Biography of an Experiment: The Search for a Predtor of CD4 Cell Count Continues: Total Lymphocyte Count is Not a Substitute for CD4 Cell Count in the Management of HIV-Infected in a Resource-Limited Setting
According to first author, Dr. Norah Akinola, this paper was “done in-house” with “no external funding.” It was chosen for a biography because it presented an excellent example of a publication in a major journal written entirely by Nigerian authors without collaborators from the West. Specifically, the paper focuses upon evaluating the World Health Organization’s recommendations about testing to determine when to start HIV treatment in resource-limited settings.
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Total lymphocyte count (TLC) has been recommended as a substitute for CD4 cell count for the management of HIV-infected individuals living in resource-limited settings. To confirm this, 151 TLCs and CD4 cell counts were obtained from 109 patients who had not yet started treatment and analyzed. CD4 cell counts of less than 200 cells/mm3 were found in 42 cases (37.8%) with TLCs of greater than or equal to 1200 cells/mm3. Thus, 1 in 3 individuals would have been deprived of needed treatment. Therefore, in this setting, TLC is not a reliable predictor of CD4 cell count in HIV-infected individuals.
FULL TEXT OF ARTICLE
Monitoring individuals with HIV infection/AIDS involves the use of expensive tools, which are not readily available in resource‐limited settings. In April 2002, the World Health Organization (WHO) recommended that, when a CD4 cell count is not available or is not affordable to obtain for affected individuals, a total lymphocyte count of less than 1000–1200 lymphocytes/mm3 in individuals with stage II or III disease be used as an indication to initiate antiretroviral therapy . This recommendation was based on rigorous evaluation of data obtained almost exclusively from developed countries [2rf3–4]. In 2001, Akanmu et al.  reported that total lymphocyte count could not be used as a surrogate for CD4 cell count in monitoring response to antiretroviral therapy. There is limited information on the relationship between CD4 cell counts and total lymphocyte count and other hematological indices in resource‐limited settings. This study was initiated to ascertain the reliability of total lymphocyte count as a substitute for CD4 cell count, determine the relationship of other hematological indices with CD4 cell count, and observe the influence of the person's sex, if any, on data collected.
Patients, materials, and methods.
All consenting HIV‐1–seropositive individuals, both symptomatic and asymptomatic, were recruited over a 12‐month period and were investigated. Hematological indices, such as hematocrit, WBC count, and WBC differential count, were obtained using an automated cell counter (Advia‐60; Advia). CD4 lymphocyte count was obtained using the Dynal Manual CD4 kit. Total lymphocyte count was calculated from the WBC count and the differential count for lymphocytes. The sensitivity and specificity of total lymphocyte count as a predictor of CD4 cell count were calculated together with the likelihood ratio . Data are presented as with 95% CIs and are analyzed using differential statistics.
A total of 151 results from 109 HIV‐1–seropositive individuals with a mean age of years were analyzed. There were significantly more female patients than male patients (ratio of male to female patients, 1:1.4). The mean hematocrit was 31.8%±7.0%, the mean WBC count was cells/mm3, the mean total lymphocyte count was lymphocytes/mm3, and the mean CD4 cell count was cells/mm3 (table 1).
Table 2 shows that male subjects were significantly older than female subjects ( vs. years; ) and had a higher mean hematocrit than female subjects (34%±7% vs. 30%±6.5%; ), but the other parameters showed no significant difference between the sexes.
Correlations between CD4 cell count and the other parameters (table 3) showed that total lymphocyte count (r =0.431; P<.001) and hematocrit (r = 0.373; P<.001) had significant positive correlations.
WBC count and age were not significantly correlated with CD4 cell count. Data on patient sex (table 4) showed that female sex had a stronger correlation (r = 0.472; P<.001) than did male sex (r =0.384; P<.01) with total lymphocyte count and CD4 cell count. However the reverse was the case for hematocrit and CD4 cell count (r = 0.453 [P<.001 ] and r=0.340 [P<.01 ], respectively).
For 111 results (73.5%; 64 female and 47 male patients), the total lymphocyte count was 1200 lymphocytes/mm3; of these patients, 42 (37.8%; 21 female and 21 male) had a CD4 cell count of <200 cells/mm3 (figure 1).
The sensitivity of TLC as a predictor of CD4 cell count was 45.5%, and the specificity was 62.2%. The likelihood ratio was 0.83.
The mean values obtained in this laboratory‐based study were similar to values reported elsewhere (table 1) [5, 6]. The correlation coefficient for CD4 cell count and hematocrit was not as strong as that for CD4 cell count and total lymphocyte count (table 3), and, therefore, hematocrit cannot be used as a predictor of CD4 cell count, particularly in patients with an advanced state of immunosuppression. Contrary to expectation, TLC did not correlate strongly with CD4 cell count, as was reported by Beck et al.  in 1996, and there was not a significant difference between male and female subjects with regard to CD4 cell count [7, 8]. Indeed, this study corroborates findings of other studies [5, 9] that TLC was not a surrogate for CD4 cell count and that it was “an imperfect predictor of CD4 count” . Again, support for this was provided by the sensitivity of total lymphocyte count as a predictor of CD4 cell count, which was <50% in this study. It was also observed that 1 of 3 results involving a total lymphocyte count of 1200 lymphocytes/mm3 had a CD4 cell count of <200 cells/mm3. This means that, at diagnosis, too many individuals would have gone untreated if the WHO guideline for the use of total lymphocyte count instead of CD4 cell count was implemented, and this would be unethical.
