ArticlesPrognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes
Introduction
Expected prognosis when combination antiretroviral therapy (ART) is started is of great importance to patients with HIV-1 and their clinicians, and for planning of health-service provision and treatment guidelines. In developed countries, prognosis for patients starting therapy has been modelled in detail.1, 2, 3 A prognostic model developed by a collaboration of prospective studies from Europe and North America showed that risk of death was dependent on CD4 cell count, HIV-1 viral load, clinical stage, history of injecting drug use, and age.1, 2
Provision of ART has been scaled up in sub-Saharan Africa since 2004. WHO estimated that 2·7–3·1 million patients had started therapy in this region by the end of 2008.4 Mortality is higher in countries with scarce resources than it is in developed ones, especially in the first year of therapy.5, 6 However, no prognostic models are available for patients in sub-Saharan Africa. CD4 cell count and HIV-1 viral load are important prognostic factors for untreated patients and for those receiving ART, but in many clinics in sub-Saharan Africa neither CD4 cell counts nor viral load are routinely measured. In these settings, WHO recommends that clinical stage, or clinical stage with total lymphocyte count, should be used to assess eligibility for ART.7 Studies from high-income settings8, 9 also reported haemoglobin to be a good predictor of mortality in patients starting therapy, as did a small study in Durban, South Africa.10
We identified risk factors for death in patients starting ART in four large scale-up programmes in sub-Saharan Africa and developed two prognostic models: one including CD4 cell count and another in which CD4 cell count was replaced by measurement of total lymphocyte count and haemoglobin.
Section snippets
Patients and cohorts
We analysed four large scale-up cohorts in sub-Saharan Africa that participate in the International epidemiologic Databases to Evaluate AIDS (IeDEA): Gugulethu11 and Khayelitsha12 in Cape Town, South Africa; Lighthouse13 in Lilongwe, Malawi; and Centre de Prise en Charge de Recherches et de Formation (CEPREF)14 in Abidjan, Côte d'Ivoire. These programmes were chosen because of their systematic efforts to trace patients lost to follow-up and ascertain deaths. Eligible patients were not
Results
The four cohorts had 11 153 eligible patients with 9908 person years of follow-up within 1 year of start of ART. Table 1 shows numbers of patients, years of follow-up, and outcomes at 1 year in every cohort. The median CD4 cell count at ART initiation was 111 cells per μL (IQR 48–179) for all patients, 117 cells per μL (55–180) for those alive at 1 year, 50 cells per μL (16–124) for those who died, 98 cells per μL (35–186) for those lost to follow-up, and 119 cells per μL (50–201) for those who
Discussion
Both our models had good discriminatory power. CD4 cell count is the best prognostic factor in HIV-1 infection, but many ART programmes in sub-Saharan Africa do not have the resources to measure it routinely in all patients. CD4 cell counts can be replaced by haemoglobin and total lymphocyte counts for prognostic purposes.
We recorded a higher mortality in men than women and therefore produced sex-specific estimates of cumulative mortality. Women were younger and started treatment with
References (34)
- et al.
Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies
Lancet
(2002) - et al.
Developing a prognostic model in the presence of missing data: an ovarian cancer case study
J Clin Epidemiol
(2003) - et al.
The influence of human immunodeficiency virus-1 on hematopoiesis
Blood
(1998) - et al.
Treatable factors associated with severe anaemia in adults admitted to medical wards in Blantyre, Malawi, an area of high HIV seroprevalence
Trans R Soc Trop Med Hyg
(2005) - et al.
Prognosis of HIV-1-infected patients up to 5 years after initiation of HAART: collaborative analysis of prospective studies
AIDS
(2007) - et al.
A clinically prognostic scoring system for patients receiving highly active antiretroviral therapy: results from the EuroSIDA study
J Infect Dis
(2002) Towards universal access. Scaling up priority HIV/AIDS interventions in the health sector, 2009 Progress Report
Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries
Lancet
(2006)- et al.
Public-health and individual approaches to antiretroviral therapy: township South Africa and Switzerland compared
PLoS Med
(2008) Scaling up antiretroviral therapy in resource-limited settings: treatment guidelines for a public health approach, 2003 revision
(2004)
Anaemia is an independent predictive marker for clinical prognosis in HIV-infected patients from across Europe
AIDS
Prognostic importance of anaemia in HIV type-1-infected patients starting antiretroviral therapy: collaborative analysis of prospective cohort studies
Antivir Ther
Predictors of mortality in patients initiating antiretroviral therapy in Durban, South Africa
S Afr Med J
Early mortality among adults accessing antiretroviral treatment programmes in sub-Saharan Africa
AIDS
Seven-year experience of a primary care antiretroviral treatment programme in Khayelitsha, South Africa
AIDS
Peripheral neuropathy in HIV-positive patients at an antiretroviral clinic in Lilongwe, Malawi
Trop Doct
Rapid scaling-up of antiretroviral therapy in 10,000 adults in Côte d'Ivoire: 2-year outcomes and determinants
AIDS
Cited by (196)
Development and external validation of a prognostic model for survival of people living with HIV/AIDS initiating antiretroviral therapy
2021, The Lancet Regional Health - Western PacificCitation Excerpt :These models might not be applicable to PLWHA in developing areas where the medical resources are inadequate and therefore the risk profile of patients could be disparate compared with that in high-income settings. Less attention has been paid to the development of prognostic models for PLWHA in developing regions, with only two models being developed for PLWHA in sub-Saharan Africa10 and Haiti21, respectively. A recent model based on PLWHA in Wenzhou city, China20 was criticized for its high risk of bias in model development and poor model performance in external validation.23