Background Cardiovascular diseases are closely linked to atherosclerotic plaque development and rupture.Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis,pre...Background Cardiovascular diseases are closely linked to atherosclerotic plaque development and rupture.Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis,prevention,and treatment.Generalized linear mixed models(GLMM)is an extension of linear model for categorical responses while considering the correlation among observations.Methods Magnetic resonance image(MRI)data of carotid atheroscleroticplaques were acquired from 20 patients with consent obtained and 3D thin-layer models were constructed to calculate plaque stress and strain for plaque progression prediction.Data for ten morphological and biomechanical risk factors included wall thickness(WT),lipid percent(LP),minimum cap thickness(MinCT),plaque area(PA),plaque burden(PB),lumen area(LA),maximum plaque wall stress(MPWS),maximum plaque wall strain(MPWSn),average plaque wall stress(APWS),and average plaque wall strain(APWSn)were extracted from all slices for analysis.Wall thickness increase(WTI),plaque burden increase(PBI)and plaque area increase(PAI) were chosen as three measures for plaque progression.Generalized linear mixed models(GLMM)with 5-fold cross-validation strategy were used to calculate prediction accuracy for each predictor and identify optimal predictor with the highest prediction accuracy defined as sum of sensitivity and specificity.All 201 MRI slices were randomly divided into 4 training subgroups and 1 verification subgroup.The training subgroups were used for model fitting,and the verification subgroup was used to estimate the model.All combinations(total1023)of 10 risk factors were feed to GLMM and the prediction accuracy of each predictor were selected from the point on the ROC(receiver operating characteristic)curve with the highest sum of specificity and sensitivity.Results LA was the best single predictor for PBI with the highest prediction accuracy(1.360 1),and the area under of the ROC curve(AUC)is0.654 0,followed by APWSn(1.336 3)with AUC=0.6342.The optimal predictor among all possible combinations for PBI was the combination of LA,PA,LP,WT,MPWS and MPWSn with prediction accuracy=1.414 6(AUC=0.715 8).LA was once again the best single predictor for PAI with the highest prediction accuracy(1.184 6)with AUC=0.606 4,followed by MPWSn(1. 183 2)with AUC=0.6084.The combination of PA,PB,WT,MPWS,MPWSn and APWSn gave the best prediction accuracy(1.302 5)for PAI,and the AUC value is 0.6657.PA was the best single predictor for WTI with highest prediction accuracy(1.288 7)with AUC=0.641 5,followed by WT(1.254 0),with AUC=0.6097.The combination of PA,PB,WT,LP,MinCT,MPWS and MPWS was the best predictor for WTI with prediction accuracy as 1.314 0,with AUC=0.6552.This indicated that PBI was a more predictable measure than WTI and PAI. The combinational predictors improved prediction accuracy by 9.95%,4.01%and 1.96%over the best single predictors for PAI,PBI and WTI(AUC values improved by9.78%,9.45%,and 2.14%),respectively.Conclusions The use of GLMM with 5-fold cross-validation strategy combining both morphological and biomechanical risk factors could potentially improve the accuracy of carotid plaque progression prediction.This study suggests that a linear combination of multiple predictors can provide potential improvement to existing plaque assessment schemes.展开更多
A new kind of combining forecasting model based on the generalized weighted functional proportional mean is proposed and the parameter estimation method of its weighting coefficients by means of the algorithm of quadr...A new kind of combining forecasting model based on the generalized weighted functional proportional mean is proposed and the parameter estimation method of its weighting coefficients by means of the algorithm of quadratic programming is given. This model has extensive representation. It is a new kind of aggregative method of group forecasting. By taking the suitable combining form of the forecasting models and seeking the optimal parameter, the optimal combining form can be obtained and the forecasting accuracy can be improved. The effectiveness of this model is demonstrated by an example.展开更多
