Hierarchical modelling of patient-reported outcomes data based on the beta-binomial distribution

The beta-binomial distribution does not belong to the exponential family and, hence classical regression techniques cannot be used when dealing with outcomes following the mentioned distribution. In this thesis we propose and develop regression models based on the beta-binomial distribution for the analysis of U, J or inverse J-shaped discrete and bounded outcomes. In fact, although this thesis is focused on the analysis of patient-reported outcomes (PROs), which usually follow the mentioned distributional shapes, proposed models can also be extended to several fields. First of all, we make a review and comparison of existing beta-binomial regression approaches in independent data context, concluding that the marginal approach is the most adequate. However, PRO studies are usually carried out in a longitudinal framework, where patients' responses are measured over time. This leads to a multilevel or correlated data structure and consequently, we extend the marginal beta-binomial regression approach to the inclusion of random effects to accommodate the hierarchical structure of the data. We develop the estimation and inference procedure for the model proposal. Furthermore, we compare the performance of our proposal with similar approaches in the literature, showing that it gets better results in terms of reducing the bias of the estimates. We apply the model to a longitudinal Chronic Obstructive Pulmonary Disease study carried out at Galdakao Hospital, reaching clinically and statistically relevant results about the evolution of the patients over time. PROs are usually obtained using rating scale questionnaires consisting of questions or items, grouped into one or more subscales, often called dimensions or domains. Therefore, we also propose a multivariate regression model based on the beta-binomial distribution for the joint analysis of all the longitudinal dimensions provided by different questionnaires. Finally, it is worth mentioning that we have implemented all the proposed regression models in the PROreg R- package which is freely available at CRAN.Department of Education, Language Policy and Culture of the Basque Government IT-620-13 program, MTM2013-40941-P and MTM2016-74931-

Comparison of beta-binomial regression model approaches to analyze health related quality of life data

Health related quality of life (HRQoL) has become an increasingly important indicator of health status in clinical trials and epidemiological research. Moreover, the study of the relationship of HRQoL with patients' and disease's characteristics has become one of the primary aims of many HRQoL studies. HRQoL scores are usually assumed to be distributed as binomial random variables and often highly skewed. The use of the beta-binomial distribution in the regression context has been proposed to model such data, however, the beta-binomial regression has been performed by means of two di erent approaches in the literature: i) beta-binomial distribution with a logistic link; and ii) hierarchical generalized linear models (HGLMs). None of the existing literature in the analysis of HRQoL survey data has performed a comparison of both approaches in terms of adequacy and regression parameter interpretation context. This paper is motivated by the analysis of a real data application of HRQoL outcomes in patients with Chronic Obstructive Pulmonary Disease (COPD), where the use of both approaches yields to contradictory results in terms of covariate e ects signi cance and consequently the interpretation of the most relevant factors in HRQoL. We present an explanation of the results in both methodologies through a simulation study and address the need to apply the proper approach in the analysis of HRQoL survey data for practitioners, providing an R package.IT-620-13, MTM2013-40941-P, MTM2014-52184-P, MTM2016-74931-P, RD12/0001/0001 - REDISSE

Predictive factors over time of health-related quality of life in chronic obstructive pulmonary disease patients

Background: Health-related quality of life (HRQoL) should be seen as a tool that provides an overall view of the general clinical condition of a COPD patient. The aims of this study were to identify variables associated with HRQoL and whether they continue to have an influence in the medium term, during follow-up. Methods: Overall, 543 patients with COPD were included in this prospective observational longitudinal study. At all four visits during a 5-year follow-up, the patients completed the Saint George’s Respiratory Questionnaire (SGRQ), pulmonary function tests, the 6-min walk test (6MWT), and a physical activity (PA) questionnaire, among others measurements. Data on hospitalization for COPD exacerbations and comorbidities were retrieved from the personal electronic clinical record of each patient at every visit. Results: The best fit to the data of the cohort was obtained with a beta-binomial distribution. The following variables were related over time to SGRQ components: age, inhaled medication, smoking habit, forced expiratory volume in one second, handgrip strength, 6MWT distance, body mass index, residual volume, diffusing capacity of the lung for carbon monoxide, PA (depending on level, 13 to 35% better HRQoL, in activity and impacts components), and hospitalizations (5 to 45% poorer HRQoL, depending on the component). Conclusions: Among COPD patients, HRQoL was associated with the same variables throughout the study period (5-year follow-up), and the variables with the strongest influence were PA and hospitalizations.Fondo de Investigación Sanitaria (PI020510) Departamento de Sanidad del Gobierno Vasco (200111002) Ministerio de Economía y Competitividad del Gobierno de España (MTM2016–74931-P) Departamento de Educación, Política Lingüística y Cultura del Gobierno Vasco (IT1294–19

Anxiety and depressive symptoms are related to core symptoms, general helath outcome and medical comorbidities in eating disorders

Objective: The goal of this study is to identify potential factors that have a significant effect on anxiety and depression of patients with eating disorders (ED) using the beta-binomial regression (BBR) approach on a broad sample of patients. Method: This cross-sectional study involved 520 ED patients. The effect of sociodemographics, core symptoms, general health outcomes and medical comorbidities in anxiety and depression were analyzed jointly using the beta-binomial mixed-effects model. Results: 255(49.4%) patients had Anorexia Nervosa, 173(33.3%) patients had Bulimia Nervosa and 92(17.7%) had Eating Disorder Not Otherwise Specified. A high level of anxiety was associated, among other variables, with having a restrictive ED subtype as compared to purgative and binge ED subtypes (β=-0.2,p<0.001,OR=0.82 and β=-0.16,p<0.03,OR=0.85, respectively), with having a high level of ED symptomatology, or with living not alone (β=-0.23,p=0.002,OR=0.80). A high level of depression was associated, among other variables, with older age (β=0.74,p<0.001,OR=2.1). Conclusions: The results of our study suggest that depressive and anxiety symptoms are related to ED symptoms, health status, ED subtype, medical comorbitidy, and educational level. In addition, another interesting finding is the inverse association between symptomatology of anxiety and living alone. Finally, BBR may be a useful approach in interpreting PRO as odds