A threshold linear mixed model for identification of treatment-sensitive subsets in a clinical trial based on longitudinal outcomes and a continuous covariate

2020 ◽  
Vol 29 (10) ◽  
pp. 2919-2931
Author(s):  
Xinyi Ge ◽  
Yingwei Peng ◽  
Dongsheng Tu
Keyword(s):  
Clinical Trial ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Likelihood Function ◽  
Specific Treatment ◽  
Likelihood Method ◽  
Simulation Studies ◽  
Longitudinal Outcomes ◽  
Continuous Covariate

Identification of a subset of patients who may be sensitive to a specific treatment is an important problem in clinical trials. In this paper, we consider the case where the treatment effect is measured by longitudinal outcomes, such as quality of life scores assessed over the duration of a clinical trial, and the subset is determined by a continuous baseline covariate, such as age and expression level of a biomarker. A threshold linear mixed model is introduced, and a smoothing maximum likelihood method is proposed to obtain the estimation of the parameters in the model. Broyden-Fletcher-Goldfarb-Shanno algorithm is employed to maximize the proposed smoothing likelihood function. The proposed procedure is evaluated through simulation studies and application to the analysis of data from a randomized clinical trial on patients with advanced colorectal cancer.

scholarly journals A Fumonisin Prevention Tool for Targeting and Ranking Agroclimatic Conditions Favoring Exposure in French Maize-Growing Areas

Toxins ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 214
Author(s):  
Agathe Roucou ◽  
Christophe Bergez ◽  
Benoît Méléard ◽  
Béatrice Orlando
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Fusarium Verticillioides ◽  
Agricultural Practices ◽  
Climatic Conditions ◽  
Agricultural Cooperatives ◽  
Mixed Model Approach ◽  
Food And Feed ◽  
Model Approach

The levels of fumonisins (FUMO)—mycotoxins produced by Fusarium verticillioides—in maize for food and feed are subject to European Union regulations. Compliance with the regulations requires the targeting of, among others, the agroclimatic factors influencing fungal contamination and FUMO production. Arvalis-Institut du végétal has created a national, multiyear database for maize, based on field survey data collected since 2003. This database contains information about agricultural practices, climatic conditions and FUMO concentrations at harvest for 738 maize fields distributed throughout French maize-growing regions. A linear mixed model approach highlights the presence of borers and the use of a late variety, high temperatures in July and October, and a water deficit during the maize cycle as creating conditions favoring maize contamination with Fusarium verticillioides. It is thus possible to target a combination of risk factors, consisting of this climatic sequence associated with agricultural practices of interest. The effects of the various possible agroclimatic combinations can be compared, grouped and classified as promoting very low to high FUMO concentrations, possibly exceeding the regulatory threshold. These findings should facilitate the creation of a national, informative and easy-to-use prevention tool for producers and agricultural cooperatives to manage the sanitary quality of their harvest.

scholarly journals Joint modeling of multiple repeated measures and survival data using multidimensional latent trait linear mixed model

2018 ◽  
Vol 28 (10-11) ◽  
pp. 3392-3403 ◽  
Author(s):  
Jue Wang ◽  
Sheng Luo
Keyword(s):  
Survival Data ◽  
Repeated Measures ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Proportional Hazards Model ◽  
Latent Trait ◽  
Joint Modeling ◽  
Fine Motor ◽  
Terminal Event ◽  
Longitudinal Outcomes

Impairment caused by Amyotrophic lateral sclerosis (ALS) is multidimensional (e.g. bulbar, fine motor, gross motor) and progressive. Its multidimensional nature precludes a single outcome to measure disease progression. Clinical trials of ALS use multiple longitudinal outcomes to assess the treatment effects on overall improvement. A terminal event such as death or dropout can stop the follow-up process. Moreover, the time to the terminal event may be dependent on the multivariate longitudinal measurements. In this article, we develop a joint model consisting of a multidimensional latent trait linear mixed model (MLTLMM) for the multiple longitudinal outcomes, and a proportional hazards model with piecewise constant baseline hazard for the event time data. Shared random effects are used to link together two models. The model inference is conducted using a Bayesian framework via Markov chain Monte Carlo simulation implemented in Stan language. Our proposed model is evaluated by simulation studies and is applied to the Ceftriaxone study, a motivating clinical trial assessing the effect of ceftriaxone on ALS patients.

scholarly journals THE IMPACT OF HOSPITAL BASED INTEGRATED MANAGEMENT OF CHILDHOOD ILLNESS TRAINING ON PEDIATRIC NURSE COMPETENCY

