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  Table of Contents    
ORIGINAL ARTICLE  
Year : 2011  |  Volume : 54  |  Issue : 1  |  Page : 107-111
Absolute lymphocyte count: A cost-effective method of monitoring HIV-infected individuals


1 Department of Medicine, Sir Ganga Ram Hospital, Rajinder Nagar, New Delhi - 110 060, India
2 Department of Hematology, Sir Ganga Ram Hospital, Rajinder Nagar, New Delhi - 110 060, India

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Date of Web Publication7-Mar-2011
 

   Abstract 

Aim: Depletion of CD4 cell count is a hallmark of disease progression in AIDS. CD4 cell count is essential for physicians to decide about the timing of initiation of antiretroviral therapy (ART) and for prophylaxis of opportunistic infections. WHO has recommended that, absolute lymphocyte count (ALC) of ≤1200/μL can substitute CD4 cell count of ≤200/μL in resource-constrained countries throughout the world. Materials and Methods: This study was undertaken to know whether there is a correlation between CD4 cell count and ALC in HIV-infected individuals. A single sample of blood was withdrawn for ALC and CD4 cell count. The samples received from December 1, 2004 to December 31, 2005 were analyzed. Results: A total of 196 samples were collected from 185 patients. After exclusion, a total of 182 samples were analyzed. Results revealed that male:female ratio was 126:56 and their age ranged from 13 to 67 years. The median ALC was 1747 cells/μL, whereas the CD4 cell count ranged from 5 to 2848. The correlation coefficient between ALC and CD4 cell count was significant (0.714). There were 49 patients with an ALC of ≤1200/μL of whom 77.6% patients had CD4 cell count ≤ 200/μL (true positive) and 22.4% had CD4 cell count > 200/μL (false positive). There were 133 patients with an ALC of >1200/μL of whom 84.2% had CD4 cell count > 200/μL (true negative) and 15.8% had CD4 cell count ≤ 200/μL (false negative). Taking ALC of ≤1200/μL as a predictor of CD4 cell count ≤ 200/μL ,the sensitivity of the test was 64.4% and specificity was 91.1%. The positive predictive value was 77.6%, negative predictive value was 84.2%, and accuracy was 82.4%. Conclusion: We found that an ALC of ≤ 1520/μL has higher sensitivity (78%) for a CD4 cell count of ≤ 200/μL. The ALC was found to be significantly cost-effective in our setup but chances of missing out patients requiring ART was 1 in 5 using the WHO guidelines.

Keywords: Absolute lymphocyte count, AIDS, CD4 cell count, HIV, India

How to cite this article:
Kakar A, Beri R, Gogia A, Byotra S P, Prakash V, Kumar S, Bhargava M. Absolute lymphocyte count: A cost-effective method of monitoring HIV-infected individuals. Indian J Pathol Microbiol 2011;54:107-11

How to cite this URL:
Kakar A, Beri R, Gogia A, Byotra S P, Prakash V, Kumar S, Bhargava M. Absolute lymphocyte count: A cost-effective method of monitoring HIV-infected individuals. Indian J Pathol Microbiol [serial online] 2011 [cited 2019 Dec 14];54:107-11. Available from: http://www.ijpmonline.org/text.asp?2011/54/1/107/77349



   Introduction Top


Measurement of viral load and CD4 cell count are important tests in the management of HIV-infected individuals. With the progression of the disease, there is a gradual depletion of CD4 cell count. Prophylaxis for opportunistic infection (OI) is also dependent on CD4 cell count, especially when CD4 falls below 200/μ L or CD4% < 20. [1] The present recommendation for testing CD4 cell count is every 4-6 months, however, the test is costly and the equipment required to do so is sophisticated. To overcome this problem, WHO has recommended that in resource-constrained countries, absolute lymphocyte count (ALC) could be the replacement for CD4 cell count. [2] There have been various studies touching on this topic with contradictory results. There have been studies showing good correlation between ALC and CD4 counts, while others showing only a weak surrogate marker for monitoring highly active antiretroviral therapy (HAART). We, therefore, studied if there was any positive correlation between ALC and CD4 cell count in our setup and if the correlation is significant enough such that ALC could be substituted for CD4 cell count in HIV-infected individuals.

