nonobstructive coronary arteries (MINOCA) remains uncertain.
Methods: A cohort of 1158 MINOCA patients was enrolled and stratified into three groups based on 10-year FRSCVD risk.
Environ Pollut
September 2025
Department of Geriatrics, Tianjin Medical University General Hospital, Anshan Road No. 154, Tianjin, 300052, China; Key Laboratory of Post-Trauma Neuro-Repair and Regeneration in Central Nervous System, Tianjin Key Laboratory of Injuries, Variations and Regeneration of Nervous System, Tianjin Neurol
This study systematically investigated the association between triclosan (TCS) exposure and Alzheimer's disease (AD) risk via integrated bioinformatics approaches. TCS-AD-related genes were identified using bioinformatics tools and public databases, followed by the screening of key genes through multi-model machine learning algorithms (LASSO, SVM-RFE, RF) to mitigate random errors in small sample sizes. DRD2 was confirmed as the most robust core gene by LASSO confidence interval analysis and SHAP evaluation, while APP and SLC6A3 were validated through cross-method intersection.
View Article and Find Full Text PDFIntroduction: Our study aimed to identify risk factors associated with the survival of gastric cancer patients with Type 2 diabetes mellitus (T2DM) and create a risk-scoring system for predicting their survival probabilities.
Methods: We gathered data from 1,912 individuals with both gastric cancer and T2DM from the Hong Kong Hospital Authority Data Collaboration Laboratory (HADCL), spanning from 2000 to 2020. We used conventional Cox proportional hazards regression and tree-based machine learning algorithms to construct models for prognosis risk prediction.
Catheter Cardiovasc Interv
September 2025
Department of Cardiovascular Medicine, Kyushu University Hospital, Fukuoka, Japan.
Background: Cardiac computed tomography (CT) is a well-established process used to diagnose coronary artery disease; however, its specific advantages in predicting the use of atherectomy devices during percutaneous coronary intervention (PCI) for moderate to severe calcified lesions remain to be determined. This study aimed to develop a risk scoring system for predicting the use of atherectomy devices in PCI on the basis of morphological findings obtained by preoperative cardiac CT.
Methods: In this retrospective, multicenter, observational study, we screened patients who underwent cardiac CT 6 months before PCI for the target lesion.
Pain Med
September 2025
Department of Pharmacy, Inner Mongolia Autonomous Region People's Hospital, Hohhot, 010017, Inner Mongolia, China.
Objective: The transition from hospital to home is a high-risk period for medication errors, particularly in patients receiving opioids. We constructed and validated a Medication Deviation Risk Prediction Model (MDRP) in cancer pain patients during hospital-to-home transition.
Methods: The medication deviation assessment table was constructed to determine whether there was a medication deviation in the MDRP modeling group.