Urban air pollution has brought great troubles to physical and mental health,economic development,environmental protection,and other aspects.Predicting the changes and trends of air pollution can provide a scientific ...Urban air pollution has brought great troubles to physical and mental health,economic development,environmental protection,and other aspects.Predicting the changes and trends of air pollution can provide a scientific basis for governance and prevention efforts.In this paper,we propose an interval prediction method that considers the spatio-temporal characteristic information of PM_(2.5)signals from multiple stations.K-nearest neighbor(KNN)algorithm interpolates the lost signals in the process of collection,transmission,and storage to ensure the continuity of data.Graph generative network(GGN)is used to process time-series meteorological data with complex structures.The graph U-Nets framework is introduced into the GGN model to enhance its controllability to the graph generation process,which is beneficial to improve the efficiency and robustness of the model.In addition,sparse Bayesian regression is incorporated to improve the dimensional disaster defect of traditional kernel density estimation(KDE)interval prediction.With the support of sparse strategy,sparse Bayesian regression kernel density estimation(SBR-KDE)is very efficient in processing high-dimensional large-scale data.The PM_(2.5)data of spring,summer,autumn,and winter from 34 air quality monitoring sites in Beijing verified the accuracy,generalization,and superiority of the proposed model in interval prediction.展开更多
The estimation of generalized exponential distribution based on progressive censoring with binomial removals is presented, where the number of units removed at each failure time follows a binomial distribution. Maximu...The estimation of generalized exponential distribution based on progressive censoring with binomial removals is presented, where the number of units removed at each failure time follows a binomial distribution. Maximum likelihood estimators of the parameters and their confidence intervals are derived. The expected time required to complete the life test under this censoring scheme is investigated. Finally, the numerical examples are given to illustrate some theoretical results by means of Monte-Carlo simulation.展开更多
In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are un...In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are unknown beforehand, and therefore, the reflection paths can not be suppressed easily. Therefore, in this article, an improved reflection paths suppression approach is presented. A block matrix aggregate is constructed based on the possible angles of the reflection paths. Combined with the beamforming-like processing, a generalized maximum likelihood estimation is derived to optimize the estimation. Moreover, the noise reduction method based on the Toeplitz covariance matrix is used for better performance. This approach is applied to the real data collected by the low-angle tracking radar with 8-channel vertical array. The experiment results show that the reflection effects are reduced and the accuracy of the elevation estimate is improved.展开更多
This paper considers the parameters and reliability characteristics estimation problem of the generalized Rayleigh distribution under progressively Type-Ⅱ censoring with random removals,that is,the number of units re...This paper considers the parameters and reliability characteristics estimation problem of the generalized Rayleigh distribution under progressively Type-Ⅱ censoring with random removals,that is,the number of units removed at each failure time follows the binomial distribution.The maximum likelihood estimation and the Bayesian estimation are derived.In the meanwhile,through a great quantity of Monte Carlo simulation experiments we have studied different hyperparameters as well as symmetric and asymmetric loss functions in the Bayesian estimation procedure.A real industrial case is presented to justify and illustrate the proposed methods.We also investigate the expected experimentation time and discuss the influence of the parameters on the termination point to complete the censoring test.展开更多
Taking the attitude control system of micro quad-rotor as a research object, a design scheme of fault estimator based on generalized Kalman-Yakubovic-Popov （GKYP） lemma is put forward to deal with the problem of est...Taking the attitude control system of micro quad-rotor as a research object, a design scheme of fault estimator based on generalized Kalman-Yakubovic-Popov （GKYP） lemma is put forward to deal with the problem of estimating multiple actuators malfunctions with couplings. Using an H_index and an appropriate algorithm, the goal of weakening the coupling can be achieved by limiting the fault frequency to a certain range, then different kinds of actuator faults can be estimated correctly. The simulations demonstrate the reliability and validity of the proposed method.展开更多
