Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts 610


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2015  |  Volume : 6  |  Issue : 1  |  Page : 23-26

Evaluation of total lymphocyte count (TLC) as a surrogate marker for CD4 count in HIV-positive patients for resource-limited settings


1 Department of Microbiology, Goldfield Institute of Medical Sciences and Research, Faridabad, Haryana, India
2 Department of Microbiology, Mayo Medical College, Lucknow, Uttar Pradesh, India
3 Department of Microbiology, Government Medical College, Aurangabad, Maharashtra, India

Date of Web Publication8-Dec-2014

Correspondence Address:
Sonali Jain
40 Anamika Apartments, 99 IP Extension, Patparganj, Delhi - 110 092
India
Login to access the Email id

Source of Support: NACO, Conflict of Interest: None

DOI: 10.4103/0975-9727.146418

Rights and Permissions
  Abstract 

Context: The immunity in HIV-infected patients becomes low due to involvement of CD4 cells. The single best predictor of AIDS onset identified is the percentage or absolute number of circulating CD4+ T cells. However, providences in resource-constraint settings may not have access to this laboratory measurement, or its cost may be prohibitive resulting in the need for an alternative, surrogate marker. Hence, total lymphocyte count (TLC) was evaluated as a probable surrogate marker for CD4 count in this study. Aims: To evaluate the correlation of CD4 counts with the TLC for predicting the progression of HIV infection, and to determine a range of TLC cut-offs for predicting CD4 count <200 cells/μl, which is important for the initiation of antiretroviral therapy (ART) and opportunistic infection (OI) prophylaxis. Settings and Design: This study was conducted in the Department of Microbiology at Government Medical College, Aurangabad. Materials and Methods: A total of 250 HIV-positive patients were included in the study. Their Complete Blood count and CD4 count were measured and the TLC was computed. Statistical Analysis Used: SPSS software version 10.0. Results: A positive correlation between TLC and CD4 count was observed in our study, highlighting the role of this surrogate marker in resource-limited settings. Further, a TLC cut-off of ≤1700 cells/μl was found to be the best predictor for a CD4 count <200 cells/μl. Conclusions: A general correlation between the surrogate marker TLC and expensive CD4 counts could be elicited for the population under study. A TLC cut-off of ≤1700 cells/μl was the best predictor of CD4 count <200 cells/μl. This study demonstrates the ability of TLC, whether used as a continuous or dichotomous data, to predict CD4 count or a CD4 count <200 cells/μl, respectively.

Keywords: CD4, HIV, surrogate marker, total lymphocyte count


How to cite this article:
Jain S, Singh AK, Bajaj J, Singh RP, Damle AS. Evaluation of total lymphocyte count (TLC) as a surrogate marker for CD4 count in HIV-positive patients for resource-limited settings. Muller J Med Sci Res 2015;6:23-6

How to cite this URL:
Jain S, Singh AK, Bajaj J, Singh RP, Damle AS. Evaluation of total lymphocyte count (TLC) as a surrogate marker for CD4 count in HIV-positive patients for resource-limited settings. Muller J Med Sci Res [serial online] 2015 [cited 2019 Oct 16];6:23-6. Available from: http://www.mjmsr.net/text.asp?2015/6/1/23/146418


  Introduction Top


Since the first reported case in the early 1980s, HIV infection has emerged as a leading cause of death infecting approximately 33 million people worldwide. In India, about 2.5 million people are living with HIV/AIDS in the country. [1] HIV infection leads to AIDS, and the major cause of morbidity and mortality in such patients is the opportunistic infections (OIs). Immunity in such patients becomes low due to involvement of CD4 cells. As the immunity of these patients declines during the course of the illness, they become vulnerable to various OIs. Hence, it is very crucial to monitor the immune status of these patients in order to evaluate the progression of the disease.

Laboratory Markers of Disease Progression in Hiv

Many clinical and laboratory markers have been used to estimate prognosis in patients with HIV-1 infection. Identification of laboratory markers that help predict progression to AIDS in people infected with HIV is desirable because of the implications for both clinical management and counselling of the patient.

The single best predictor of AIDS onset identified thus far is the percentage or absolute number of circulating CD4+ T cells. [2]

However, providences in resource-constraint settings may not have access to this laboratory measurement or its cost may be prohibitive resulting in the need for an alternative, surrogate marker. [3] Estimation of plasma viral loads is another reliable measure of the immune status and disease stage of HIV-infected patients. In the absence of viral loads and CD4 counts for monitoring HIV disease, the value of total lymphocyte count (TLC) as a surrogate for CD4 has been argued. [4]

Thus, a surrogate marker for CD4, if proven reliable, can provide a tool for monitoring disease status in the underdeveloped nations where the bulk of the HIV patients are present.

