Predictive factors over time of health-related quality of life in COPD 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.

A beta-binomial mixed-effects model approach for analysing longitudinal discrete and bounded outcomes.

Patient-reported outcomes (PROs) are currently being increasingly used as primary outcome measures in observational and experimental studies since they inform clinicians and researchers about the health-status of patients and generate data to facilitate improved care. PROs usually appear as discrete and bounded with U, J, or inverse J shapes, and hence, exponential family members offer inadequate distributional fits. The beta-binomial distribution has been proposed in the literature to fit PROs. However, the fact that the beta-binomial distribution does not belong to the exponential family limits its applicability in the regression model context, and classical estimation approaches are not straightforward. Moreover, PROs are usually measured in a longitudinal framework in which individuals are followed up for a certain period. Hence, each individual obtains several scores of the PRO over time, which leads to the repeated measures and defines the correlation structure in the data. In this work, we have developed and proposed an estimation procedure for the analysis of correlated discrete and bounded outcomes, particularly PROs, by a beta-binomial mixed-effects model. Additionally, we have implemented the methodology in the PROreg package in R. Because there are similar approaches in the literature to address the same issue, this work also incorporates a comparison study between our proposal and alternative methodologies commonly implemented in R and shows the superior performance of our estimation procedure. This paper was motivated by the analysis of the health-status of patients with chronic obstructive pulmonary disease, where the main objective is the assessment of risk factors that may affect the evolution of the disease. The application of the proposed approach in the study leads to clinically relevant results.

Anxiety and depressive symptoms are related to core symptoms, general health 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 analysed jointly using the beta-binomial mixed-effects model. RESULTS: Two hundred fifty-five (49.4%) patients had anorexia nervosa, 173 (33.3%) patients had bulimia nervosa, and 92 (17.7%) had ED not otherwise specified. A high level of anxiety was associated, among other variables, with having a restrictive ED subtype as compared with purgative and binge ED subtypes (ß = -0.2, p < 0.001, OR = 0.82 and ß = -0.16, p < 0.03, OR = 0.85, respectively), with having a high level of ED symptomatology or with living not alone (ß = -0.23, p = 0.002, OR = 0.80). A high level of depression was associated, among other variables, with older age (ß = 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 patient-reported outcome as odds.

Pre-operative ribociclib plus letrozole versus chemotherapy: Health-related quality of life outcomes from the SOLTI CORALLEEN trial.

INTRODUCTION: In the phase II CORALLEEN trial, patients with PAM50 luminal B early breast cancer (EBC) were randomised to neoadjuvant ribociclib plus letrozole (R + L) or chemotherapy based on anthracyclines and taxanes. Results from the primary efficacy analysis showed a similar proportion of patients with response at surgery in both groups. How health-related quality of life (HRQoL) outcomes with R + L compare with chemotherapy in EBC setting is still unknown. Here, we report the results of the HRQoL analysis from the CORALLEEN study. METHODS: A total of 106 women were randomised 1:1 to receive neoadjuvant R + L (n = 52) or chemotherapy (n = 54). Patient-reported outcomes were assessed using two questionnaires: EORTC QLQ-C30 and EORTC QLQ-BR23. Change from baseline in the global health status, functional, and symptom scales was analysed using linear mixed-effect models, and between-treatment differences were estimated along with 95% confidence interval (95% CI). RESULTS: At baseline, the overall questionnaire available rate was 94.3%, and patient-reported outcomes were similar between treatment groups. At the end of the study treatment (24 weeks), patients receiving R + L showed better global health status scores with a between-treatment difference of 17.7 points (95% CI 9.2-26.2; p-value <0.001). The R + L group also presented numerically better outcomes in all functional and symptom scales. The larger between-treatment differences in symptom severity were found in fatigue (-28.9; 95% CI -38.5 to -19.3), appetite loss (-23; 95% CI -34.9 to -11.2) and systematic therapy side-effects (-11.4; 95% CI -18.3 to -4.6). CONCLUSIONS: Neoadjuvant R + L was associated with better HRQoL outcomes compared with chemotherapy in patients with luminal B EBC. REGISTRATION IDENTIFICATION: ClinicalTrials.gov Identifier: NCT03248427.

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

Health-related quality of life has become an increasingly important indicator of health status in clinical trials and epidemiological research. Moreover, the study of the relationship of health-related quality of life with patients and disease characteristics has become one of the primary aims of many health-related quality of life studies. Health-related quality of life 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 different approaches in the literature: (i) beta-binomial distribution with a logistic link; and (ii) hierarchical generalized linear models. None of the existing literature in the analysis of health-related quality of life 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 health-related quality of life outcomes in patients with Chronic Obstructive Pulmonary Disease, where the use of both approaches yields to contradictory results in terms of covariate effects significance and consequently the interpretation of the most relevant factors in health-related quality of life. 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 health-related quality of life survey data for practitioners, providing an R package.