Statistical modelling to analyse health-related quality of life outcomes in randomised clinical trials in oncology

Randomised controlled clinical trials are commonly designed to study the efficacy of a new drug. Health-related quality of life (HRQoL) outcomes have been increasingly recognized as an important endpoint in cancer treatment. Recent reviews show little consensus on the analysis, interpretat...

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Detalhes bibliográficos
Autor: Villacampa Javierre, Guillermo
Formato: tesis de maestría
Fecha de publicación:2022
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/364892
Acesso em linha:https://hdl.handle.net/2117/364892
Access Level:acceso abierto
Palavra-chave:Mathematical statistics
Medical statistics
Longitudinal data analysis
Mixed model
Quality of life
Clinical trials
Survival analysis
Ordinal outcomes
Estadística matemàtica
Estadística mèdica
Classificació AMS::62 Statistics
Classificació AMS::62 Statistics::62P Applications
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
Descrição
Resumo:Randomised controlled clinical trials are commonly designed to study the efficacy of a new drug. Health-related quality of life (HRQoL) outcomes have been increasingly recognized as an important endpoint in cancer treatment. Recent reviews show little consensus on the analysis, interpretation, and reporting of these data from a statistical perspective. In this project, we aim to understand the strengths and limitations of the current statistical approaches to evaluate quality of life data. Linear model, generalised and linear mixed models, the beta-binomial distribution, time-to-event analysis and missing data analysis will be explored. Additionally, the above approaches will be used to analyse the patient-reported HRQoL of the breast cancer phase II of the Coralleen trial (NCT03248427).