With better awareness about the immune status of the HIV-infected individuals through available reliable laboratory markers, an early diagnosis of OIs can be made. Highly active antiretroviral therapy (HAART) can also be instituted at an early stage.

Thus, this study was undertaken to evaluate the efficacy of TLC as a surrogate marker for CD4 in resource-limited areas.

Aims and Objectives

  1. To evaluate the correlation of CD4 counts with the TLC for predicting the progression of HIV infection.
  2. To determine a range of TLC cut-offs for predicting CD4 count <200 cells/μl, which is important for the initiation of ART and opportunistic infection prophylaxis.



  Materials and Methods Top


HIV-seropositive patients either hospitalized or reporting to the ART center at our institute between January 2007 and October 2008 were included in the study.

Their complete blood count was performed through the automated hematology coulter, and CD4 count was established through flow cytometry. TLC was derived by multiplying the total leukocyte count by the percentage of lymphocytes.



Correlation between CD4 counts and TLC was assessed by the computation of Spearman's (Rho) two-tailed correlation coefficient.

Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of various TLC ranges were also computed for CD4 count ≤200 cells/μl.

All statistical analyses were performed using SPSS software version 10.0 (SPSS, Chicago, IL, USA).


  Results Top


A total of 250 HIV-positive patients irrespective of the stage of the disease were included in the study.

Correlation of the CD4 Counts with the TLC

Correlation between the CD4 counts and TLC was computed to determine the significance, if any, of the relationship. Spearman's (Rho) two-tailed correlation coefficient [Table 1] was computed between the two variables using the SPSS software version 10.0.
Table 1: Correlation of TLC with CD4

Click here to view


A positive correlation (Rho or "r" = 0.77) between CD4 counts and TLC was found in our study.

Selecting TLC Cut-offs for Predicting CD4 Counts <200 cells/μl

Sensitivity, specificity, PPV, and NPV of the various TLC ranges were also computed for predicting CD4 counts <200 cells/μl. The results are shown in [Table 2].
Table 2: TLC for CD4 counts <200 cells/μl

Click here to view


A TLC cut-off of ≤1700 cells/μl had a PPV of 89.47% and NPV of 88.77%, and was 92.51% sensitive and 84.46% specific for a CD4 count <200 cells/μl. Thus, it had the best predictive value and was most sensitive in predicting a CD4 count of <200 cells/μl while not compromising on its specificity or NPV.


  Discussion Top


Correlation of the Absolute CD4 Counts with the TLC

In our study, there was a strong positive correlation between CD4 counts and TLC as determined by the Spearman's rank order coefficient (r = 0.77). A good correlation between the two variables has also been observed by other workers across the world [Kumaraswamy et al., in India [5] (r = 0.744), England [6] (r = 0.76), North America [7] (r = 0.77), South Africa [8] (r = 0.70), Uganda [9] (r = 0.73), and London [10] (r = 0.70)]. Other authors have had less convincing results and found a weaker correlation between CD4 cell count and TLC. [11],[12],[13]

Based on clinical studies of CD4 cell count and TLC, such as the ones outlined above, the World Health Organization (WHO) recommended that health facilities without the ability to perform CD4 measurement should use TLC to guide decisions on initiating ART. [14]

An important consideration is the variation in CD4 count among HIV-infected individuals of different ethnic groups. For example, CD4 counts in HIV-infected Asians and Ugandan patients have been reported to be lower than those of HIV-infected patients in Europe and the United States. Other studies have shown that West African adults have a physiological lymphocytosis that leads to higher TLC and CD4 counts than those of European patients. An additional potential confounder may be simple measurement error, which the authors suggest can be addressed by multiple TLC determinations at a single point. [3]

Thus, further research is needed to understand how to use TLC (alone and along with other low-cost markers like hemoglobin or symptoms staging) in resource-limited settings and how to account for the observed variability in TLC that is associated with inter-current infections, regional and ethnic differences, and differing measuring technologies.

Selecting TLC Cut-off for Predicting CD4 Counts <200 Cells/μl

In our study, we found that the TLC performed well in predicting CD4 counts and a TLC cutoff for predicting CD4 count<200cells/μl As per WHO and CDC guidelines, a CD4 count cutoff of <200 cells/μl should be used for the initiation of ART. [15] Thus, a TLC equivalent for CD4 <200 cells/μl was determined.

