Upadacitinib for refractory ulcerative colitis with primary nonresponse to infliximab and vedolizumab:A case report

BACKGROUND Many patients with ulcerative colitis(UC)do not respond well to,or tolerate conventional and biological therapies.There is currently no consensus on the treatment of refractory UC.Studies have demonstrated that the selective Janus kinase 1 inhibitor upadacitinib,a small-molecule drug,is effective and safe for treating UC.However,no studies have revealed that upadacitinib is effective in treating refractory UC with primary nonresponse to infliximab and vedolizumab.CASE SUMMARY We report the case of a 44-year-old male patient with a chief complaint of bloody diarrhoea with mucus and pus,in addition to dizziness.The patient had recurrent disease after receiving mesalazine,prednisone,azathioprine,infliximab and vedolizumab over four years.Based on the endoscopic findings and pathological biopsy,the patient was diagnosed with refractory UC.In particular,the patient showed primary nonresponse to infliximab and vedolizumab.Based on the patient’s history and recurrent disease,we decided to administer upadacitinib.During hospitalisation,the patient was received upadacitinib under our guidance.Eight weeks after the initiation of upadacitinib treatment,the patient’s symptoms and endoscopic findings improved significantly.No notable adverse reactions have been reported to date.CONCLUSION Our case report suggests that upadacitinib may represent a valuable strategy for treating refractory UC with primary nonresponse.

Predictors and optimal management of tumor necrosis factor antagonist nonresponse in inflammatory bowel disease:A literature review

Tumor necrosis factor-α(TNF-α)antagonists,the first biologics approved for treating patients with inflammatory bowel disease(IBD),are effective for the induction and maintenance of remission and significantly improving prognosis.However,up to one-third of treated patients show primary nonresponse(PNR)to anti-TNF-αtherapies,and 23%-50%of IBD patients experience loss of response(LOR)to these biologics during subsequent treatment.There is still no recognized predictor for evaluating the efficacy of anti-TNF drugs.This review summarizes the existing predictors of PNR and LOR to anti-TNF in IBD patients.Most predictors remain controversial,and only previous surgical history,disease manifestations,drug concentrations,antidrug antibodies,serum albumin,some biologic markers,and some genetic markers may be potentially predictive.In addition,we also discuss the next steps of treatment for patients with PNR or LOR to TNF antagonists.Therapeutic drug monitoring plays an important role in treatment selection.Dose escalation,combination therapy,switching to a different anti-TNF drug,or switching to a biologic with a different mechanism of action can be selected based on the concentration of the drug and/or antidrug antibodies.

Longitudinal Survey, Nonmonotone, Nonresponse, Imputation, Nonparametric Regression

The study focuses on the imputation for the longitudinal survey data which often has nonignorable nonrespondents. Local linear regression is used to impute the missing values and then the estimation of the time-dependent finite populations means. The asymptotic properties (unbiasedness and consistency) of the proposed estimator are investigated. Comparisons between different parametric and nonparametric estimators are performed based on the bootstrap standard deviation, mean square error and percentage relative bias. A simulation study is carried out to determine the best performing estimator of the time-dependent finite population means. The simulation results show that local linear regression estimator yields good properties.

Pseudo likelihood and dimension reduction for data with nonignorable nonresponse

Tang et al. (2003. Analysis of multivariate missing data with nonignorable nonresponse.Biometrika, 90(4), 747–764) and Zhao & Shao (2015. Semiparametric pseudo-likelihoods in generalized linear models with nonignorable missing data. Journal of the American Statistical Association, 110(512), 1577–1590) proposed a pseudo likelihood approach to estimate unknownparameters in a parametric density of a response Y conditioned on a vector of covariate X, whereY is subjected to nonignorable nonersponse, X is always observed, and the propensity of whetheror not Y is observed conditioned on Y and X is completely unspecified. To identify parameters, Zhao & Shao (2015. Semiparametric pseudo-likelihoods in generalized linear models withnonignorable missing data. Journal of the American Statistical Association, 110(512), 1577–1590)assumed that X can be decomposed into U and Z, where Z can be excluded from the propensitybut is related with Y even conditioned on U. The pseudo likelihood involves the estimation ofthe joint density of U and Z. When this density is estimated nonparametrically, in this paper weapply sufficient dimension reduction to reduce the dimension of U for efficient estimation. Consistency and asymptotic normality of the proposed estimators are established. Simulation resultsare presented to study the finite sample performance of the proposed estimators.

