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Background: Since body mass index (BMI) is a convincing risk factor for breast cancer, it is speculated to be associated with lymph node metastasis. However, epidemiological studies are inconclusive. Therefore, this study was conducted to investigate the effect of BMI on the lymph node metastasis risk of breast cancer.Methods: Cohort studies that evaluating BMI and lymph node metastasis in breast cancer were selected through various databases including PubMed, PubMed Central (PMC), Web of science, the China National Knowledge Infrastructure (CNKI), Chinese Scientific Journals (VIP) and Wanfang Data Knowledge Service Platform (WanFang) until November 30, 2019. The two-stage, random effect meta-analysis was performed to assess the dose-response relationship between BMI and lymph node metastasis risk. Between-study heterogeneity was assessed using I2. Subgroup analysis was done to find possible sources of heterogeneity.Results: We included a total of 20 studies enrolling 52,904 participants. The summary relative risk (RR) (1.10, 95%CI: 1.06-1.15) suggested a significant effect of BMI on the lymph node metastasis risk of breast cancer. The dose-response meta-analysis (RR = 1.01, 95%CI: 1.00-1.01) indicated a positive linear association between BMI and lymph node metastasis risk. For every 1 kg/m2 increment of BMI, the risk of lymph node metastasis increased by 0.89%. In subgroup analyses, positive linear dose-response relationships between BMI and lymph node metastasis risk were observed among Asian, European, American, premenopausal, postmenopausal, study period less than 5 years, and more than 5 years groups. For every 1 kg/m2 increment of BMI, the risk of lymph node metastasis increased by 0.99, 0.85, 0.61, 1.44, 1.45, 2.22, and 0.61%, respectively.Conclusion: BMI significantly increases the lymph node metastasis risk of breast cancer as linear dose-response reaction. Further studies are needed to identify this association. [ABSTRACT FROM AUTHOR]

Moderate traumatic brain injury (mTBI) is a heterogeneous entity that is poorly defined in the literature. Patients with mTBI have a high rate of neurological deterioration (ND), which is usually accompanied by poor prognosis and no definitive methods to predict. The purpose of this study is to develop and validate a prediction model that estimates the ND risk in patients with mTBI using data collected on admission. Data for 479 patients with mTBI collected retrospectively in our department were analyzed by logistic regression models. Bivariable logistic regression identified variables with a p < 0.05. Multi-variable logistic regression modeling with backward stepwise elimination was used to determine reduced parameters and establish a prediction model. The discrimination efficacy, calibration efficacy, and clinical utility of the prediction model were evaluated. The prediction model was validated using data for 176 patients collected from another hospital. Eight independent prognostic factors were identified: hypertension, Marshall scale (types III and IV), subdural hemorrhage (SDH), location of contusion (frontal and temporal contusions), Injury Severity Score >13, D-dimer level >11.4 mg/L, Glasgow Coma Scale score ≤10, and platelet count ≤152 × 109/L. A prediction model was established and was shown as a nomogram. Using bootstrapping, internal validation showed that the C-statistic of the prediction model was 0.881 (95% confidence interval [CI]: 0.849–0.909). The results of external validation showed that the nomogram could predict ND with an area under the curve of 0.827 (95% CI: 0.763–0.880). The present model, based on simple parameters collected on admission, can predict the risk of ND in patients with mTBI accurately. The high discriminative ability indicates the potential of this model for classifying patients with mTBI according to ND risk. [ABSTRACT FROM AUTHOR]