HIV-disease progression modelling
Collaborative partners: University of Ulster, UK and University of Cagliari, Italy.
Approach: Phase type survival tree analysis, survival analysis, Markov process model, Bayesian Analysis
Data: Istituto Superiore di Sanità (ISS), Roma, Italy
Abstract: Disease progression models are useful tools for gaining a systems' understanding of the transitions to disease states, and characterizing the relationship between disease progress and factors affecting it such as patients' profile, treatment and the HIV diagnosis stage. Patients are classified into four states (based on CD4+ T-lymphocyte count) and all the transitions are allowed. Examinations to identify disease progression of the patient are carried out routinely throughout the follow-up period. Therefore, the times spent at the various HIV infection stages are interval censored or right censored. This makes difficult to use simple statistical methods such as regression to model the disease progression and its relationship with the diagnosis stage. We would develop novel, more intuitive and realistic approaches based on phase type distributions and phase type survival trees to model progression of HIV infection and the effects and prognostic significance of HIV diagnosis stage and other covariates including patient's age and gender. The approach is illustrated using a real database of total 2,092 HIV infected patients enrolled in the Italian public structures from January 1996 to January 2008. The approach can also be used to examine the effect of other covariates such as patient's profile.
Reference:
Approach: Phase type survival tree analysis, survival analysis, Markov process model, Bayesian Analysis
Data: Istituto Superiore di Sanità (ISS), Roma, Italy
Abstract: Disease progression models are useful tools for gaining a systems' understanding of the transitions to disease states, and characterizing the relationship between disease progress and factors affecting it such as patients' profile, treatment and the HIV diagnosis stage. Patients are classified into four states (based on CD4+ T-lymphocyte count) and all the transitions are allowed. Examinations to identify disease progression of the patient are carried out routinely throughout the follow-up period. Therefore, the times spent at the various HIV infection stages are interval censored or right censored. This makes difficult to use simple statistical methods such as regression to model the disease progression and its relationship with the diagnosis stage. We would develop novel, more intuitive and realistic approaches based on phase type distributions and phase type survival trees to model progression of HIV infection and the effects and prognostic significance of HIV diagnosis stage and other covariates including patient's age and gender. The approach is illustrated using a real database of total 2,092 HIV infected patients enrolled in the Italian public structures from January 1996 to January 2008. The approach can also be used to examine the effect of other covariates such as patient's profile.
Reference:
- Garg, L., Masala G., McClean S.I., Micocci M., Cannas G. (2012). Using phase type distributions for modelling HIV disease progression, Computer-Based Medical Systems (CBMS), 2012 25th International Symposium on, 20-22 June 2012. doi: 10.1109/CBMS.2012.6266408.
- Garg L, McClean SI, Meenan BJ, Millard PH (2011). Phase-type survival trees and mixed distribution survival trees for clustering patients’ hospital length of stay. INFORMATICA. 22(1): 57-72.
Skills required
Soft skills: Strong analytical and problem solving skills and fast learning abilities, reliable, responsible, hard working, enthusiasm and determination to learn and acquire new skills.
Software Skills: Good programming skills in a language of your choice is highly desirable but not required.
Soft skills: Strong analytical and problem solving skills and fast learning abilities, reliable, responsible, hard working, enthusiasm and determination to learn and acquire new skills.
Software Skills: Good programming skills in a language of your choice is highly desirable but not required.