Multivariate small area estimation under nonignorable nonresponse

We consider multivariate small area estimation under nonignorable, not missing at random(NMAR) nonresponse. We assume a response model that accounts for the different patterns ofthe observed outcomes, (which values are observed and which ones are missing), and estimatethe response probabilities by application of the Missing Information Principle (MIP). By this principle, we first derive the likelihood score equations for the case where the missing outcomes areactually observed, and then integrate out the unobserved outcomes from the score equationswith respect to the distribution holding for the missing data. The latter distribution is definedby the distribution fitted to the observed data for the respondents and the response model. Theintegrated score equations are then solved with respect to the unknown parameters indexingthe response model. Once the response probabilities have been estimated, we impute the missing outcomes from their appropriate distribution, yielding a complete data set with no missingvalues, which is used for predicting the target area means. A parametric bootstrap procedure isdeveloped for assessing the mean squared errors (MSE) of the resulting predictors. We illustratethe approach by a small simulation study.

Efficacy of integrated Traditional Chinese Medicine and anti-retroviral therapy on immunological nonresponse in patients with human immunodeficiency virus/acquired immunodeficiency syndrome: a Meta-analysis of randomized controlled trials

OBJECTIVE:To explore the efficacy of integrating Traditional Chinese Medicine(TCM)and anti-retroviral therapy(ART),a customized combination of different classes of medications which was also called cock-tail treatment,on the immunological nonresponse(INR)in people living with human immunodeficiency virus(HIV)(PLWH).METHODS:Relevant literature in databases such as China National Knowledge Infrastructure Database(CNKI),Wanfang Digital Journal,Chinese Medical Journal Database(CMJD),Chinese Biomedical Literature Database(CBM),Pub Med,Cochrane,and Embase was reviewed by two independent investigators.Data were extracted from the studies according to the eligible criteria and analyzed using Review Manager 5.3.RESULTS:Nine randomized controlled trials(RCTs)with 1078 patients were analyzed.Our analyses showed that CD4 T cell counts in the treatment group improved compared with that in the control group[mean difference(MD)=13.51,95%confidence interval(CI):7.42-19.60,P<0.0001].There was no significant difference between the treated and control groups after 3 months(MD=25.31,95%CI:-2.78 to 53.41,P=0.08).However,after 6 and 12 months,the response of the treatment group was superior to the control group(MD=27.45,95%CI:7.09-47.81,P=0.008 and MD=27.34,95%CI:6.31–48.37,P=0.01,respectively).The clinical efficacy of the treatment group was also higher than that of the control group(RR=1.75,95%CI:1.16-2.65,P=0.007).However,CD45 RO and CD45 RA T cell counts did not differ significantly between the two groups(MD=12.37,95%CI:-6.71 to 31.45,P=0.20 and MD=5.67,95%CI:-3.00 to14.35,P=0.20,respectively).CONCLUSION:The combined treatment strategy of integrated TCM and Western Medicine promotes long-term reconstitution of the immune system and thus,is beneficial and has potential use for improving INR in PLWH.However,large-scale RCTs are required to provide evidence for optimal intervention strategies.

Estimated conditional score function for missing mechanism model with nonignorable nonresponse

Missing data mechanism often depends on the values of the responses,which leads to nonignorable nonresponses.In such a situation,inference based on approaches that ignore the missing data mechanism could not be valid.A crucial step is to model the nature of missingness.We specify a parametric model for missingness mechanism,and then propose a conditional score function approach for estimation.This approach imputes the score function by taking the conditional expectation of the score function for the missing data given the available information.Inference procedure is then followed by replacing unknown terms with the related nonparametric estimators based on the observed data.The proposed score function does not suffer from the non-identifiability problem,and the proposed estimator is shown to be consistent and asymptotically normal.We also construct a confidence region for the parameter of interest using empirical likelihood method.Simulation studies demonstrate that the proposed inference procedure performs well in many settings.We apply the proposed method to a data set from research in a growth hormone and exercise intervention study.