The four statistical parameters (PPV, NPV, sensitivity, and specificity) maximally aggregated at TLC ≤1700 cells/μl for CD4 <200 cells/μl and, hence, it was selected as the cut-off.

Various researchers across the globe have found different correlates of TLC for CD4 <200 cells/μl. Kumaraswamy et al., [5] from India found a TLC <1400 cells/μl, Blatt et al., [16] found a TLC <1400 cells/μl in the USA, Mwamburi et al., [4] found a TLC <1500 cells/μl in the USA, Stebbing et al., [17] found a TLC <1500 cells/μl in London, and Spaeck et al.,[18] found a TLC <1200 cells/μl in the USA corresponded to the canonical CD4 cut-off of 200 cells/μl, when therapy should be introduced.

The WHO recommends starting therapy when TLC falls below 1200 cells/μl in the presence of symptomatic HIV disease and CD4 counts are not available. TLC below 1200 cells/μl alone, without symptoms, is not considered grounds for starting treatment. [19]

Using the WHO-recommended TLC cut-off of 1200 cells/μl to diagnose a CD4 <200 cells/μl, the study conducted by Kamya et al., [9] in Uganda could not identify the majority of WHO stage 2 and 3 patients with CD4 counts less than 200 cells/μl. A prospective study of TLC as a simple surrogate for CD4 count, conducted in Mozambique, comes to a similar conclusion. [20] Thus, there is a need to establish a region-wise TLC cut-off for CD4 count <200 cells/μl.

Further, as explained earlier, variations in CD4 cell count may occur among patients of different racial ethnic and geographic backgrounds and among patients of different ages. For example, although Kumaraswamy et al., [5] have predicted a TLC cut-off of <1400 cells/μl for CD4 count <200 cells/μl in a South Indian HIV-positive cohort, our study has demonstrated a TLC cut-off of <1700 cells/μl for this western Indian HIV-positive cohort. This could be explained partly by geographic and demographic variations.

A national task force was constituted by the Indian Council of Medical Research (ICMR) to define reference ranges for several lymphocyte sub-populations in healthy Indians. The task force comprised six centers in different locations in India. In southern states, especially Tamil Nadu and Kerala, donors had relatively lower values of CD4 T cells and higher values of CD8 T cells, as compared to those from northern and western parts of India. [21] This could in part explain the reason for the higher TLC cut-off (1700 cells/μl) found in our study from western India, in comparison to the study from northern India by Kumaraswamy et al., [5] where the cut-off was lower (1400 cells/μl).

Thus, consideration must be given to demographic differences and their effects on CD4 cell count when interpreting studies and choosing TLC cut-off points.

 
  References Top

1.
Report on Global AIDS Epidemic 2008. p. 18. Available from: http://www.unaids.org. [Last accessed on 2008 Jan 28].  Back to cited text no. 1
    
2.
Fahey JL, Taylor JM, Detels R, Hofmann B, Melmed R, Nishanian P, et al. The prognostic value of cellular and serologic markers in infection with human immunodeficiency virus type 1. N Engl J Med 1990;322:166-72.  Back to cited text no. 2
    
3.
Schreibman T, Freidland G. Use of total lymphocyte count for monitoring response to antiretroviral therapy. Clin Infect Dis 2004;38:257-62.  Back to cited text no. 3
    
4.
Mwamburi DM, Ghosh M, Fauntleroy J, Gorbach SL, Wanke CA. Predicting CD4 counts using total lymphocyte count: A sustainable tool for clinical decisions during HAART use. Am J Trop Med Hyg 2005;73:58-62.  Back to cited text no. 4
    
5.
Kumarasamy N, Mahajan AP, Flanigan TP, Hemlatha R, Mayer KH, Carpenter CC, et al. Total lymphocyte count (TLC) is a useful tool for the timing of opportunistic infection prophylaxis in India and other resource-constrained countries. J Acquir Immune Defic Syndr 2002;31:378-83.  Back to cited text no. 5
    
6.
Beck EJ, Kupek EJ, Gompels 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;7:422-8.  Back to cited text no. 6
    
7.
Fournier AM, Sosenko JM. The relationship of total lymphocyte count to CD4 lymphocyte counts in patients infected with human immunodeficiency virus. Am J Med Sci 1992;304:79-82.  Back to cited text no. 7
    