The aims of our study were to evaluate the correlation between ALC of ≤ 1200/μ L to CD4 cell count of ≤ 200/μ L; also to evaluate if the ALC ≤ 1200/μ L would correspond to CD4 cell % of ≤ 20%. The study was aimed at determining the ALC cutoff, that would have maximum correlation with CD4 cell count of ≤ 200/μ L.


   Materials and Methods Top


All the patients presenting to the outpatient and inpatient department of the Department of Internal Medicine, Sir Ganga Ram Hospital, a tertiary care center in Delhi, were included in the study. A single sample of blood was withdrawn (5 mL of EDTA blood) for complete blood count (CBC) and CD4 cell count. Cases included in the study presented to the Hospital from December 1, 2004 to December 31, 2005 (a total of 13 months).

A total of 196 samples were taken from 185 patients. Demographic details such as age/gender were also noted. Samples belonging to pediatric age group (<12 years) were omitted. Finally a total of 182 samples were analyzed.

BC was done on a fully automated 5-part differential hematology analyzer (Gen S, Beckman-Coulter, Fullerton, California, USA), and the total leukocyte count was measured by flow cytometry (EPICS×L, Beckman-Coulter, Fullerton, California, USA). A hematologist also did differential count manually. The ALC was calculated by multiplying the percentage of lymphocytes in the peripheral smear by TLC (total lymphocyte count). Besides this, CD4 cell count, CD4%, CD8 cell count, CD8%, and CD4:CD8 ratio was obtained by flow cytometry.

Statistical analysis, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated taking CD4 cell count as a gold standard. Descriptive statistics of hematologic parameters were calculated, which included minimum, maximum, mean, Standard Deviation (SD), and standard error of mean (SEM). Spearman rank correlation (r) between ALC and CD4 cell count, CD4%, and CD8% were also calculated.

Receiver operating characteristic (ROC) curve was used to display the result of sensitivity and the false-positive error rate (1-specificity) of ALC and CD4 count ≤ 200/μ L and a similar curve depicted the relation between ALC and CD4% ≤ 20%. Scatter plots depicting the relationship between ALC and CD4 count were also plotted.


   Results Top


A total of 182 samples were analyzed for correlation between ALC and CD4 count. There were 126 males and 56 females. Their age ranged between 13 and 67 years with mean (±SD) of 36.3 (±10.6) [Table 1]. There were 15 patients in the age group of 13-19 years. Of these 17 patients, 15 were HIV positive and 2 were AIDS patients. The median (±SEM) value of ALC was 1747 (±83.89) /μ L. The CD4 cell count ranged from 5 to 2848 with a median (±SEM) value of 344 (±26.24). The median (±SEM) CD4% was 18.5% (±0.87) and CD8% was 56.8% (±26.055). [Table 1] summarizes the various hematologic parameters, and [Table 2] gives the distribution of CD4 cell count and CD4% with respect to ALC of <1200/μ L. The ROC curve was drawn between ALC and CD4 < 200/μ L and it was found that the area under the curve was 0.864 (significant). According to our study, the optimum cutoff value for ALC corresponding with CD4 cell count ≤ 200/μ L would be 1520/μ L [Figure 1]. Using similar statistical analysis, ROC relationship between ALC and CD4 cell % was calculated [Figure 2] and the area under the curve was 0.570 (not significant). Our study did not have a very good correlation between CD4% and ALC, although there was a good correlation between ALC and CD4 cell count as also depicted in scatter diagrams [Figure 3]. There were 26.9% of patients with an ALC of ≤1200/μ L and 73.1% patients with an ALC of >1200/μ L. There were 32.4% patients with CD4 cell count ≤ 200/μ L and 67.6% with CD4 cell count > 200/μ L. Taking CD4 cell count ≤ 200/μ L as a gold standard to depict ALC, the sensitivity, specificity, PPV, NPV, and accuracy were calculated for ALC of ≤1200/μ L and ALC of ≤1520/μ L [Table 3].
Figure 1: ROC curve between ALC & CD4 cell count < 200