Total lymphocyte count is not a substitute for CD4 cell count in a resource‐limited setting: 1 in 3 individuals would be deprived of needed medication if a total lymphocyte count of 1200 cells/mm3 were used, as recommended by the WHO. CD4 cell counts per se were similar for male and female patients. Other hematological indices have not been found to be useful predictors of CD4 cell count, which will have to remain the gold standard for monitoring HIV‐infected individuals, even in a resource‐limited setting, until another readily available surrogate marker is found. The search continues.
References from Paper
1. WHO approved draft treatment guidelines for HIV-infected people in resource limited settings. The Hopkin's HIV report. The John Hopkins University AIDS Service2002;14:1-4. Available at: http://www.hopkins-aids.edu.
2. Beck EJ, Kupek EJ, Gompeis MM, Pinching AJ. Correlation between total and CD4 lymphocyte counts in HIV infection: not making the good an enemy of the not so perfect. Int J STD AIDS 1996;6:422-8.Web of Science
3. Blatt SP, Carlin J, Crowes SM. Total lymphocyte count as a predictor of absolute CD4+ count and CD+ percentage in HIV-infection persons. JAMA 1993;269:622-6.
4. Sloan P, Carlin J, Crowe SM. Program and abstracts of the VIIth International Conference on AIDS (Florence, Italy). Stockholm: International AIDS Society; 1991.Total lymphocyte count can predict low CD4: a useful substitute for T-subset analysis [abstract WB 2409].
5. Akanmu AS, Akinsete I, Eshofonie AO, Davies AO, Okanny CC. Absolute lymphocyte count as surrogate for CD4+ cell count in monitoring response to antiretroviral therapy. Niger Postgrad Med J 2001;8:105-11.
6. Adewuyi JO, Coutts AM, Latif AS, Smith H, Abayomi AE, Moyo AA.Haematological features of the human immunodeficiency virus (HIV) infection in adult Zimbabweans. Cent Afr J Med 1999;45:26-30.
7. Rudy BJ, Wilson CM, Durako S, Moscicki AB, Muenz L, Douglas SD. Peripheral blood lymphocyte subsets from the REACH project. Clin Diagn Lab Immunol2002;9:959-65
8. Gorter RW, Vranizan KM, Osmond DH, Moss AR. Differences in laboratory values in HIV infection by sex, race and risk group. AIDS 1992;6:1341-7.
9. van der Ryst E, Kotze M, Joubert G, et al. Correlation among total lymphocyte count, absolute CD4+ count, and CD4+ percentage in a group of HIV-1-infected South African patients. J Acquir Immune Defic Syndr Hum Retrovirol1998;19:238-44.
References for Tips [Amy]
3. Cohen, G.M. Access to diagnostics in support of HIV/AIDS and tuberculosis treatment in developing countries‚Äù AIDS. 21 (2007); S81-S87.
4. Mbanya, D., Assah, F., Ndembi, N., and Kaptue, L. ‚ÄúMonitoring antiretroviral therapy in HIV/AIDS patients in resource-limited settings: CD4 counts or total lymphocyte counts?‚Äù Int. Jour. of Inf. Dis. 11 (2006); 157-60.
5. Interview with Dr. Irinoye.
6. Interview with Professor Onayemi.
7. Interview with Professor Durosinmi.
8. For more information about flow cytometry, please visit: http://biology.berkeley.edu/crl/flow_cytometry_basic.html
10. Interview with Dr. Akinola.
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Clockwise from top right: Department of Pharmacy, Medical Microbiology and Parasitology Laboratory, Health Sciences Building, Obafemi Awolowo University, Ile-Ife, Nigeria
Photos courtesy of Laura VanArendonk.
Learn about Research in Developing Countries
The advantages of conducting research in resource-limited setting are clear – in that research relevant to a location can best be performed on site. As Professor Onayemi stated in our interview, despite limited resources, the global standard can still be used. It is nearly impossible for outside people to come into another setting and have the same level of knowledge as personnel from the region.
However, there are obstacles in infrastructure to conducting research in resource-limited setting that must be confronted head-on. For example, if there is a strike amongst the faculty at a university, no teaching occurs, but research goes on, according to Professor Durosinmi. Furthermore, Professor Onayemi noted that the erratic supply of electricity can present a challenge to sotring samples.
Hi! My name is Amy Labar and I am a Biology major with an Africana Studies concentration, class of 2010. During the summer of 2009, I spent 8 weeks working at Haverford on biology research about the transmission of antibiotic resistance in West Africa as well as 3 and a half weeks in Nigeria continuing my research and helping to lead a molecular microbiology workshop. During this trip, I interviewed as many of the authors of “The Search for a Predictor of CD4 Cell Count Continues: a Subsitute for CD4 Cell Count in the Management of HIV-Infected Individuals in a Resource-Limited Setting” as was possible. While in Nigeria, we extracted DNA from samples previously collected to take back to the US on which my thesis was done.
From left: Ikogosi Warm Springs, Ado-Ekiti, Nigeria and At Work in Medical Microbiology and Parasitology Lab, OAU, Ile-Ife, Nigeria
Photos courtesy of Laura VanArendonk.