8.
van der Ryst E, Kotze M, Joubert G, Steyn M, Pieters H, van der Westhuizen, 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 Human Retrovirol 1998;19:238-44.  Back to cited text no. 8
    
9.
Kamya MR, Semitala FC, Quinn TC, Ronald A, Njama-Meya D, Mayanja-Kizza H, et al. Total lymphocyte count of 1200 is not a sensitive predictor of CD4 lymphocyte count among patients with HIV disease in Kampala, Uganda. Afr Health Sci 2004;4:94-101.  Back to cited text no. 9
    
10.
Prasad KN, Nag VL, Dole TN, Ayyagari A. Identification of enteric pathogens in HIV-positive patients with diarrhoea in northern India. J Health Popul Nutr 2000;18:23-6.  Back to cited text no. 10
    
11.
Jacobson MA, Liu L, Khayam-Bashi H, Deeks SG, Hecht FM, Kahn J. Absolute or total lymphocyte count as a marker for CD4 T lymphocyte criterion for initiating antiretroviral therapy. AIDS 2003;17:917-9.  Back to cited text no. 11
    
12.
Badri M, Wood R. Usefulness of total lymphocyte count in monitoring highly active antiretroviral therapy in resource-limited settings. AIDS 2003;17:541-5.  Back to cited text no. 12
    
13.
Pascale JM, Isaacs MD, Contreras P, Gomez B, Lozano L, Austin E, et al. Immunological markers of disease progression in patients infected with the human immunodeficiency virus. Clin Diagn Lab Immunol 1997;4:474-7.  Back to cited text no. 13
    
14.
Ammann A, Burrowes S. Use of Total Lymphocyte Count vs. CD4 Cell Count as a Marker of Immunity in HIV-infected Adults and Children. 2006. Available from: http://www.womenchildrenhiv.org/whiv. [Last accessed on 2008 Jun 10].  Back to cited text no. 14
    
15.
National Guidelines for Implementation of Antiretroviral Therapy (ART) August 2004. National AIDS Control Organization. Available from: http//www.nacoonline.org/guidelines/ART. Guidelines.pdf. [Last accessed on 2008 May 26].  Back to cited text no. 15
    
16.
Blatt SP, Lucey CR, Butzin CA, Hendrix CW, Lucey DR. Total lymphocyte count as a predictor of absolute CD4+ count and CD4+ percentage in HIV-infected persons. JAMA 1993;269:622-6.  Back to cited text no. 16
    
17.
Stebbing J, Sawleshwarkar S, Michailidis C, Jones R, Bower M, Mandalia S, et al. Assessment of the efficacy of total lymphocyte counts as predictors of AIDS defining infections in HIV-1 infected people. Postgrad Med J 2005;81:586-8.  Back to cited text no. 17
    
18.
Spacek LA, Griswold M, Quinn TC, Moore RD. Total lymphocyte count and hemoglobin combined in an algorithm to initiate the use of highly active antiretroviral therapy in resource-limited settings. AIDS 2003;17:1311-7.  Back to cited text no. 18
    
19.
WHO Guidelines for Scaling up Antiretroviral Therapy in Resource Limited Setting. Available from: http://www.aidsmap.com. May 20, 2004. [Last accessed on 2008 Jan 14].  Back to cited text no. 19
    
20.
Liotta G, Perno CF, Ceffa S, Gialloreti LE, Coehlo E, Erba F, et al. Is total lymphocyte count a reliable predictor of the CD4 lymphocyte cell count in resource-limited settings? AIDS 2004;18:1082-3.  Back to cited text no. 20
[PUBMED]    
21.
Saxena RK, Choudhry V, Nath I, Das SN, Paranjape RS, Babu G, et al. Normal ranges of some select lymphocyte sub-populations in peripheral blood of normal healthy Indians. Curr Sci 2004;86:969-75.  Back to cited text no. 21
    



 
 
    Tables

  [Table 1], [Table 2]


This article has been cited by
1 Costs of HIV/AIDS treatment in Indonesia by time of treatment and stage of disease
Adiatma Y. M. Siregar,Noor Tromp,Dindin Komarudin,Rudi Wisaksana,Reinout van Crevel,Andre van der Ven,Rob Baltussen
BMC Health Services Research. 2015; 15(1)
[Pubmed] | [DOI]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Materials and Me...
Results
Discussion
References
Article Tables

 Article Access Statistics
    Viewed2926    
    Printed104    
    Emailed0    
    PDF Downloaded264    
    Comments [Add]    
    Cited by others 1    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]