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Figure 2: ROC curve between ALC and CD4 cell %

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Figure 3 : Scatter diagram between CD4 T cell (cells/mcl) count and absolute lymphocyte count

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Table 1: The demographic and laboratory profile of patients included in the study

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Table 2: Distribution of CD4 cell count and CD4% with respect to ALC

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Table 3: Taking CD4 cell count by flow cytometry as the gold standard, correlation of ALC ≤ 1200/μL with CD4 cell count ≤ 200/μL and CD4% ≤ 20% and correlation of ALC ≤ 1520/μL with CD4 cell count ≤ 200/μL and CD4% ≤ 20%

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The correlation coefficient between ALC and CD4 count was 0.714 and was significant with a P value of 0.01 [Table 4].
Table 4: Absolute lymphocyte count* CD4 (cells/μL)

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The cost-effectiveness of ALC was also calculated. The cost of CBC in our setup is Rs 200/-($4 USD) and that of a single CD4 count measurement is Rs 1000/-($20 USD). ALC was found to be cost-effective, as it could have saved Rs 62,000 ($1240 USD) in our study.


   Discussion Top


CD4 cell count of ≤200 cell/μ L is an important land mark in the management of AIDS patients; it is at this stage that antiretroviral therapy (ART) is started and co-trimoxazole prophylaxis is required. [1] Although CD4 cell count is considered the best laboratory marker of HIV infection, it is an expensive test and not widely available because of lack of sophisticated equipment. This problem is more in resource-constrained developing countries where the majority of people infected with HIV are living. Here the facilities for CD4 cell count testing may not be available/affordable. To overcome this problem, WHO has recommended that irrespective of the CD4 cell count, ART can be started on patients who have WHO stage III or IV disease and on patients who have WHO stage II disease with an ALC of ≤1200 /μ L (which can substitute CD4 cell count of ≤200/μ L), especially in resource-constrained areas. [2]

In our study, we found that ALC of <1200/μ L, as suggested by WHO, had a sensitivity of 64.4%, specificity of 91.1%, PPV 77.6%, NPV of 84.2%, and accuracy of 82.4%. We also found that ALC of 1520/μ L was more sensitive than 1200/μ L. Several other authors have also suggested a higher cutoff. [3],[4] The advantage of using a higher ALC is that it would help reduce failure rate of identifying patients who might benefit from ART or OI prophylaxis. However, this approach has the disadvantage of early (premature) institution of ART in patients for whom it is not required. [5]

Till recently no data was available from India correlating ALC with CD4 cell count, when in 2002 Kumarasamy et al. studied ALC as a useful tool for timing of OI in AIDS patients. They studied 650 paid samples for CD4 cell count and total lymphocyte count and found a good correlation as also found in our study. Instead of a cutoff value of 1200/μ L as suggested by WHO, they found ALC of ≤1400/μ L as a more appropriate value, which had 76% PPV, 86% NPV, 73% sensitivity, and 88% specificity. [3]

Another study suggested that sensitivity/specificity of ALC tends to be higher for patients younger than 50 years, and patients with higher plasma HIV-RNA values. [6] Post et al. suggested that ALC of ≤ 1250/μ L preceded the development of Pneumocystis carinii pneumonia or cerebral toxoplasmosis in 76% of patients. [7]

In our study, we found a strong correlation between ALC and CD4 cell count by Spearman rank order correlation (r = 0.714). A similar correlation has also been suggested in studies done in India and other parts of the world. However, there is a chance of missing 1 in 5 patients as was shown by our results. Moreover, not all authors have reported a positive correlation of CD4 cell count with ALC. A high missing rate of 1 in 3 was suggested by Akinola et al.[8] when ALC alone was used as a marker for CD4 cell count of < 200/μ L who concluded ALC to be an imperfect predictor of CD4 cell count.