Hypothesis testing analysis and unknown parameter estimation of both the intermediate frequency(IF) and baseband GPS signal detection are given by using the generalized likelihood ratio test(GLRT) approach,applying th...Hypothesis testing analysis and unknown parameter estimation of both the intermediate frequency(IF) and baseband GPS signal detection are given by using the generalized likelihood ratio test(GLRT) approach,applying the model of GPS signal in white Gaussian noise,It is proved that the test statistic follows central or noncentral F distribution,It is also pointed out that the test statistic is nearly identical to central or noncentral chi-squared distribution because the processing samples are large enough to be considered as infinite in GPS acquisition problem.It is also proved that the probability of false alarm,the probability of detection and the threshold are affected largely when the hypothesis testing refers to the full pseudorandom noise(PRN) code phase and Doppler frequency search space cells instead of each individual cell.The performance of the test statistic is also given with combining the noncoherent integration.展开更多
The inference for the dependent competing risks model is studied and the dependent structure of failure causes is modeled by a Marshall-Olkin bivariate Rayleigh distribution. Under generalized progressive hybrid censo...The inference for the dependent competing risks model is studied and the dependent structure of failure causes is modeled by a Marshall-Olkin bivariate Rayleigh distribution. Under generalized progressive hybrid censoring(GPHC), maximum likelihood estimates are established and the confidence intervals are constructed based on the asymptotic theory. Bayesian estimates and the highest posterior density credible intervals are obtained by using Gibbs sampling. Simulation and a real life electrical appliances data set are used for practical illustration.展开更多
This paper deals with the problem of H∞ fault estimation for linear time-delay systems in finite frequency domain.First a generalized coordinate change is applied to the original system such that in the new coordinat...This paper deals with the problem of H∞ fault estimation for linear time-delay systems in finite frequency domain.First a generalized coordinate change is applied to the original system such that in the new coordinates all the time-delay terms are injected by the system＇s input and output.Then an observer-based H∞ fault estimator with input and output injections is proposed for fault estimation with known frequency range.With the aid of Generalized Kalman-Yakubovich-Popov lemma,sufficient conditions on the existence of the H∞ fault estimator are derived and a solution to the observer gain matrices is obtained by solving a set of linear matrix inequalities.Finally,a numerical example is given to illustrate the effectiveness of the proposed method.展开更多
This paper investigates methods of value-at-risk (VaR) estimation using extreme value theory (EVT). It compares two different estimation methods, 'two-step subsample bootstrap' based on moment estimation and m...This paper investigates methods of value-at-risk (VaR) estimation using extreme value theory (EVT). It compares two different estimation methods, 'two-step subsample bootstrap' based on moment estimation and maximum likelihood estimation (MLE), according to their theoretical bases and computation procedures. Then, the estimation results are analyzed together with those of normal method and empirical method. The empirical research of foreign exchange data shows that the EVT methods have good characters in estimating VaR under extreme conditions and 'two-step subsample bootstrap' method is preferable to MLE.展开更多
目的:探究腹部浅表超声引导下介入治疗对中晚期胰腺癌患者的近期疗效及其对免疫水平的影响。方法:选择2018年5月至2020年3月于岳池县人民医院确诊的中晚期胰腺癌患者152例为研究对象,其中84例采用联合化疗方式治疗,68例采用单纯化疗方...目的:探究腹部浅表超声引导下介入治疗对中晚期胰腺癌患者的近期疗效及其对免疫水平的影响。方法:选择2018年5月至2020年3月于岳池县人民医院确诊的中晚期胰腺癌患者152例为研究对象,其中84例采用联合化疗方式治疗,68例采用单纯化疗方式治疗,通过倾向性评分匹配(PSM)法按1∶1匹配后两组各60例。比较匹配后两组临床资料,并采用广义估计方程评价不同治疗方法对中晚期胰腺癌近期疗效及免疫水平的影响。结果:匹配后两组年龄、BMI、肿瘤部位、性别、肿瘤大小、肿瘤分期差异均无统计学意义(P>0.05)。匹配后两组患者经治疗后局部控制率(LCR)呈下降趋势(P<0.05),联合化疗组局部无进展生存期(LPFS)、总生存期(OS)中位数均高于单纯化疗组(P<0.05)。联合化疗组和单纯化疗组治疗前CA19-9水平差异无统计学意义(P>0.05)。联合化疗组患者治疗后CA19-9水平呈连续下降趋势,6个月随访结果较治疗前显著降低;单纯化疗组治疗后CA19-9水平整体变化呈先降后升,1个月为最低点,CA19-9水平比治疗前明显降低,其余时期随访结果与治疗前差异无统计学意义(P>0.05)。单纯化疗组与联合化疗组治疗后7 d、14 d CA19-9水平差异无统计学意义(P>0.05),联合化疗组1个月、3个月、6个月CA19-9水平明显低于单纯化疗组(P<0.05)。联合化疗组所有免疫指标均呈先升后降趋势,1个月达到最高点,治疗后6个月总T细胞数较治疗前显著降低(P<0.05),CD3^(+)T、NK细胞、IL-2、IFN-γ仍高于治疗前(P<0.05),其余指标与治疗前差异无统计学意义(P>0.05)。单纯化疗组CD4^(+)T/CD8^(+)T变化趋势不显著,其余指标与联合化疗组趋势一致(P<0.05),治疗后6个月总T细胞、CD3^(+)T细胞、NK细胞数、IL-2水平较治疗前更低(P<0.05),其余指标与治疗前差异无统计学意义(P>0.05)。随访期内,联合化疗组总T细胞数、CD3^(+)T细胞数、NK细胞数、IL-2、IFN-γ、IL-6水平较单纯化疗组偏高(P>0.05)。随访14 d和3个月联合化疗组CD4^(+)T/CD8^(+)T显著高于单纯化疗组(P<0.05),其余随访时间差异无统计学意义(P>0.05)。广义估计方程评估结果显示,所有指标差异均有统计学意义。结论:腹部浅表超声引导下介入治疗能够有效提高中晚期胰腺癌近期疗效和免疫水平。展开更多
