Mixture mean residual life model for competing risks data with mismeasured covariates.

This paper proposes a mixture regression model for competing risks data, where the logistic regression model is specified for the marginal probabilities of the failure types and the mean residual lifetime (MRL) model is assumed for the failure time given the failure of interest. The estimating equations (EEs) are derived to infer the logistic regression and MRL model separately. We further consider the situation where the covariates are subject to measurement error.

Far-infrared therapy improves cardiovascular and infectious outcomes in peritoneal dialysis patients.

Introduction: While far-infrared (FIR) therapy has improved the treatment of various diseases, its effects on peritoneal dialysis (PD) remain understudied. The study aims to investigate the impact of FIR therapy on the cardiovascular and infectious outcomes in PD patients.

Methods: A prospective observational study was conducted for six months, comparing a group receiving FIR therapy (n = 49) with a control group (n = 50).

The association of vascular access flow with sacubitril/valsartan and left ventricular ejection fraction in hemodialysis patients with heart failure with reduced ejection fraction.

Background: Sacubitril/valsartan improves heart function in maintenance hemodialysis (HD) patients with heart failure with a reduced ejection fraction of <40% (HFrEF). However, the effect of sacubitril/valsartan on vascular access flow (Qa) in this population is still unclear.

Methods: Hemodialysis patients with HFrEF were enrolled and divided into sacubitril/valsartan and non-sacubitril/valsartan treatment groups and received echocardiographic and Qa measurements at baseline and after 12 months.

The impact of the COVID-19 pandemic on dyslipidemia in peritoneal dialysis patients.

Background: The coronavirus disease 2019 (COVID-19) pandemic has had a profound impacted on various aspects of society, including the healthcare system and patient care. In this context, this study aimed to evaluate the impact of COVID-19 control strategies on the lipid profile and blood sugar levels of peritoneal dialysis (PD) patients in Taiwan, a crucial focus for understanding the pandemic's influence on individuals with chronic kidney disease (CKD).

Methods: A retrospective cohort study was conducted, analyzing data from the medical records of 170 PD patients who visited the nephrology division of Taipei Veterans General Hospital in 2021.

Mean residual life cure models for right-censored data with and without length-biased sampling.

We propose a semiparametric mean residual life mixture cure model for right-censored survival data with a cured fraction. The model employs the proportional mean residual life model to describe the effects of covariates on the mean residual time of uncured subjects and the logistic regression model to describe the effects of covariates on the cure rate. We develop estimating equations to estimate the proposed cure model for the right-censored data with and without length-biased sampling, the latter is often found in prevalent cohort studies.

The mean residual life model for the right-censored data in the presence of covariate measurement errors.

In this article, we consider the mean residual life regression model in the presence of covariate measurement errors. In the whole cohort, the surrogate variable of the error-prone covariate is available for each subject, while the instrumental variable (IV), which is related to the underlying true covariates, is measured only for some subjects, the calibration sample. Without specifying distributions of measurement errors but assuming that the IV is missing at random, we develop two estimation methods, the IV calibration and cohort estimators, for the regression parameters by solving estimation equations (EEs) based on the calibration sample and cohort sample, respectively.

Trajectory of Estimated Glomerular Filtration Rate and Malnourishment Predict Mortality and Kidney Failure in Older Adults With Chronic Kidney Disease.

The trajectory patterns of estimated glomerular filtration rates (eGFR) in chronic kidney disease (CKD) older adults with malnourishment and their association with subsequent patient outcomes have not been elucidated. We aimed to assess the eGFR trajectory patterns for predicting patient survival and kidney failure in the elderly without or with malnourishment. Based on a prospective longitudinal cohort, CKD patients aged 65 years or older were enrolled from 2001 to 2013.

Maximum likelihood estimation for length-biased and interval-censored data with a nonsusceptible fraction.

Left-truncated data are often encountered in epidemiological cohort studies, where individuals are recruited according to a certain cross-sectional sampling criterion. Length-biased data, a special case of left-truncated data, assume that the incidence of the initial event follows a homogeneous Poisson process. In this article, we consider an analysis of length-biased and interval-censored data with a nonsusceptible fraction.

The TVGH-NYCU Thal-Classifier: Development of a Machine-Learning Classifier for Differentiating Thalassemia and Non-Thalassemia Patients.

Thalassemia and iron deficiency are the most common etiologies for microcytic anemia and there are indices discriminating both from common laboratory simple automatic counters. In this study a new classifier for discriminating thalassemia and non-thalassemia microcytic anemia was generated via combination of exciting indices with machine-learning techniques. A total of 350 Taiwanese adult patients whose anemia diagnosis, complete blood cell counts, and hemoglobin gene profiles were retrospectively reviewed.

Influence of Traditional Chinese Medicine on Medical Adherence and Outcome in Estrogen Receptor (+) Breast Cancer Patients in Taiwan: A Real-World Population-Based Cohort Study.

Background: Medical adherence is often higher in clinical trials than in real world practice. The aim of this study was to investigate the effects of traditional Chinese medicine (TCM) on medical adherence to hormonal therapy (HT) and survival outcome in ER (+) breast cancer patients in Taiwan.

Subjects And Methods: Using a nationwide longitudinal population-based database, we enrolled patients with newly diagnosed ER-positive breast cancer who had received HT, and followed for up to 5 years (N = 872).

