Objective To analyze the factors associated with the adoption of targeted therapy in patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer and to generate evidence to inform decision-making on public security policy regarding innovative anticancer medicines for the benefit of patients. Methods The study population comprised female patients diagnosed with HER2-positive breast cancer and treated at Fujian Cancer Hospital from 2014 to 2020. The patients were eligible for targeted therapy. The demographic and sociological characteristics and clinical information of patients were extracted from the hospital information system. We performed binary logistic regression analysis of factors associated with the adoption of targeted therapy in patients with HER2-positive breast cancer. We also divided the participants into two groups according to their tumor stage for subgroup analysis. Results A total of 1 041 female patients with HER2-positive breast cancer were included, among them, 803 received targeted therapy. In September 2017, molecular-targeted medicines for HER2-positive breast cancer began to be included in the local basic health insurance program. Only 282 (35.1%) patients adopted targeted therapy before September 2017, after which this number increased to 521 (64.9%). Among the patients who adopted targeted therapy, most were formally employed (45.8%) and enrollees of the urban employee health insurance program (66.0%). Among those who did not adopt targeted therapy, most were unemployed (42.4%) and enrollees of the resident health insurance program (50.0%). Binary logistic regression analysis revealed that patient occupation, gene expression of estrogen receptor, tumor stage, surgery or not, radiotherapy or not, and undergoing treatment before or after September 2017 were correlated with the adoption of targeted therapy (P<0.05). Conclusions Inclusion of targeted medicines for HER2-positive breast cancer in the health insurance program substantially increased the overall administration of these therapies. Individual affordability is a critical factor associated with the application of targeted therapy in eligible patients. Future policies should enhance the public security of patients with a relatively weak ability to pay and provide insurance coverage for innovative anti-cancer medicines.
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.
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.
ObjectiveTo explore the selection problem of independent variables and stepwise regression method for multiple logistic regression analysis. MethodsAccording to the data of the case-control investigation for coronary heart disease, age (X1), hypertension history (X2), hypertension family history (X3), smoking (X4), hyperlipidemia history (X5), animal fat intake (X6), weight index (X7), type A personality (X8), and coronary heart disease (CHD, Y) were analyzed by SPSS 18.0 software. The multiple logistic regression analysis was done and the differences of risk factors were compared among 6 kinds stepwise regression variable selection method. ResultsThe univariate analysis showed that no difference was found between CHD group and non-CHD group in age distribution (P=0.116). But the multivariate logistic regression analysis showed that, comparing to population over 65 years old, age was a protective factor on the low age groups (OR< 45=0.100, 0.000 to 0.484, P=0.020; OR45-54=0.051, 0.003 to 0.975, P=0.048). If the age was defined as categorical variable, the risk factors for coronary heart disease were animal fat intake (X6), type A personality (X8), hypertension history (X5) and age (X1), respectively (P < 0.05). If the age was defined as a continuous variable, the effect of age (X1) was not statistically significant (P=0.053). The common risk factors were intake of animal fat (X6) and type a personality (X8) by six kinds method of stepwise variable selection. In addition, the risk factor also included hyperlipidemia history (X5) (forward-condition, forward-LR, forward-wald), hypertension family history (X3), age (X1) (backward-condition, backward-LR) and hypertension history (X2) (backward-wald). ConclusionStepwise regression method should be used to analyze all the variables, including no statistically significant independent variables in univariate analysis. If the categorical variable is regarded as continuous variables, some information may be lost, and even the risk factors may be missed. When the risk factors are not the same by several stepwise regression variable selection method, it should be combined with clinical and epidemiological significance, as well as biological mechanisms and other professional knowledge.
Objective To explore the positive rate of emphysema in groups under Low-dose CT screening, then take the regression analysis on related risk factors for emphysema. Methods A total of 1 175 volunteers involved in low-dose CT screening and completing the questionnaire were collected and taken the CT quantitative assessment for emphysema, then the positive rate of emphysema was calculated. Questionnaire data were collected and non-conditional Logistic regression was used to analyze the factors in the questionnaire. Results Ninety-seven cases of emphysema had been detected in 1 175 volunteers, and the positive rate was 8.26%. The positive rate for the males and the females was 9.90% (71/717) and 5.68% (26/458), respectively. Three risk factors (smoking, second-hand smoking, history of chronic bronchitis) were screened out by Logistic regression. Conclusions According to the results of the regression analysis, smoking, second-hand smoking and history of chronic bronchitis are main risk factors for emphysema. Some effective measures could be made against emphysema in high risk population. In that way the morbidity and perniciousness of emphysema could be reduced.