基金supported in part by National Sciences Foundation of China grant ( 11672001)Jiangsu Province Science and Technology Agency grant ( BE2016785)supported in part by Postgraduate Research & Practice Innovation Program of Jiangsu Province grant ( KYCX18_0156)
文摘Background Cardiovascular diseases are closely linked to atherosclerotic plaque development and rupture.Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis,prevention,and treatment.Generalized linear mixed models(GLMM)is an extension of linear model for categorical responses while considering the correlation among observations.Methods Magnetic resonance image(MRI)data of carotid atheroscleroticplaques were acquired from 20 patients with consent obtained and 3D thin-layer models were constructed to calculate plaque stress and strain for plaque progression prediction.Data for ten morphological and biomechanical risk factors included wall thickness(WT),lipid percent(LP),minimum cap thickness(MinCT),plaque area(PA),plaque burden(PB),lumen area(LA),maximum plaque wall stress(MPWS),maximum plaque wall strain(MPWSn),average plaque wall stress(APWS),and average plaque wall strain(APWSn)were extracted from all slices for analysis.Wall thickness increase(WTI),plaque burden increase(PBI)and plaque area increase(PAI) were chosen as three measures for plaque progression.Generalized linear mixed models(GLMM)with 5-fold cross-validation strategy were used to calculate prediction accuracy for each predictor and identify optimal predictor with the highest prediction accuracy defined as sum of sensitivity and specificity.All 201 MRI slices were randomly divided into 4 training subgroups and 1 verification subgroup.The training subgroups were used for model fitting,and the verification subgroup was used to estimate the model.All combinations(total1023)of 10 risk factors were feed to GLMM and the prediction accuracy of each predictor were selected from the point on the ROC(receiver operating characteristic)curve with the highest sum of specificity and sensitivity.Results LA was the best single predictor for PBI with the highest prediction accuracy(1.360 1),and the area under of the ROC curve(AUC)is0.654 0,followed by APWSn(1.336 3)with AUC=0.6342.The optimal predictor among all possible combinations for PBI was the combination of LA,PA,LP,WT,MPWS and MPWSn with prediction accuracy=1.414 6(AUC=0.715 8).LA was once again the best single predictor for PAI with the highest prediction accuracy(1.184 6)with AUC=0.606 4,followed by MPWSn(1. 183 2)with AUC=0.6084.The combination of PA,PB,WT,MPWS,MPWSn and APWSn gave the best prediction accuracy(1.302 5)for PAI,and the AUC value is 0.6657.PA was the best single predictor for WTI with highest prediction accuracy(1.288 7)with AUC=0.641 5,followed by WT(1.254 0),with AUC=0.6097.The combination of PA,PB,WT,LP,MinCT,MPWS and MPWS was the best predictor for WTI with prediction accuracy as 1.314 0,with AUC=0.6552.This indicated that PBI was a more predictable measure than WTI and PAI. The combinational predictors improved prediction accuracy by 9.95%,4.01%and 1.96%over the best single predictors for PAI,PBI and WTI(AUC values improved by9.78%,9.45%,and 2.14%),respectively.Conclusions The use of GLMM with 5-fold cross-validation strategy combining both morphological and biomechanical risk factors could potentially improve the accuracy of carotid plaque progression prediction.This study suggests that a linear combination of multiple predictors can provide potential improvement to existing plaque assessment schemes.
文摘A new kind of combining forecasting model based on the generalized weighted functional proportional mean is proposed and the parameter estimation method of its weighting coefficients by means of the algorithm of quadratic programming is given. This model has extensive representation. It is a new kind of aggregative method of group forecasting. By taking the suitable combining form of the forecasting models and seeking the optimal parameter, the optimal combining form can be obtained and the forecasting accuracy can be improved. The effectiveness of this model is demonstrated by an example.
