# Survival probabilities for HIV infected patients through semi-Markov processes

Giovanni Masala; Giuseppina Cannas; Marco Micocci

Biometrical Letters (2014)

- Volume: 51, Issue: 1, page 13-36
- ISSN: 1896-3811

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topGiovanni Masala, Giuseppina Cannas, and Marco Micocci. "Survival probabilities for HIV infected patients through semi-Markov processes." Biometrical Letters 51.1 (2014): 13-36. <http://eudml.org/doc/268735>.

@article{GiovanniMasala2014,

abstract = {In this paper we apply a parametric semi-Markov process to model the dynamic evolution of HIV-1 infected patients. The seriousness of the infection is rendered by the CD4+ T-lymphocyte counts. For this purpose we introduce the main features of nonhomogeneous semi-Markov models. After determining the transition probabilities and the waiting time distributions in each state of the disease, we solve the evolution equations of the process in order to estimate the interval transition probabilities. These quantities appear to be of fundamental importance for clinical predictions. We also estimate the survival probabilities for HIV infected patients and compare them with respect to certain categories, such as gender, age group or type of antiretroviral therapy. Finally we attach a reward structure to the aforementioned semi-Markov processes in order to estimate clinical costs. For this purpose we generate random trajectories from the semi-Markov processes through Monte Carlo simulation. The proposed model is then applied to a large database provided by ISS (Istituto Superiore di Sanità, Rome, Italy), and all the quantities of interest are computed.},

author = {Giovanni Masala, Giuseppina Cannas, Marco Micocci},

journal = {Biometrical Letters},

keywords = {semi-Markov process; HIV states; waiting time distribution; evolution equation; survival probabilities; Monte Carlo simulation},

language = {eng},

number = {1},

pages = {13-36},

title = {Survival probabilities for HIV infected patients through semi-Markov processes},

url = {http://eudml.org/doc/268735},

volume = {51},

year = {2014},

}

TY - JOUR

AU - Giovanni Masala

AU - Giuseppina Cannas

AU - Marco Micocci

TI - Survival probabilities for HIV infected patients through semi-Markov processes

JO - Biometrical Letters

PY - 2014

VL - 51

IS - 1

SP - 13

EP - 36

AB - In this paper we apply a parametric semi-Markov process to model the dynamic evolution of HIV-1 infected patients. The seriousness of the infection is rendered by the CD4+ T-lymphocyte counts. For this purpose we introduce the main features of nonhomogeneous semi-Markov models. After determining the transition probabilities and the waiting time distributions in each state of the disease, we solve the evolution equations of the process in order to estimate the interval transition probabilities. These quantities appear to be of fundamental importance for clinical predictions. We also estimate the survival probabilities for HIV infected patients and compare them with respect to certain categories, such as gender, age group or type of antiretroviral therapy. Finally we attach a reward structure to the aforementioned semi-Markov processes in order to estimate clinical costs. For this purpose we generate random trajectories from the semi-Markov processes through Monte Carlo simulation. The proposed model is then applied to a large database provided by ISS (Istituto Superiore di Sanità, Rome, Italy), and all the quantities of interest are computed.

LA - eng

KW - semi-Markov process; HIV states; waiting time distribution; evolution equation; survival probabilities; Monte Carlo simulation

UR - http://eudml.org/doc/268735

ER -

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