General Semiparametric Shared Frailty Model Estimation and Simulation with frailtySurv

The R package frailtySurv for simulating and fitting semi-parametric shared frailty models is introduced. Package frailtySurv implements semi-parametric consistent estimators for a variety of frailty distributions, including gamma, log-normal, inverse Gaussian and power variance function, and provides consistent estimators of the standard errors of the parameters' estimators. The parameters' estimators are asymptotically normally distributed, and therefore statistical inference based on the results of this package, such as hypothesis testing and confidence intervals, can be performed using the normal distribution. Extensive simulations demonstrate the flexibility and correct implementation of the estimator. Two case studies performed with publicly available datasets demonstrate applicability of the package. In the Diabetic Retinopathy Study, the onset of blindness is clustered by patient, and in a large hard drive failure dataset, failure times are thought to be clustered by the hard drive manufacturer and model

Le risque de décès dans les Centres d'hébergement de soins de longue durée au Québec

Ce mémoire a pour but principal d'analyser le risque de décès (ou de survie) dans les Centres d'hébergement de soins de longue durée (CHSLD) au Québec. Les données sociosanitaires issues de la Régie d'assurance maladie du Québec (RAMQ) et du ministère de la Santé et des Services Sociaux (MSSS) ont permis de construire des modèles de risque proportionnel paramétrique permettant d'analyser ce phénomène. L'estimation de ces modèles montre que les patients qui manifestent un fort risque de décès dans les CHSLD sont : les hommes, les patients les plus âgés, les Montréalais vivant en CHSLD et ceux qui ont un mauvais état de santé avant le début du séjour. Ainsi, l'espérance de vie moyenne à l'entrée du CHSLD au Québec est d'environ 157 semaines. Quant à la relation entre les revenus moyens régionaux et le risque de décès dans les CHSLD, l'estimation faite à partir de données appariées n'a pu mettre en évidence sa significativité.The main aim of this thesis is to estimate the hazard of death (or survival) in long-term health care facilities in Quebec (CHSLD). The sociosanitary data from the Quebec Health Insurance Board (RAMQ) and the Ministry of Health and Social Services (MSSS) were used to build parametric proportional hazard models to analyze this phenomenon. The estimation of these models indicates that the patients who show a high risk of death in CHSLD are: males, oldest patients, Montrealers living in CHSLD, and those who have a worse health status before the beginning of the stay. The average life expectancy at the entrance of the CHSLD in Quebec is approximately 157 weeks (around 3 years). As for the relationship between average regional income and the risk of death in long-term health care facilities, the estimation based on matched data fails to its significance

Determining predictors of mortality in HIV positive people in South Africa, 2003 to 2009: a mixed methods approach incorporating unobserved variables