基金Project(2020YFC2008605)supported by the National Key Research and Development Project of ChinaProject(52072412)supported by the National Natural Science Foundation of ChinaProject(2021JJ30359)supported by the Natural Science Foundation of Hunan Province,China。
文摘Urban air pollution has brought great troubles to physical and mental health,economic development,environmental protection,and other aspects.Predicting the changes and trends of air pollution can provide a scientific basis for governance and prevention efforts.In this paper,we propose an interval prediction method that considers the spatio-temporal characteristic information of PM_(2.5)signals from multiple stations.K-nearest neighbor(KNN)algorithm interpolates the lost signals in the process of collection,transmission,and storage to ensure the continuity of data.Graph generative network(GGN)is used to process time-series meteorological data with complex structures.The graph U-Nets framework is introduced into the GGN model to enhance its controllability to the graph generation process,which is beneficial to improve the efficiency and robustness of the model.In addition,sparse Bayesian regression is incorporated to improve the dimensional disaster defect of traditional kernel density estimation(KDE)interval prediction.With the support of sparse strategy,sparse Bayesian regression kernel density estimation(SBR-KDE)is very efficient in processing high-dimensional large-scale data.The PM_(2.5)data of spring,summer,autumn,and winter from 34 air quality monitoring sites in Beijing verified the accuracy,generalization,and superiority of the proposed model in interval prediction.
基金supported by the National Natural Science Foundation of China(70471057)
文摘The estimation of generalized exponential distribution based on progressive censoring with binomial removals is presented, where the number of units removed at each failure time follows a binomial distribution. Maximum likelihood estimators of the parameters and their confidence intervals are derived. The expected time required to complete the life test under this censoring scheme is investigated. Finally, the numerical examples are given to illustrate some theoretical results by means of Monte-Carlo simulation.
文摘In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are unknown beforehand, and therefore, the reflection paths can not be suppressed easily. Therefore, in this article, an improved reflection paths suppression approach is presented. A block matrix aggregate is constructed based on the possible angles of the reflection paths. Combined with the beamforming-like processing, a generalized maximum likelihood estimation is derived to optimize the estimation. Moreover, the noise reduction method based on the Toeplitz covariance matrix is used for better performance. This approach is applied to the real data collected by the low-angle tracking radar with 8-channel vertical array. The experiment results show that the reflection effects are reduced and the accuracy of the elevation estimate is improved.
基金supported by the National Statistical Science Research Project of China(2019LZ32)
文摘This paper considers the parameters and reliability characteristics estimation problem of the generalized Rayleigh distribution under progressively Type-Ⅱ censoring with random removals,that is,the number of units removed at each failure time follows the binomial distribution.The maximum likelihood estimation and the Bayesian estimation are derived.In the meanwhile,through a great quantity of Monte Carlo simulation experiments we have studied different hyperparameters as well as symmetric and asymmetric loss functions in the Bayesian estimation procedure.A real industrial case is presented to justify and illustrate the proposed methods.We also investigate the expected experimentation time and discuss the influence of the parameters on the termination point to complete the censoring test.
基金supported by the National Natural Science Foundation of China(61203090)the Natural Science Foundation of Jiangsu Province of China(BK2012384)
文摘Taking the attitude control system of micro quad-rotor as a research object, a design scheme of fault estimator based on generalized Kalman-Yakubovic-Popov （GKYP） lemma is put forward to deal with the problem of estimating multiple actuators malfunctions with couplings. Using an H_index and an appropriate algorithm, the goal of weakening the coupling can be achieved by limiting the fault frequency to a certain range, then different kinds of actuator faults can be estimated correctly. The simulations demonstrate the reliability and validity of the proposed method.
文摘Hypothesis testing analysis and unknown parameter estimation of both the intermediate frequency(IF) and baseband GPS signal detection are given by using the generalized likelihood ratio test(GLRT) approach,applying the model of GPS signal in white Gaussian noise,It is proved that the test statistic follows central or noncentral F distribution,It is also pointed out that the test statistic is nearly identical to central or noncentral chi-squared distribution because the processing samples are large enough to be considered as infinite in GPS acquisition problem.It is also proved that the probability of false alarm,the probability of detection and the threshold are affected largely when the hypothesis testing refers to the full pseudorandom noise(PRN) code phase and Doppler frequency search space cells instead of each individual cell.The performance of the test statistic is also given with combining the noncoherent integration.
基金supported by the China Postdoctoral Science Foundation(2019M650260)the National Natural Science Foundation of China(11501433)。
文摘The inference for the dependent competing risks model is studied and the dependent structure of failure causes is modeled by a Marshall-Olkin bivariate Rayleigh distribution. Under generalized progressive hybrid censoring(GPHC), maximum likelihood estimates are established and the confidence intervals are constructed based on the asymptotic theory. Bayesian estimates and the highest posterior density credible intervals are obtained by using Gibbs sampling. Simulation and a real life electrical appliances data set are used for practical illustration.
