Multi-state models for the analysis of time-to-treatment modification among HIV patients under highly active antiretroviral therapy in Southwest Ethiopia

BMC Infectious Diseases

Research Article

Belay Birlie¹  Roel Braekers²  Ziv Shkedy²  Tadesse Awoke³  Adetayo Kasim⁴ 

[1] Department of Statistics, Jimma University, Jimma, Ethiopia;I-BioStat, Hasselt University, Diepenbeek, Belgium;Institute of public Health, University of Gondar, Gondar, Ethiopia;Wolfson Research Institute for Health and Wellbeing, Durham University, Manchester, UK;

关键词: HIV/AIDS;    Highly active antiretroviral therapy;    Treatment modification;    Survial analysis;    Multistate models;   

DOI  :  10.1186/s12879-017-2533-3

 received in 2016-10-07, accepted in 2017-06-07,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundHighly active antiretroviral therapy (HAART) has shown a dramatic change in controlling the burden of HIV/AIDS. However, the new challenge of HAART is to allow long-term sustainability. Toxicities, comorbidity, pregnancy, and treatment failure, among others, would result in frequent initial HAART regimen change. The aim of this study was to evaluate the durability of first line antiretroviral therapy and to assess the causes of initial highly active antiretroviral therapeutic regimen changes among patients on HAART.MethodsA Hospital based retrospective study was conducted from January 2007 to August 2013 at Jimma University Hospital, Southwest Ethiopia. Data on the prescribed ARV along with start date, switching date, and reason for change was collected. The primary outcome was defined as the time-to-treatment change. We adopted a multi-state survival modeling approach assuming each treatment regimen as state. We estimate the transition probability of patients to move from one regimen to another.ResultA total of 1284 ART naive patients were included in the study. Almost half of the patients (41.2%) changed their treatment during follow up for various reasons; 442 (34.4%) changed once and 86 (6.69%) changed more than once. Toxicity was the most common reason for treatment changes accounting for 48.94% of the changes, followed by comorbidity (New TB) 14.31%. The HAART combinations that were robust to treatment changes were tenofovir (TDF) + lamivudine (3TC)+ efavirenz (EFV), tenofovir + lamivudine (3TC) + nevirapine (NVP) and zidovudine (AZT) + lamivudine (3TC) + nevirapine (NVP) with 3.6%, 4.5% and 11% treatment changes, respectively.ConclusionMoving away from drugs with poor safety profiles, such as stavudine(d4T), could reduce modification rates and this would improve regimen tolerability, while preserving future treatment options.

【 授权许可】

CC BY   
© The Author(s) 2017

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