Recently, there has been controversy about the relationship between the number of lymph nodes removed and survival of patients diagnosed with lymph node-negative breast cancer. To assess this relationship, 603 cases of lymph node-negative breast cancer with a median of 126 months of follow-up data were studied. Patients were stratified into two groups (Group A, 10 or fewer tumor-free lymph nodes removed; Group B, more than 10 tumor-free lymph nodes removed). The number of tumor-free lymph nodes in ipsilateral axillary resections as well as 5 other disease parameters were analyzed for prognostic value. Our results revealed that the risk of death from breast cancer was significantly associated with patient age, marital status, histologic grade, tumor size, and adjuvant therapy. The 5- and 10-year survival rates for patients with 10 or fewer tumor-free lymph nodes removed was 88.0% and 66.4%, respectively, compared with 69.2% and 51.1%, respectively, for patients with more than 10 tumor-free lymph nodes removed. For patients with 10 or fewer tumor-free lymph nodes removed, the adjusted hazard ratio (HR) for risk of death from breast cancer was 0.579 (95% confidence interval, 0.492-0.687, P < 0.001), independent of patient age, marital status, histologic grade, tumor size, and adjuvant therapy. Our study suggests that the number of tumor-free lymph nodes removed is an independent predictor in cases of lymph node-negative breast cancer.
Axilla ; Breast Neoplasms ; mortality ; Female ; Humans ; Lymph Node Excision ; Lymphatic Metastasis ; Prognosis ; Risk Factors ; Survival Rate

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825–0.910) in the training cohort and 0.890 (0.844–0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcomes.

Bone mass is important for dental implant success and is regulated by mechanoresponsive osteocytes. We aimed to investigate the relationship between the levels and orientation of tensile strain and morphology and orientation of osteocytes at different dental implant positions in the maxillary bone. Bone biopsies were retrieved from eight patients who underwent maxillary sinus-floor elevation with β-tricalcium phosphate prior to implant placement. Gap versus free-ending locations were compared using 1) a three-dimensional finite-element model of the maxilla to predict the tensile strain magnitude and direction and 2) histology and histomorphometric analyses. The finite-element model predicted larger, differently directed tensile strains in the gap versus free-ending locations. The mean percentage of mineralised residual native-tissue volume, osteocyte number (mean ± standard deviations: 97 ± 40/region-of-interest), and osteocyte shape (~90% elongated, ~10% round) were similar for both locations. However, the osteocyte surface area was 1.5-times larger in the gap than in the free-ending locations, and the elongated osteocytes in these locations were more cranially caudally oriented. In conclusion, significant differences in the osteocyte surface area and orientation seem to exist locally in the maxillary bone, which may be related to the tensile strain magnitude and orientation. This might reflect local differences in the osteocyte mechanosensitivity and bone quality, suggesting differences in dental implant success based on the location in the maxilla.
Biopsy ; Bone-Implant Interface ; Calcium Phosphates ; pharmacology ; Dental Implants ; Finite Element Analysis ; Humans ; Maxilla ; surgery ; Osteocytes ; physiology ; Radiography, Panoramic ; Sinus Floor Augmentation ; Tensile Strength