Objective To investigate the prognostic factors of esophageal squamous cell carcinoma（ESCC） by multivariate analysis of clinicopathologic features of ESCC between long-term and short-term survivals after esophagectomy. Methods The clinicopathologic features of randomly selected 126 cases with ESCC were analyzed with binary logistic regression, 48 cases of which was divided into long-term survival group（≥5 years） and 78 cases into short-term survival group（≤1 year） according to the follow-up. Results Under univariate analysis, the differences between two groups on tumor pathologic grading, metastasis to lymph node, depth of tumor invasion and length of tumor were significant （Plt;0.01）, however, that on age, gender, location of tumor and status of residues were not （Pgt;0. 05）. Multivariate analysis showed that tumor pathologic grading, metastasis to lymph node, depth of tumor invasion and length of tumor correlated with the prognosis of ESCC （Plt;0. 05）. Their risk coefficient were 2. 943, 2. 641, 2. 126 and 1. 728, respectively. Age, gender, location of tumor and status of residues did not correlated with the prognosis of ESCC （Pgt;0. 05）. Correlation analysis indicated that depth of tumor invasion was positively related to the length of tumor （r=0. 488, Plt;0. 001）, metastasis to lymph node was positively related with depth of tumor invasion and tumor pathologic grading （r=0. 216, P=0. 014; r=0. 238, P=0. 007）. Conclusions The main prognostic factors of ESCC are tumor pathologic grading, metastasis to lymph nodes, depth of tumor invasion and length of tumor,Tumor pathologic grading is high risk factor for prognosis of ESCC,while length of tumor is low risk factor. Age and gender of patients, location of tumor and status of esophageal residues are non-risk factors.
Objective To investigate the prognostic factors related to in-hospital mortality in patients with acute exacerbation of chronic obstructive pulmonary disease ( AECOPD) . Methods A prospective cohort study was carried out in AECOPD patients admitted in three district general hospitals of Jiangyou city, Sichuan province from February 2007 to February 2008. The clinical and epidemiological data at admission and all-cause death in hospital were recorded. The in-hospital mortality rate and potential determinants of mortality of AECOPD were analyzed using Logistic regression method. Results 257 AECOPD inpatients with AECOPD were recruited into the cohort study. The in-hospital mortality rate was 5.84% (15/257) . Univariate analysis showed in-hospital mortality was significantly associated with age, FEV1% pred, arterial oxygen tension ( PaO2 ) , arterial oxygen saturation ( SaO2 ) , pH, and Charlson’s complication index. Multivariate logistic regression model showed that lower arterial oxygen tension ( OR 4.775;95%CI 1.545 ～14.757; P =0.007) and higher Charlson’s complication index ( OR 4. 608; 95% CI 1. 330 ～15. 966; P =0. 016) were significantly associated with in-hospital mortality after adjustment by age. Conclusion For in-patients with AECOPD, PaO2 and Charlson’s complication index are independent risk factors associated with in-hospital mortality.
ObjectiveTo establish logistic regression analysis model to evaluate the diagnostic efficacy of breast imaging report and data system (BI-RADS) ultrasound signs in forecasting malignant risk of breast lesions. MethodUltrasound graphic materials of 1 660 breast lesions diagnosed during January to September 2011 were retrospectively studied and standardized by BI-RADS. Pathology results were regarded as gold standard reference. Ultrasound signs with significant efficacy after single-factor logistic regression were evaluated in multi-factor logistic regression model to predict the malignant risk of breast lesions. ResultsEighteen ultrasound signs of breast lesions on BI-RADS were included in the final regression model. Among them, Cooper ligaments stretch, echogenic halo, skin thickening, axillary lymph node abnormalities, structural distortions and speculation had high OR values of 30 or more and had higher specificity than 90%. The diagnosis values of regressions model were high, with a sensitivity of 84.5%, specificity 95.5% and accuracy 91.4%. The area under ROC curve was 0.964 and prediction accuracy was 91.0%. ConclusionsThe logistic regression model based on BI-RADS ultrasound signs of breast lesions has high diagnostic values in detecting breast cancer.
Early detection of vascular function plays an important role in the prevention and treatment of cardiovascular diseases (CVDs). This paper reports the main studies of the effectiveness of fingertip temperature curve in digital thermal monitoring (DTM) for predicting CVDs, as well as the relationship between parameters from DTM and pulse wave velocity (PWV) detection. A total of 112 subjects [age (42.18±12.28) years, 50% male, 37 with known CVDs] underwent DTM and PWV detection. Results showed that most of parameters related to CVDs were from the declining stage of the digital thermal signal. Binary Logistic regression models were built, and the best one was chosen by ten-fold validation to predict CVDs. Consistency was great between the detection result of PWV and that of the Logistic model of DTM parameters. Parameters from DTM also contained information for early detecting of vascular stiffness. This study indicates that the fingertip temperature curve in DTM has a potential application for predication of CVDs, and it would be used to access vascular function in the initial stage of CVDs.
Objective To analyze the substitution mechanism of surrogate endpoints for traditional Chinese medicine (TCM) clinical efficacy evaluation of chronic heart failure (CHF). Methods To obtain data from the occurrence of surrogate endpoints and cardiogenic death of patients with CHF in 7 hospitals. The causal relationship between surrogate endpoints and cardiogenic mortality was inferred by the Bayesian network model, and the interaction among surrogate endpoints was analyzed by non-conditional logistic regression model. Results A total of 2 961 patients with CHF were included. The results of Bayesian network causal inference showed that cardiogenic mortality had a causal relationship with the surrogate endpoints including NYHA classification (P=0.46), amino-terminal pro-B-type natriuretic peptide (NT-proBNP) (P=0.24), left ventricular ejaculation fraction (LVEF) (P=0.19), and hemoglobin (HB) (P=0.11); non-conditional logistic regression analysis showed that NYHA classification had interaction with NT-proBNP, LVEF, and HB prior to and after adjusting confounders. Conclusions The substitution capability of surrogate endpoints for TCM clinical efficacy evaluation of CHF for cardiogenic mortality are NYHA classification, NT-proBNP, LVEF, and HB in turn, and there is a multiplicative interaction between the main surrogate endpoint NYHA classification and the secondary surrogate endpoints including NT-proBNP, LVEF, and HB, suggesting that when the two surrogate endpoints with interaction exist at the same time, it can enhance the substitution capability of surrogate endpoints for cardiogenic mortality.