2018 ◽  
Vol 4 (1) ◽  
pp. 16-23
Author(s):  
Fitri Haryanti ◽  
Mohammad Hakimi ◽  
Yati Sunarto ◽  
Yayi S Prabandari
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Integrated Management ◽  
Well Being ◽  
Childhood Illness ◽  
Internal Conflict ◽  
Child Health Services ◽  
Management Support ◽  
The Impact

Background: Although the WHO strategy integrated management of childhood illness (IMCI) for primary care has been implemented in over 100 countries, there is less global experience with hospital-based IMCI training. Until recently, no training had been done in Indonesia, and globally there has been limited experience of the role of IMCI in rebuilding health systems after complex emergencies.Objective: We aimed to examine the effect of hospital-based IMCI training on pedicatric nurse competency and explore the perception of Indonesian doctors, nurse managers and paediatricians about IMCI training and its development in West Aceh, a region that was severely affected by the South-Asian tsunami in December 2004.Methods: This study used stepped wedge design. Training was conducted for 39 nurses staff, 13 midwifes, 6 Head nurses, 5 manager of nurses, 5 doctors, 1 paediatricians, and 3 support facilities  (nutritionist, pharmacist, laboratory) in Cut Nyak Dien (CND) Hospital in Meulaboh, West Aceh, Indonesia. The IMCI training was developed based on the WHO Pocketbook of Hospital Care for Children. A nurses competency questionnaire was used based on the guideline of assessment of the quality of child health services at the first level reference hospitals in districts / municipalities issued by the Ministry of Health in 2007. A linear mixed model was used for data analysis.Results: The hospital based IMCI training improved the competences of nurses paediatric in assessing emergency signs of the sick children, management of cough and difficulty breathing, diarrhoea, fever, nutritional problems, supportive care, monitoring, discharge planning and follow up.  The assessment highlighted several problems in adaptation process of material training, training process and implementation in an environment soon after a major disaster.Conclusion: Hospital based IMCI training can be implemented in a setting after major disasters or internal conflict as part of a rebuilding process.  The program requires strong management support and the emergency phase to be subsided.  Other pre-requisites include the existence of standard operating procedures, adequate physical facilities and support for staff morale and well-being.  Improving the quality of paediatric care requires more than just training and clinical guidelines; internal motivation and health worker support are essential.

scholarly journals Parkinson Symptoms and Health Related Quality of Life as Predictors of Costs: A Longitudinal Observational Study with Linear Mixed Model Analysis

PLoS ONE ◽  
2015 ◽  
Vol 10 (12) ◽  
pp. e0145310 ◽  
Author(s):  
Pablo Martinez-Martín ◽  
Carmen Rodriguez-Blazquez ◽  
Silvia Paz ◽  
Maria João Forjaz ◽  
Belén Frades-Payo ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Observational Study ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Health Related Quality ◽  
Mixed Model Analysis ◽  
Longitudinal Observational Study ◽  
Related Quality ◽  
Health Related

scholarly journals DenVar: Density-based Variation analysis of multiplex imaging data

2021 ◽  
Author(s):  
Souvik Seal ◽  
Thao Vu ◽  
Tusharkanti Ghosh ◽  
Julia Wrobel ◽  
Debashis Ghosh
Keyword(s):  
Cell Biology ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Ion Beam ◽  
Joint Analysis ◽  
Functional Markers ◽  
Simulation Studies ◽  
Threshold Selection ◽  
Imaging Data ◽  
Probability Densities

AbstractMultiplex immunohistochemistry (mIHC) and multiplexed ion beam imaging (MIBI) platforms have become increasingly popular for studying complex single-cell biology in cancer patients. In such studies, researchers test for association between functional markers and survival in a two-step process. First, they count the number of positive cells, defined as the number of cells where a functional marker is significantly expressed. Then, they partition the patients into two groups and test for association between the group label with survival. Consequently, the approach suffers from subjectivity and lack of robustness. In this paper, we propose a threshold-free distance metric between patients solely based on their marker probability densities. Using the proposed distance, we have developed two association tests, one based on hierarchical clustering and the other based on linear mixed model. Our method obviates the need for the arduous step of threshold selection, getting rid of the subjectivity bias. The method also intuitively generalizes to joint analysis of multiple markers. We assessed the performance of our method through extensive simulation studies and also used it to analyze two multiplex imaging datasets.

scholarly journals A generalized linear mixed model for understanding determinant factors of student's interest in pursuing bachelor's degree at Universitas Syiah Kuala

2021 ◽  
Vol 21 (2) ◽  
pp. 72-80
Author(s):  
ASEP RUSYANA ◽  
KHAIRIL ANWAR NOTODIPUTRO ◽  
BAGUS SARTONO
Keyword(s):  
High Schools ◽  
Normal Distribution ◽  
Random Effects ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Model ◽  
Likelihood Method ◽  
Response Variable ◽  
Banda Aceh

