Bayesian joint ordinal and survival modeling for breast cancer risk assessment
MetadataShow full item record
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 proportionalhazards 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 JohnWiley & Sons Ltd.
Is part ofStatistics in Medicine, 2016, vol. 35, núm. 28, p. 5267-5282
European research projects
Except where otherwise noted, this item's license is described as cc-by-nc-nd (c) Armero, C. et al., 2016
Showing items related by title, author, creator and subject.
Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal PSA data Serrat, Carles; Rué i Monné, Montserrat; Armero, Carmen; Piulachs, Xavier; Perpiñán, Hèctor; Forte, Anabel; Páez, Álvaro; Gómez, Guadalupe (Taylor & Francis, 2014)The paper describes the use of frequentist and Bayesian shared-parameter joint models of longitudinal measurements of prostate specific antigen (PSA) and the risk of prostate cancer (PCa). The motivating dataset corresponds ...
An assessment of existing models for individualized breast cancer risk estimation in a screening program in Spain Arrospide, Arantzazu; Forné Izquierdo, Carles; Rué i Monné, Montserrat; Torà, Núria; Mar, Javier; Baré, Marisa (BioMed Central, 2013)Background: The aim of this study was to evaluate the calibration and discriminatory power of three predictive models of breast cancer risk. Methods: We included 13,760 women who were first-time participants in the ...
Roso-Llorach, Albert; Forné Izquierdo, Carles; Macià, Francesc; Galcerán, Jaume; Marcos-Gragera, Rafael; Rué i Monné, Montserrat (Institut d'Estadística de Catalunya, 2014)Survival estimates for women with screen-detected breast cancer are affected by biases specific to early detection. Lead-time bias occurs due to the advance of diagnosis, and length-sampling bias because tumors detected ...