Search results for "survival analysi"

Bayesian models for data missing not at random in health examination surveys

2018

In epidemiological surveys, data missing not at random (MNAR) due to survey nonresponse may potentially lead to a bias in the risk factor estimates. We propose an approach based on Bayesian data augmentation and survival modelling to reduce the nonresponse bias. The approach requires additional information based on follow-up data. We present a case study of smoking prevalence using FINRISK data collected between 1972 and 2007 with a follow-up to the end of 2012 and compare it to other commonly applied missing at random (MAR) imputation approaches. A simulation experiment is carried out to study the validity of the approaches. Our approach appears to reduce the nonresponse bias substantially…

Generating survival times to simulate Cox proportional hazards models

2005

Simulation studies present an important statistical tool to investigate the performance, properties and adequacy of statistical models in pre-specified situations. One of the most important statistical models in medical research is the proportional hazards model of Cox. In this paper, techniques to generate survival times for simulation studies regarding Cox proportional hazards models are presented. A general formula describing the relation between the hazard and the corresponding survival time of the Cox model is derived, which is useful in simulation studies. It is shown how the exponential, the Weibull and the Gompertz distribution can be applied to generate appropriate survival times f…

Bayesian analysis of a disability model for lung cancer survival

2016

Bayesian reasoning, survival analysis and multi-state models are used to assess survival times for Stage IV non-small-cell lung cancer patients and the evolution of the disease over time. Bayesian estimation is done using minimum informative priors for the Weibull regression survival model, leading to an automatic inferential procedure. Markov chain Monte Carlo methods have been used for approximating posterior distributions and the Bayesian information criterion has been considered for covariate selection. In particular, the posterior distribution of the transition probabilities, resulting from the multi-state model, constitutes a very interesting tool which could be useful to help oncolog…

Effects of record linkage errors on registry-based follow-up studies

1997

The importance of reliable record linkage for high quality-population-based disease registration is widely recognized. Systematic methodologic work is lacking, however, on the effects of record linkage errors on the use of disease registries for epidemiologic purposes. The present paper provides algebraic models describing the effects of record linkage errors on monitoring survival of registered patients, which is commonly performed by matching registry records against a database of death certificates, and on registry-based incidence follow-up of external cohorts. Homonym errors, that is, erroneous linkage of records that pertain to distinct individuals, lead to underestimation of survival …

Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal prostate-specific antigen data

2015

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 to the screening arm of the Spanish branch of the European Randomized Screening for Prostate Cancer study. The results show that PSA is highly associated with the risk of being diagnosed with PCa and that there is an age-varying effect of PSA on PCa risk. Both the frequentist and Bayesian paradigms produced very close parameter estimates and subsequent 95% confidence and credibility intervals. Dynamic estimations of disease-free probabilities obtained using Bayesian infe…

Estimating regression models with unknown break-points.

2003

This paper deals with fitting piecewise terms in regression models where one or more break-points are true parameters of the model. For estimation, a simple linearization technique is called for, taking advantage of the linear formulation of the problem. As a result, the method is suitable for any regression model with linear predictor and so current software can be used; threshold modelling as function of explanatory variables is also allowed. Differences between the other procedures available are shown and relative merits discussed. Simulations and two examples are presented to illustrate the method.

Comment on ‘Generating survival times to simulate Cox proportional hazards models with time-varying covariates’

2013

STUDY OF MASTITIS IN DAIRY SHEEP USING SURVIVAL ANALYSIS

2013

Mastitis is the most prevalent disease present in livestock species leading to economic loss. In dairy sheep, it caused mainly from bacterial infections. The aim of this work was to investigate the risk of having mastitis in Valle del Belice dairy ewes during the first lactation, due to environmental or contagious pathogens, using a survival analysis approach. All test‐day records from primiparous ewes were collected from five flocks. All test‐day were grouped in two data sets, one with mastitis due to environmental pathogens (ENV) and the other with mastitis due to contagious pathogens (CON). In this analysis the follow up period of a ewe was the lactation, consequently all the record bega…

A survival approach for the analysis of cruise passengers’ behavior at the destination

2016

The present work aims at proposing an analysis of cruise passengers’ behavior at the destination through a survival analysis approach. Data collected through GPS devices on cruise passengers’ behavior in the port of Palermo and Dubrovnik are analyzed in order to show similarities and differences among behaviors at the destination, according to socio-demographic characteristics. Results are of interest from both a methodological perspective, related with the processing and the analysis of GPS data, and from the destination management perspective.

Expanded criteria for liver transplantation in patients with cirrhosis and hepatocellular carcinoma

2008

Orthotopic liver transplantation (OLT) selection for patients with hepatocellular carcinoma (HCC) is a matter of debate. The Milan criteria (MC) have been largely adopted by the international community. The main aim of this study was to evaluate the survival rates and recurrence probabilities of a new proposal for criteria (up to 3 tumors, each no larger than 5 cm, and a cumulative tumor burden </= 10 cm). Patients with cirrhosis and HCC included on the waiting list (WL) from 1991 to 2006 were retrospectively analyzed. Outcomes in patients who had tumors within and beyond the MC were compared. The survival analysis was done (1) with the intention-to-treat principle and (2) among transplante…