Generalized Linear Mixed Model (GLMM) is a framework that has a response variable, fixed effects, and random effects. The response variable comes from an exponential family, whereas random effects have a normal distribution. Estimating parameters can be calculated using the maximum likelihood method using the Laplace approach or the Gauss-Hermite Quadrature (GHQ) approach. The purpose of this study was to identify factors that trigger student's interest to continue studying at Universitas Syiah Kuala (USK) using both techniques.  The GLMM is suitable for the data because the variable response has a Bernoulli distribution, and the random effects are assumed to be having a normal distribution. Also, the model helps identify the relationship between the dependent variable and the predictors. This study utilizes data from six high schools in Banda Aceh city drawn using a two-stage sampling technique. Stage 1, we randomly chose six out of sixteen public senior high schools in Banda Aceh. Stage 2, we selected students from each school from four different major classes. The GLMM model includes one binary response variable, five numerical fixed-effects, and two random effects. The response variable is the interest of high school students to continue study at USK (yes or no). The five fixed effects in the model including scores of collaboration (C), Action (A), Emotion (E), Purposes (P), and Hope (H).  Finally, the random effects are schools (S) and majors (M). In this study, both Laplace and GHQ techniques produce identical results. The predictors that can explain student interest are A, E, and H. These predictors have a positive effect. The random effects of schools and majors are not significantly different from zero. The model with three significant predictors is better than the complete predictor model.

scholarly journals Superior immunogenicity and effectiveness of the 3rd BNT162b2 vaccine dose

2021 ◽  
Author(s):  
Yaniv Lustig ◽  
Tal Gonen ◽  
Lilac Meltzer ◽  
Mayan Gilboa ◽  
Victoria Indenbaum ◽  
...  
Keyword(s):  
Health Care Workers ◽  
Neutralizing Antibodies ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Vaccine Dose ◽  
High Avidity ◽  
Igg Antibodies ◽  
The Third ◽  
Care Workers

In a prospective cohort study involving 12,413 Health Care Workers (HCW), we assessed immunogenicity, vaccine-effectiveness (VE) and safety of the third BNT162b2 vaccine dose. One month after third dose, anti-RBD-IgG were induced 1.7-folds compared to one month after the second. A significant increase in avidity from 61.1% (95%CI:56.1-66.7) to 96.3% (95%CI:94.2-98.5) resulted in a 6.1-folds neutralizing antibodies induction. Linear mixed model demonstrated that the third dose elicited a greater response among HCW≥60 or those with ≥two comorbidities who had a lower response following the second dose. VE of the third dose relative to two doses was 85.6% (95% CI, 79.2-90.1%). No serious adverse effects were reported. These results suggest that the third dose is superior to the second dose in both quantity and quality of IgG-antibodies and safely boosts protection from SARS-CoV-2 infection by generating high avidity antibodies to levels that are not significantly different between healthy and vulnerable populations.

scholarly journals Influence of Sleep Characteristic Changes on Nurses’ Quality of Life during Their Transition to Practice: A Prospective Cohort Study

2022 ◽  
Vol 19 (1) ◽  
pp. 573
Author(s):  
Kyoungja Kim ◽  
Youngjin Lee
Keyword(s):  
Quality Of Life ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Model ◽  
Transition To Practice ◽  
Quality Of Sleep ◽  
Graduate Nurses ◽  
New Graduate Nurses ◽  
New Graduate

Aim: To explore the effect of changes in sleep characteristics on changes in quality of life during the transition period of new graduate nurses. Background: Sleep problems among nurses are associated with negative physical and psychological consequences. Methods: This prospective cohort study was conducted at a tertiary hospital in South Korea. Participants included 88 newly graduated nurses. Data were collected twice, prior to shift work and after 4 months of working as a nurse, via online structured self-report questionnaires created using Survey Monkey from March 2018 to February 2020. A generalized linear mixed model was used to analyze the influence of changes in sleep characteristics on quality of life. Results: A generalized linear mixed model showed that changes in the subjective quality of sleep, subjective health perception, and daytime dysfunction influenced quality of life changes during the transition. This implies that deterioration already existed. From their undergraduate period to four months after they began working as nurses, a significant decrease was observed in the quality of sleep. Participants’ quality of life significantly decreased. Conclusions: Changes in the quality of life of new graduate nurses may show deterioration with a significant drop in subjective sleep quality. Institutions should improve existing work adaptation programs provided during new graduate nurses’ transition to practice by including information on changes in nurses’ health caused by changes in sleep characteristics and sleep quality.

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