ObjectiveTo explore risk factors of gastric paralysis following gastrectomy of gastric cancer and analyze its causes. MethodsThe clinical data of 116 patients with gastric cancer for hospitalization time more than 21 days following gastrectomy were retrospectively analyzed from October 2011 to October 2013 in this hospital, in which 16 patients with gastric paralysis and 116 patients without gastric paralysis. The factors relevant gastric paralysis were analyzed by logistic regression analysis. ResultsThe results of single factor analysis showed that the preoperative body mass index, history of diabetes, operative time, postoperative cardiovascular complications, albumin and hemoglobin levels within 3 d after operation, time to get out of bed after surgery, extubation time of gastric tube, the first drinking time and the first feeding time were associated with the gastric paralysis (P < 0.05), but the gender, age, time of diabetes history, life mode, smoking history, hypertension history, pylorus preserving or not, laparoscopy or not, intraoperative blood loss, intraoperative blood transfusion, uses of postoperative intraperitoneal chemotherapy drugs and postoperative analgesic drugs, and indwelling time of jejunum nutrition tube were not associated with gastric paralysis (P > 0.05). The results of logistic regression analysis showed that the preoperative body mass index, history of diabetes, operative time, time to get out of bed after surgery, and postoperative cardiovascular complications were the independent risk factors of gastric paralysis (P < 0.05). ConclusionsThere are many factors that affect occurrence of gastric paralysis following gastrectomy of gastric cancer. Preoperative or intraoperative positive prevention measures could be taken according to the factors that might affect occurrence of gastric paralysis, which might be reduce gastric paralysis following gastrectomy of gastric cancer.
ObjectiveTo investigate the risk factor for restenosis of esophageal anastomosis stricture after esophageal cancer operation. MethodsWe retrospectively analyzed the clinical data of 83 patients including 61males and 22 females at age of 58.9(41-81) years with esophageal anastomoic stricture after esophageal cancer operation between January 2002 and December 2013. According to whether the patients developed to restenosis or not, the statistical test and logistic regression was conducted to analyze the risk factors for restenosis. ResultsIn the 83 patients with esophageal anastomoic stricture after esophageal cancer surgery, 35 patients (42.2%) experienced restenosis within the following-up of 1 year. The result of logistic regression analysis indicated that restenosis appeared in 3 months (Wald value=23.3, P < 0.001), the interval between two subsequent sessions of more than 4 weeks at each esophagus dilatation(Wald value=4.8, P=0.029) and the stricture diameter of less than 12 mm after dilation (Wald value=5.8, P=0.016) are the independent risk factors for restenosis in esophageal anastomotic stricture. ConclusionFor the patients with esophageal anastomoic stricture after esophageal cancer operation, we believe that it's conducive to reduce esophageal restenosis if the interval between dilations is within 4 weeks and the diameter of stricture after dilation can reach above 12 mm.
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.
ObjectivesTo explore the value of neural networks (NN) in estimating propensity score, and to compare the performance of propensity score methods based on both logistic regression (LR) and NN.MethodsData sets including ten binary or continuous covariates, binary treatment variable and continuous outcome variable were simulated by SAS 9.2 software, and 5 scenarios differing by non-linear and/or non-additive associations between treatment assignment and covariates were set up. The sample sizes 500, 1000, 2000, 5000 and 10000 were considered. Propensity scores were estimated using either LR or NN model using only partial covariates associated with the outcome (methods LR1, NN1), or all covariates associated with either outcome or treatment (methods LR2, NN2). The average treatment effect (ATE) estimates, standard error (SE), bias, and mean square error (MSE) of ATE among the different models were compared.ResultsThe 95% confidence intervals of the average treatment effect were narrower in NN than that in LR models. SE, bias and MSE increased with the increasing complexity of non-linear and/or non-additive associations between the treatment and covariates, and smaller SE, bias, and MSE were observed in LR1 than LR2, and in NN1 than NN2. NN generally produced less bias than LR under most scenarios when variables associated with the outcome were introduced. SE and MSE decreased with the increasing sample size for both LR and NN models.ConclusionsNN for estimating propensity scores may be less biased and produce more precise estimates for ATE than LR in a meaningful manner when the complex association between treatment and covariates exists.