Regression Estimation for Longitudinal Data with Nonignorable Intermittent Nonresponse and Dropout

We mainly focus on regression estimation in a longitudinal study with nonignorable intermittent nonresponse and dropout.To handle the identifiability issue,we take a time-independent covariate as nonresponse instrument which is independent of nonresponse propensity conditioned on other covariates and responses to ensure the identifiability of nonresponse propensity.The nonresponse propensity is assumed to be a parametric model,and the corresponding parameters are estimated by using the generalized method of moments approach.Then the marginal response means are estimated by inverse probability weighting method.Furthermore,to improve the robustness of estimators,we derive an augmented inverse probability weighting estimator which is shown to be consistent and asymptotically normally distributed.Simulation studies and a real-data analysis show that the proposed approach yields highly efficient estimators.

Efficacy of Real-world Entecavir Therapy in Treatment-naive Chronic Hepatitis B Patients

Background：Entecavir （ETV） has been shown to be effective in randomized controlled trials in highly selected patients with hepatitis B virus （HBV） infection.This study aimed to evaluate the efficacy of ETV in chronic hepatitis B （CHB） patients in the real-world setting.Methods：A total of 233 treatment-na（i）ve,CHB patients who received at least 12 months of ETV treatment were included in this retrospective study.Rates of virological response （VR）,hepatitis B s antigen （HBsAg） loss,hepatitis B e antigen （HBeAg） clearance/seroconversion,virological breakthrough,cirrhosis,and hepatocellular carcinoma were evaluated.Results：Of 233 patients,175 patients were male,with mean age of 43 years old,and 135 patients were HBeAg positive.The mean baseline levels of serum alanine aminotransferase and HBV DNA in all patients were 230 U/L and 6.6 log 10 IU/ml,respectively.The mean follow-up period was 28 months.The cumulative rates of achieving VR increased from 3.4% at 3 months to 94.4% at 60 months.Primary nonresponse occurred in 3 （1.3%） patients.Partial VR （PVR） occurred in 61 （26.2%） patients at 12 months.The baseline serum HBV DNA level （hazard ratio [HR],2.054;P 〈 0.001） was an independent risk factor for PVR.HBsAg loss did not occur.The cumulative rates of HBeAg clearance increased from 2.2% at 3 months to 28.2% at 60 months.PVR was the significant determinant of HBeAg clearance （HR,0.341;P =0.026）.Age （HR,1.072;P =0.013） and PVR （HR,5.131;P =0.017） were the significant determinants of cirrhosis.Conclusions：ETV treatment was effective for HBV DNA suppression in this study,but HBsAg loss and HBeAg clearance/seroconversion rates were lower compared with previous clinical trials.PVR was associated with HBeAg clearance and cirrhosis.

Imputation of Mean of Ratios for Missing Data and Its Application to PPSWR Sampling

In practical survey sampling, nonresponse phenomenon is unavoidable. How to impute missing data is an important problem. There are several imputation methods in the literature. In this paper, the imputation method of the mean of ratios for missing data under uniform response is applied to the estimation of a finite population mean when the PPSWR sampling is used. The imputed estimator is valid under the corresponding response mechanism regardless of the model as well as under the ratio model regardless of the response mechanism. The approximately unbiased jackknife variance estimator is also presented. All of these results are extended to the case of non-uniform response. Simulation studies show the good performance of the proposed estimators.

Cross-Entropy Minimization Estimation for Two-Phase Sampling and Non-Response

This paper considers the problem of estimating the finite population total in two-phase sampling when some information on auxiliary variable is available. The authors employ an informationtheoretic approach which makes use of effective distance between the estimated probabilities and the empirical frequencies. It is shown that the proposed cross-entropy minimization estimator is more efficient than the usual estimator and has some desirable large sample properties. With some necessary modifications, the method can be applied to two-phase sampling for stratification and non-response. A simulation study is presented to assess the finite sample performance of the proposed estimator.

Sample rotation theory with missing data

This paper studies how the sample rotation method is applied to the case where item nonresponse occurs in surveys. The two cases where the response to the first occasion is complete or incomplete are considered. Using ratio imputation method, the estimators of the current population mean are proposed, which are valid under uniform response regardless of the model and under the ratio model regardless of the response mechanism. Under uniform response, the variances of the proposed estimators are derived. Interestingly, although their expressions are similar, the estimator for the case of incomplete response on the first occasion can have smaller variance than the one for the case of complete response on the first occasion under uniform response. The linearized jackknife variance estimators are also given. These variance estimators prove to be approximately design-unbiased under uniform response. It should be noted that similar property on variance estimators has not been discussed in literature.