基金supported in part by the National Natural Science Foundation of China (60774071)the National High Technology Research and Development Program of China (863 Program) (2008AA121302)+1 种基金the Major State Basic Research Development Program of China (973 Program) (2009CB724000)the State Scholarship Fund of China
文摘This paper deals with the problem of H∞ fault estimation for linear time-delay systems in finite frequency domain.First a generalized coordinate change is applied to the original system such that in the new coordinates all the time-delay terms are injected by the system＇s input and output.Then an observer-based H∞ fault estimator with input and output injections is proposed for fault estimation with known frequency range.With the aid of Generalized Kalman-Yakubovich-Popov lemma,sufficient conditions on the existence of the H∞ fault estimator are derived and a solution to the observer gain matrices is obtained by solving a set of linear matrix inequalities.Finally,a numerical example is given to illustrate the effectiveness of the proposed method.
基金the National Natural Science Foundation of China (No. 79970041).
文摘This paper investigates methods of value-at-risk (VaR) estimation using extreme value theory (EVT). It compares two different estimation methods, 'two-step subsample bootstrap' based on moment estimation and maximum likelihood estimation (MLE), according to their theoretical bases and computation procedures. Then, the estimation results are analyzed together with those of normal method and empirical method. The empirical research of foreign exchange data shows that the EVT methods have good characters in estimating VaR under extreme conditions and 'two-step subsample bootstrap' method is preferable to MLE.
文摘目的:探究腹部浅表超声引导下介入治疗对中晚期胰腺癌患者的近期疗效及其对免疫水平的影响。方法:选择2018年5月至2020年3月于岳池县人民医院确诊的中晚期胰腺癌患者152例为研究对象,其中84例采用联合化疗方式治疗,68例采用单纯化疗方式治疗,通过倾向性评分匹配(PSM)法按1∶1匹配后两组各60例。比较匹配后两组临床资料,并采用广义估计方程评价不同治疗方法对中晚期胰腺癌近期疗效及免疫水平的影响。结果:匹配后两组年龄、BMI、肿瘤部位、性别、肿瘤大小、肿瘤分期差异均无统计学意义(P>0.05)。匹配后两组患者经治疗后局部控制率(LCR)呈下降趋势(P<0.05),联合化疗组局部无进展生存期(LPFS)、总生存期(OS)中位数均高于单纯化疗组(P<0.05)。联合化疗组和单纯化疗组治疗前CA19-9水平差异无统计学意义(P>0.05)。联合化疗组患者治疗后CA19-9水平呈连续下降趋势,6个月随访结果较治疗前显著降低;单纯化疗组治疗后CA19-9水平整体变化呈先降后升,1个月为最低点,CA19-9水平比治疗前明显降低,其余时期随访结果与治疗前差异无统计学意义(P>0.05)。单纯化疗组与联合化疗组治疗后7 d、14 d CA19-9水平差异无统计学意义(P>0.05),联合化疗组1个月、3个月、6个月CA19-9水平明显低于单纯化疗组(P<0.05)。联合化疗组所有免疫指标均呈先升后降趋势,1个月达到最高点,治疗后6个月总T细胞数较治疗前显著降低(P<0.05),CD3^(+)T、NK细胞、IL-2、IFN-γ仍高于治疗前(P<0.05),其余指标与治疗前差异无统计学意义(P>0.05)。单纯化疗组CD4^(+)T/CD8^(+)T变化趋势不显著,其余指标与联合化疗组趋势一致(P<0.05),治疗后6个月总T细胞、CD3^(+)T细胞、NK细胞数、IL-2水平较治疗前更低(P<0.05),其余指标与治疗前差异无统计学意义(P>0.05)。随访期内,联合化疗组总T细胞数、CD3^(+)T细胞数、NK细胞数、IL-2、IFN-γ、IL-6水平较单纯化疗组偏高(P>0.05)。随访14 d和3个月联合化疗组CD4^(+)T/CD8^(+)T显著高于单纯化疗组(P<0.05),其余随访时间差异无统计学意义(P>0.05)。广义估计方程评估结果显示,所有指标差异均有统计学意义。结论:腹部浅表超声引导下介入治疗能够有效提高中晚期胰腺癌近期疗效和免疫水平。
