An evaluation of low‐cost progression markers in HIV‐1 seropositive Zambians

Abstract

CD4 count and viral load are important parameters for the follow-up of HIV disease and antiretroviral treatment decisions. On political levels, the possibility of supplying antiretrovirals at a reduced cost for developing countries is being discussed. However, expensive laboratory tests will be out of reach for the majority of the world's HIV-infected individuals. Alternative methods for the counting of lymphocyte subsets have been introduced, but have not been evaluated on a larger scale. Very few studies have addressed the use of surrogate markers for HIV progression in African populations. In this study, we measured CD4 counts in Zambians using a fluorescence-activated cell sorter (FACS), compared them with CD4 counts obtained manually by the immunoalkaline phospatase method (IA) on blood smears, and investigated their correlation with neopterin, beta-2-microglobulin (B2M), haemoglobin and total lymphocyte count (TLC). We compared progression markers with clinical parameters and outcomes in these patients. Blood was taken from 147 HIV-1 infected individuals attending an out-patient clinic at the University Teaching Hospital in Lusaka. All patients were part of a study on tuberculosis preventive therapy, the results of which we have reported before[1]. FACS CD4 results were obtained using a FACScount analyser (Becton Dickinson, Mountain-View, CA, USA) with controls and reagents provided by the manufacturer. Blood smears, prepared as for conventional haematological examination, were stored at −20 °C until the immunocytochemical labelling was done with monoclonal antibodies against CD4 and CD8 receptors (provided by DAKO, Copenhagen, Denmark) using the IA technique[2]. Two hundred lymphocytes were counted on each slide for determination of CD4 and CD8 percentages. The absolute counts for the lymphocyte subsets were calculated using the differential counts done manually and full blood counts obtained by Coulter counter. Serum neopterin levels were measured by ELISA (BRAHMS, Berlin, Germany), as was B2M (Pharmacia, Uppsala, Sweden), using standards provided by the manufacturers. All correlations were assessed using Spearman's rank correlation coefficient. The median value of each progression marker was compared for those patients with and without particular clinical symptoms using the rank sum test. Data were analysed using EpiInfo version 5 (CDC, Atlanta, GA, USA) and Stata version 5 (Stata Corporation, College Station, TX, USA). Sixty-five patients (44%) were female and the mean age was 31.8 years. Twenty-nine patients (20.1%) had a history of herpes zoster infection. Diarrhoeal disease of more than 6 days during the previous 6 months was reported in 45 patients (31%). Eleven individuals (8%) presented with oral candidiasis, and 82 (56%) with lymphadenopathy. Eighteen patients were lost to follow-up, the remaining 129 patients were seen for 12 months: 85 (66%) stayed well or presented with minor clinical problems, and 44 patients (34%) fell ill with conditions such as diarrhoea or cough for more than 2 weeks, weight loss more than 10% of the body weight, illnesses requiring admission to hospital, or any opportunistic infections. Fourteen patients (11%) died. The median values (interquartile ranges in brackets) for progression markers at baseline were: FACS CD4 232/μL [144–402], IA CD4 386/μL [230–592], FACS CD4/CD8 ratio 0.28 [0.16–0.46], IA CD4/CD8 ratio 0.35 [0.23–0.55], FACS CD8 858/μL [579–1192], IA CD8 1041/μL [738–1494], neopterin 16.8 nmol/L [11.8–22.9], B2M 3.9 mg/L [2.9–5.9], haemoglobin 12.3 g/dL [10.9–13.9], TLC 2173/μL [1568–2650]. IA CD4 counts were highly correlated with FACS CD4 counts (r = 0.89; P < 0.001) ( Fig. 1a); an IA CD4 < 350/μL had 83% sensitivity and 87% specificity to detect a FACS CD4 < 200/μL. Correlations (a) between CD4 counts obtained by the immunoalkaline phosphatase method (IA CD4) and by FACScount analysis (FACS CD4), and (b) between CD4/CD8 ratios obtained by the immunoalkaline phosphatase method (IA CD4/CD8) and by FACScount analysis (FACS CD4/CD8). The correlations between IA and FACS CD8 (r = 0.88) and IA and FACS ratio (r = 0.91) were similarly strong (P < 0.001) ( Fig. 1b). Significant correlations were also found between FACS CD4 and neopterin (r = − 0.41, P < 0.001), B2M (r = − 0.28, P = 0.004), haemoglobin (r = 0.20, P = 0.025), and TLC (r = 0.56, P < 0.001). A TLC < 2000/μL identified 69% of patients with a FACS CD4 < 200/μL with a specificity of 60%. Comparing median values in patients presenting with and without oral candidiasis, we found significant differences in CD4 count (158 vs. 248/μL, P = 0.01), neopterin (36.5 vs. 15.6 nmol/L, P = 0.002), haemoglobin (11 vs. 12.5 g/dL, P = 0.048), and TLC (1632 vs. 2202/μL, P = 0.011). Patients with a history of herpes zoster had lower CD4 counts than those without (171 vs. 248/μL, P = 0.023). Lymphadenopathy was associated with lower CD4 (203 vs. 282/μL, P = 0.011) and higher neopterin (18.2 vs. 14.1 nmol/L, P = 0.02). Patients with and without recent diarrhoea showed differences in CD4 counts (178 vs. 263/μL, P = 0.007), neopterin (22.6 vs. 15 nmol/L, P < 0.001), B2M (5.5 vs. 3.6 mg/L, P = 0.006), and haemoglobin (11.7 vs. 12.6 g/dL, P = 0.005). Looking at the patients' well-being in the follow-up period, we found median progression markers significantly different between patients staying well and patients falling ill (CD4 316 vs. 154/μL, P < 0.001; neopterin 14.9 vs. 21.8 nmol/L, P < 0.001; B2M 3.7 vs. 5.7 mg/L, P = 0.003; haemoglobin 12.9 vs. 11.3 g/dL, P = 0.001; TLC 2268 vs. 1898/μL, P = 0.006). Death was associated with lower CD4 (80 vs. 249/μL, P < 0.001), higher neopterin (21.6 vs. 15.4 nmol/L, P = 0.01), lower haemoglobin (10.8 vs. 12.8 g/dL, P = 0.002), and lower TLC (1610 vs. 2236/μL, P = 0.009). The difference in B2M (5.9 vs. 3.9 mg/L) was not significant. Neopterin was the only progression marker to predict weight loss (21 vs. 15.1 nmol/L, P = 0.01). The FACScount is a simple analyser providing automated absolute T subset counts, but the cost per sample (US$25) is too high for most Zambian patients. The IA method is simple and cheap (< US$5), being based on manual counting, but gives consistently higher results, which have been described elsewhere[3]. CD4 antibody reaction with monocytes is not blocked on slides; we found differentiation between lymphocytes and monocytes difficult on smears of poor quality, or on smears with many activated lymphocytes, as were frequently found in our patients. The heterogeneity of the CD8 cell population caused problems for the counting of some samples; the very weakly reacting population of CD8+ cells can easily be missed and counted as negative. Using the IA method, a CD4 count < 350/μL would provide an appropriate detection of immunosuppression in our study population. The role of immune activation markers in African HIV infection is not clear; immune activation is prevalent in many individuals, regardless of their HIV status. However, neopterin and B2M were good predictors of survival in West Africans[4]. B2M predicted death in Rwandans[5], and neopterin indicated response to antituberculosis treatment in Zambia[6]. In this study, neopterin is more sensitive than B2M for the clinical evaluation of HIV-infected patients. Unlike neopterin, B2M did not give additional information justifying its cost (US$5 for each). In most clinical settings in the developing world a full blood count is easily available. Anaemia was a very good indicator of HIV progression in our cohort from urban Lusaka. Haemoglobin could be of limited value in populations where anaemia due to parasitic infections and micronutrient deficiency is more common. Our findings do not support the use of lymhocyte counts to predict CD4 counts: sensitivity is much lower than in study populations from industrialized countries[7]. However, lymphopenia was indicative of clinical HIV progression. and sadly, for many settings in developing countries, a simple blood count will at present remain the only available laboratory parameter for HIV progression.