Semiparametric mixture cure model analysis with competing risks data: Application to vascular access thrombosis data.

The article is motivated by a nephrology study in Taiwan, which enrolled hemodialysis patients who suffered from vascular access thrombosis. After treatment, some patients were cured of thrombosis, while some may experience recurrence of either type (acute or nonacute) of vascular access thrombosis. Our major interest is to estimate the cumulative incidence probability of time to the first recurrence of acute thrombosis after therapy.

Impact of time-varying center volume on technique failure and mortality in peritoneal dialysis.

Background: Most studies on volume-outcome association used the number of patients at a particular period as the independent variable. However, peritoneal dialysis (PD) is a chronic treatment, and center volume usually changes over a patient's treatment period. Accordingly, this study used the time-varying center volume to explore the volume-outcome association in PD.

Semiparametric transformation models for interval-censored data in the presence of a cure fraction.

Mixed case interval-censored data arise when the event of interest is known only to occur within an interval induced by a sequence of random examination times. Such data are commonly encountered in disease research with longitudinal follow-up. Furthermore, the medical treatment has progressed over the last decade with an increasing proportion of patients being cured for many types of diseases.

The association of sociodemographic factors and needs of haemodialysis patients according to Maslow's hierarchy of needs.

Aim: To explore the association between the sociodemographic factors and the needs of patients undergoing haemodialysis in Taiwan.

Background: Concomitant discomfort, including physical and mental aspects, affects the patients' quality of life and their willingness to undergo haemodialysis. Maslow's hierarchy of needs is a well-known tool to assess different levels of human needs.

Methotrexate might reduce ischemic stroke in patients with rheumatoid arthritis: a population-based retrospective cohort study.

Aim: To investigate the effects of hydroxychloroquine, sulfasalazine and methotrexate on ischemic stroke in patients with rheumatoid arthritis (RA).

Methods: This population-based retrospective cohort study included 7904 RA patients and 15 808 non-RA patients between 2000 and 2010. All of the participants were sampled from the National Health Insurance Research Database (NHIRD) of Taiwan.

Impact of Sjogren's syndrome on Parkinson's disease: A nationwide case-control study.

Objective: To investigate whether Sjogren's syndrome would have an influence on the development of Parkinson's disease.

Methods: A population-based case-control study was conducted. Participants consisted of 7716 subjects with newly diagnosed Parkinson's disease and a population of 75129 matched control subjects between 2000 and 2010.

The effect of anti-rheumatic medications for coronary artery diseases risk in patients with rheumatoid arthritis might be changed over time: A nationwide population-based cohort study.

Objectives: To determine whether anti-rheumatic drug usage is associated with risk of coronary artery diseases (CAD) in incident Rheumatoid Arthritis (RA) patients.

Methods: Data were obtained from the Taiwan National Health Insurance Research Database. The study cohort comprised 6260 patients who were newly diagnosed with RA between 2001-2010.

Semiparametric regression analysis of failure time data with dependent interval censoring.

Interval-censored failure-time data arise when subjects are examined or observed periodically such that the failure time of interest is not examined exactly but only known to be bracketed between two adjacent observation times. The commonly used approaches assume that the examination times and the failure time are independent or conditionally independent given covariates. In many practical applications, patients who are already in poor health or have a weak immune system before treatment usually tend to visit physicians more often after treatment than those with better health or immune system.

Conditional maximum likelihood estimation in semiparametric transformation model with LTRC data.

Left-truncated data often arise in epidemiology and individual follow-up studies due to a biased sampling plan since subjects with shorter survival times tend to be excluded from the sample. Moreover, the survival time of recruited subjects are often subject to right censoring. In this article, a general class of semiparametric transformation models that include proportional hazards model and proportional odds model as special cases is studied for the analysis of left-truncated and right-censored data.

A semiparametric mixture cure survival model for left-truncated and right-censored data.

In follow-up studies, the disease event time can be subject to left truncation and right censoring. Furthermore, medical advancements have made it possible for patients to be cured of certain types of diseases. In this article, we consider a semiparametric mixture cure model for the regression analysis of left-truncated and right-censored data.

Heteroscedastic transformation cure regression models.

Cure models have been applied to analyze clinical trials with cures and age-at-onset studies with nonsusceptibility. Lu and Ying (On semiparametric transformation cure model. Biometrika 2004; 91:331?-343.

The partly Aalen's model for recurrent event data with a dependent terminal event.

Recurrent event data are commonly observed in biomedical longitudinal studies. In many instances, there exists a terminal event, which precludes the occurrence of additional repeated events, and usually there is also a nonignorable correlation between the terminal event and recurrent events. In this article, we propose a partly Aalen's additive model with a multiplicative frailty for the rate function of recurrent event process and assume a Cox frailty model for terminal event time.

Two-stage estimation for multivariate recurrent event data with a dependent terminal event.

Recurrent event data arise in longitudinal follow-up studies, where each subject may experience the same type of events repeatedly. The work in this article is motivated by the data from a study of repeated peritonitis for patients on peritoneal dialysis. Due to the aspects of medicine and cost, the peritonitis cases were classified into two types: Gram-positive and non-Gram-positive peritonitis.