title: Bayesian joint ordinal and survival modeling for breast cancer risk assessment.
abstract: We propose a joint model to analyze the structure and intensity of the association between longitudinal measurements of an ordinal marker and time to a relevant event. The longitudinal process is defined in terms of a proportional-odds cumulative logit model. Time-to-event is modeled through a left-truncated proportional-hazards model, which incorporates information of the longitudinal marker as well as baseline covariates. Both longitudinal and survival processes are connected by means of a common vector of random effects. General inferences are discussed under the Bayesian approach and include the posterior distribution of the probabilities associated to each longitudinal category and the assessment of the impact of the baseline covariates and the longitudinal marker on the hazard function. The flexibility provided by the joint model makes possible to dynamically estimate individual event-free probabilities and predict future longitudinal marker values. The model is applied to the assessment of breast cancer risk in women attending a population-based screening program. The longitudinal ordinal marker is mammographic breast density measured with the Breast Imaging Reporting and Data System (BI-RADS) scale in biennial screening exams. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
authors: Department of Statistics and Operational Research, Universitat de València, Doctor Moliner, 50, 46100, Burjassot, Spain. Carmen.Armero@uv.es.
authors: C
authors: C
authors: Armero
authors: Department of Basic Medical Sciences, Universitat de Lleida-IRBLleida, Avda. Rovira Roure, 80, 25198, Lleida, Spain.|Oblikue Consulting, Barcelona, Spain.
authors: C
authors: C
authors: Forné
authors: Department of Basic Medical Sciences, Universitat de Lleida-IRBLleida, Avda. Rovira Roure, 80, 25198, Lleida, Spain.|Health Services Research Network in Chronic Diseases (REDISSEC), Spain.
authors: M
authors: M
authors: Rué
authors: Department of Statistics and Operational Research, Universitat de València, Doctor Moliner, 50, 46100, Burjassot, Spain.
authors: A
authors: A
authors: Forte
authors: Department of Statistics and Operational Research, Universitat de València, Doctor Moliner, 50, 46100, Burjassot, Spain.|Fundación para el Fomento de la Investigación Sanitaria y Biomédica (FISABIO), Generalitat Valenciana, Spain.
authors: H
authors: H
authors: Perpiñán
authors: Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, Barcelona, Spain.
authors: G
authors: 0000-0003-4252-4884
authors: G
authors: Gómez
authors: Clinical Epidemiology and Cancer Screening, Corporació Sanitària Parc Taulí-UAB, Sabadell, Parc Taulí s/n, Sabadell, 08208, Spain.
authors: M
authors: M
authors: Baré
mesh_terms: D001499:Bayes Theorem; D001940:Breast; D000071060:Breast Density; D001943:Breast Neoplasms / Q000453:epidemiology*; D005260:Female; D006801:Humans; D018570:Risk Assessment / Q000379:methods
keywords: BI-RADS scale; Latent process; Proportional-odds cumulative logit model; left-truncated proportional-hazards model