ALC can also be used as a surrogate marker to monitor changes in the CD4 cell count following the initiation of HAART. [9] Badri and Wood in their study had suggested that ALC changes on HAART and the median change in CD4 cell count correlated with this change. [10]

There are many factors, such as diurnal variation, intercurrent illness besides age dependence, on which CD4 cell count depends. Some authors have suggested that adding hemoglobin, platelets, hematocrit, and clinical profile to ALC may improve the prediction of immunosuppression and studies done on this have shown a good correlation suggesting their use as surrogate markers. However, in India more studies need to be taken up before such criteria can be followed because of the difference in status of parity, co-infections, and nutrition. Adding clinical data and other hematologic parameters would also increase the efficacy of ALC test. In our study, although we have eliminated pediatric data, we could not ensure uniformity of collection of blood, as our collection center is open for 12 h only.

The cost of CD4 cell count is tremendous in India despite being subsidized by various organizations and facilities to measure this are not available universally. In our hospital, testing CD4 cell count would cost a patient 5 times more than the cost of ALC. Such huge amount of money if saved can be invested for supplying medicine to HIV/AIDS patients and improving their quality of life. The main drawback of our study was a small sample size, therefore, to make these results reproducible, larger studies may be done and the results confirmed further. On the basis of our study, we would suggest an algorithm as given in [Figure 4] below for workup of HIV-positive patients in resource-constrained areas with limited funding, expertise, and laboratory back up.
Figure 4: Suggested algorithm for workup of HIV-positive patient

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   Conclusion Top


Our study suggests that ALC is a good surrogate test for HIV management and has a significant strong positive correlation with CD4 cell count. Using WHO guidelines, with a cutoff ≤ 1200/μ L for ALC we would be able to treat 82% of patient requiring ART. The test is cost-effective and the funds saved can be utilized for the initiation of ART. We would recommend a higher cutoff value of ALC, that is, 1520/μ L, which would pick up maximum number of patients having CD4 count < 200/μ L. Our study did not have a very good correlation between CD4% and ALC < 1200/μ L.

 
   References Top

1.Sax PE. HIV Infection: In: Cunha BA, editor. Antibiotic Essentials. New York: Physicians press; 2005. P. 227-33.  Back to cited text no. 1
    
2.Scaling up antiretroviral therapy in resource-limited setting. Treating in resource limited setting. Treatment guidelines for public health approach. 2003 revision. Geneva: World Health Organization; 2004.  Back to cited text no. 2
    
3.Kumarasamy N, Mahajan AP, Flanign TP, Hemalatha 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. 3
    
4.Beck EJ, Kupek EJ, Gompels MM, Pinching AJ. Correlation between total and CD4 lymphocytes count 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. 4
[PUBMED]  [FULLTEXT]  
5.Stebbing J, Sawleshwarkar S, Michailidis C, Jones R, Bower M, Mandalia S, et al. Assessment of the efficacy of total lymphocyte count as predictor of AIDS defining infection in HIV -I infected people. Postgrad Med J 2005;81:586-8.  Back to cited text no. 5
[PUBMED]  [FULLTEXT]  
6.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. 6
[PUBMED]  [FULLTEXT]  
7.Post FA, Wood R, Maartens G. CD4 and total lymphocyte as predictor of HIV disease progression. Q J Med 1996;89:505-8.  Back to cited text no. 7
    
8.Akinola NO, Olasode O, Adediran IA, Onayemi O, Murainah A, Irinoye O, et al. The search for a predictor of CD 4 cell count continues. Total lymphocyte count is not a substitute for CD4 cell count in the management of HIV infected individuals in a resource limited setting. Clin Infect Dis 2004;39:79-81.  Back to cited text no. 8
    
9.Mahajan AP, Hogan JW, Synder B, Kumarasamy N, Mehta K, Solomon S, et al. Changes in total lymphocyte as a surrogate for change in CD4 count following initiation of HAART: Implications for monitoring in resource limited setting. J Acquir Defic Syndr 2004;36:567-76.  Back to cited text no. 9
    
10.Badri M, Wood R. Usefulness of total lymphocyte count in monitoring highly active antiretroviral therapy in resource limited setting. AIDS 2003;17:541-5  Back to cited text no. 10
    

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Correspondence Address:
A Gogia
J-6/27 Rajouri Garden, New Delhi - 110 027
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0377-4929.77349

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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]

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