A thesis submitted to the School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, in fulfilment of the requirements for the degree Of Doctor of Philosophy. 02 April 2018.Background The largest proportion of HIV-infected people resides in Southern Africa. In South Africa, the government has taken the lead in the provision of free HIV treatment with a high coverage rate. Provision of free antiretroviral treatment has led to a decline in mortality rates and an increase in life expectancy. However, a significant number of people with HIV continue to die despite the availability of free treatment. A large proportion of studies have concentrated on using quantitative methods of analysis. Very few have used mixed methods that combine quantitative time-to-event frailty models and qualitative methods in assessing risk factors for mortality in HIV-infected individuals. However, use of such mixed methods approach could provide insights that may lead to an improvement in patient care and management. Aim To determine mortality risk factors in HIV-infected people through incorporating unobserved variables using a mixed methods approach in which quantitative findings are explained by the qualitative. Methods To critically review statistical methods used for assessing risk factors for mortality in HIV-infected people between the years 2002 and 2011. We conducted a literature review on the design of studies, how data were analysed and whether suitable statistical methods were utilised in assessing mortality risk factors in HIV-infected people in the period 2002-2011. Only publications written in English and listed in Pubmed/Medline were considered. In this review, papers using time-to-event techniques were regarded as appropriate. Data were split into two equal periods allowing for the comparison of the statistical methods over time. To compare the different time-to-event methods, we ran 1,000 simulations of parametric clustered data using parameters derived from an HIV study that was conducted in South Africa by the Perinatal HIV Research Unit (PHRU). Data for 5, 10 and 20 clusters of size 50 and 100 were simulated. Survival and censoring times were derived from a Weibull distribution. The minimum of survival and censoring times was taken as the study time. Using the simulated data, we compared the following time-to-event methods: Cox proportional hazards regression, shared Gamma frailty with Weibull and exponential baseline hazards (frequentist models), and the Bayesian integrated nested Laplace approximation (INLA) with Weibull baseline hazard. Parameter estimates, standard errors and their fit statistics were averaged over 1,000 simulations. Similarly, means and standard deviations from INLA were averaged (over the 1,000 simulations). Frequentist models were compared using the -2 loglikelihood fit statistics while all the four models were compared using the mean square error (MSE). Additionally, we simulated semiparametric clustered frailty models (using gamma and log-normal frailties) including INLA, h-likelihood, penalized likelihood and penalised partial likelihood estimations. Parameter estimates and their standard errors were presented graphically and compared using the MSE. To assess mortality risk factors in HIV-infected people in South Africa in different settings, factors associated with mortality in HIV-infected people were assessed by INLA survival frailty model using cohort data of HIV-infected people from South Africa. Two thirds were from Soweto (urban) and the rest from Mpumalanga (rural). Findings were evaluated by site. Mixed methods were used to evaluate risk factors for mortality by combining the best fitting model applied to retrospective data and qualitative analysis on prospective data. In order to explain the unobserved frailty modelling results, we conducted a qualitative study that enrolled 20 participants who had confirmed knowing a person that had died as a result of HIV. Participants were recruited from the Zazi VCT in PHRU and were interviewed using a semi-structured interview guide. The aim of the qualitative study was to attempt to explain the unobserved factors influencing mortality in HIV-infected individuals using perceived reasons for death given by the participants. These were later used to complement the potential reasons for death as identified in the frailty modelling (quantitative) results. Results In the critical review, 189 studies met the inclusion criteria that included prospective (69%) and retrospective (30%) studies. Of the 189 studies, 91 were published in the period 2002-2006 and 98 in 2007-2011. Cox regression analysis with frailty was used in only 7 studies (~4%); of which 6 were published between the years 2007- 2011. The simulation study showed that the shared frailty models performed better than Cox-PH. Within the shared frailty models, the Gamma frailty model with a Weibull baseline performed better than the Gamma frailty model with an exponential baseline. The MSE showed that in general, the Bayesian INLA had better results. In the semiparametric simulations, results were similar but INLA had a slightly better fit with consistently lower MSE values relative to both gamma and log-normal frailty models. The random effects estimate for INLA, whose method is slightly different, had lower MSE values consistently relative to the other methods. In the HIV cohort study, 6,690 participants were enrolled with majority being female (78%) and most participants residing in an urban area (67%). Rural participants were older (36 years; IQR: 31-44) and with a higher mortality rate (11/100 person years). Among those residing in rural areas, HAART treatment for between six and twelve months (HR: 0.2, 95% CI: 0.1-0.4) and more than 12 months (HR: 0.1, 95% CI: 0.1- 0.2) was protective relative to not being on treatment. Being on HAART treatment for greater than twelve months was protective in the urban participants (HR: 0.35, 95%CI: 0.27-0.46). Significant heterogeneity, assessed by frailty variance, was high in rural participants and lower in the urban. Since the frailty modelling results suggested that the unobserved variables had a significant effect on mortality in HIV-infected individuals, a qualitative study was conducted to explore the potential causes of death. In the qualitative study, participants perceived that mortality in HIV-infected individuals may have been influenced by engagement in risky sexual behaviour such as multiple sexual partnerships, negative attitude by healthcare workers towards HIV-infected people, believing in the healing power of religion, traditional medicine, food security and social support structure. Conclusions The study found that Cox proportional hazards regression with frailty is not commonly used in research on mortality in HIV-infected individuals as it is used in other fields of health research. Additionally, use of the more complex semiparametric frailty models was even lower in this population. From simulations, we found that frailty survival models provided a better fit in modelling mortality due to their ability to account for unobserved variables especially the Bayesian INLA. As the unobserved variables are complex to explain using only quantitative modelling techniques, qualitative analysis of perceived causes of death was explored. Unobserved variables affecting mortality were explored through qualitative analysis of perceived reasons provided by bereaved participants. This mixed methods approach optimised data by using a quantitative approach followed by a qualitative one that complemented each other. Use of optimal methods in assessing morbidity and mortality in HIV-infected patients may improve patient care and management in South Africa and other countries. Key words: HIV, Mortality, Rural, Urban, unmeasured variables, HAART, FrailtyLG201