Multi-state models for defining degrees of chronicity related to HIV-infected patient therapy adherence

• Published in: Cadernos de saúde pública Vol. 29; no. 4; pp. 801 - 811
• Main Authors: Oliveira, Raquel de Vasconcellos Carvalhaes de, Shimakura, Silvia Emiko, Campos, Dayse Pereira, Victoriano, Flaviana Pavan, Ribeiro, Sayonara Rocha, Veloso, Valdiléa G., Grinsztejn, Beatriz, Carvalho, Marilia Sá
• Format: Journal Article
• Language: English
• Published: Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz 01-04-2013; Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz
• Subjects: Disease Progression; HIV; Patient Compliance; PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH; Survival Analysis; Análise de Sobrevivência; HIV; VIH; Survival Analysis; Cooperação do Paciente; Patient Compliance; Progressão da Doença; Cooperación del Paciente; Progresión de la Enfermedad; Análisis de Supervivencia; Disease Progression
• ISSN: 1678-4464; 1678-4464
• DOI: 10.1590/S0102-311X2013000400017

Few studies on AIDS that evaluate factors associated with treatment failure have considered the slow evolution of the disease and multiple health state transitions following the use of antiretrovirals. In this article we study factors associated with the progression between different stages of the disease, focusing on therapy adherence using a sample of 722 HIV+ patients followed up for 3 years. States were defined using the following classifications of the CD4 cell count: s1 (CD4 ≥ 500); s2 (350 ≤ CD4 < 500); and s3 (CD4 < 350). The transitions between states were modeled using multi-state models. Antiretroviral therapy adherence and disease duration were associated with transitions between immune states during follow-up. Low adherence increased the hazard ratio of a transition between s1 to s2 and intermediate adherence increased the hazard ratio of a transition between s2 to s3. On the other hand, older age and disease duration between two and four years are protective factors for AIDS progression. Multi-state modeling is a powerful approach for studying chronic diseases and estimating factors associated with transitions between each stage of progression, thus enabling the use of more individualized and effective interventions.