Elsevier

The Lancet

Volume 376, Issue 9739, 7–13 August 2010, Pages 449-457
The Lancet

Articles
Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes

https://doi.org/10.1016/S0140-6736(10)60666-6Get rights and content

Summary

Background

Prognostic models have been developed for patients infected with HIV-1 who start combination antiretroviral therapy (ART) in high-income countries, but not for patients in sub-Saharan Africa. We developed two prognostic models to estimate the probability of death in patients starting ART in sub-Saharan Africa.

Methods

We analysed data for adult patients who started ART in four scale-up programmes in Côte d'Ivoire, South Africa, and Malawi from 2004 to 2007. Patients lost to follow-up in the first year were excluded. We used Weibull survival models to construct two prognostic models: one with CD4 cell count, clinical stage, bodyweight, age, and sex (CD4 count model); and one that replaced CD4 cell count with total lymphocyte count and severity of anaemia (total lymphocyte and haemoglobin model), because CD4 cell count is not routinely measured in many African ART programmes. Death from all causes in the first year of ART was the primary outcome.

Findings

912 (8·2%) of 11 153 patients died in the first year of ART. 822 patients were lost to follow-up and not included in the main analysis; 10 331 patients were analysed. Mortality was strongly associated with high baseline CD4 cell count (≥200 cells per μL vs <25; adjusted hazard ratio 0·21, 95% CI 0·17–0·27), WHO clinical stage (stages III–IV vs I–II; 3·45, 2·43–4·90), bodyweight (≥60 kg vs <45 kg; 0·23, 0·18–0·30), and anaemia status (none vs severe: 0·27, 0·20–0·36). Other independent risk factors for mortality were low total lymphocyte count, advanced age, and male sex. Probability of death at 1 year ranged from 0·9% (95% CI 0·6–1·4) to 52·5% (43·8–61·7) with the CD4 model, and from 0·9% (0·5–1·4) to 59·6% (48·2–71·4) with the total lymphocyte and haemoglobin model. Both models accurately predict early mortality in patients starting ART in sub-Saharan Africa compared with observed data.

Interpretation

Prognostic models should be used to counsel patients, plan health services, and predict outcomes for patients with HIV-1 infection in sub-Saharan Africa.

Funding

US National Institute of Allergy And Infectious Diseases, Eunice Kennedy Shriver National Institute of Child Health and Human Development, and National Cancer Institute.

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

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