Total lymphocyte count (TLC) is a useful tool for the timing of opportunistic infection prophylaxis in India and other resource-constrained countries.
BACKGROUND
In most resource-constrained countries, CD4 cell count testing is prohibitively expensive for routine clinical use and is not widely available. As a result, physicians are often required to make decisions about opportunistic infection (OI) chemoprophylaxis without a laboratory evaluation of HIV stage and level of immunosuppression. OBJECTIVES To evaluate the correlation of total lymphocyte count (TLC), an inexpensive and widely available parameter, to CD4 count. To determine a range of TLC cutoffs for the initiation of OI prophylaxis that is appropriate for resource-constrained settings.


METHODS
Spearman correlation between CD4 count and TLC was assessed in patients attending an HIV/AIDS clinic in South India. Positive predictive value (PPV), negative predictive value (NPV), and sensitivity and specificity of various TLC cutoffs were computed for CD4 count <200 cells/mm3 and <350 cells/mm3. Correlation and statistical indices computed for all patients and for patients dually infected with HIV and active tuberculosis.


RESULTS
High degree of correlation was noted between 650 paired CD4 and TLC counts (r = 0.744). TLC <1400 cells/mm3 had a 76% PPV, 86% NPV, and was 73% sensitive, 88% specific for CD4 count <200 cells/mm3. TLC <1700 cells/mm3 had a 86% PPV, 69% NPV, and was 70% sensitive, 86% specific for CD4 count <350 cells/mm3. The cost of a single CD4 count in India is approximately 30 US dollars, whereas the cost of a single TLC is 0.80 US dollars.


CONCLUSIONS
TLC could serve as a low-cost tool for determining both a patient's risk of OI and when to initiate prophylaxis in resource-constrained settings. PPV, NPV, sensitivity, and specificity maximally aggregated at TLC <1400 cells/mm3 for CD4 <200 cell/mm3 and TLC <1700 cells/mm3 for CD4 <350 cells/mm3. Selection of appropriate TLC cutoffs for prophylaxis administration should be made on a regional basis depending on OI incidence, antimicrobial resistance patterns, and availability of the antimicrobials.
Kumarasamy
N
N
Y.R.G. Centre for AIDS Research and Education, Chennai, India. nkumarasamy@eth.net
Mahajan
Anish P
AP
Flanigan
Timothy P
TP
Hemalatha
R
R
Mayer
Kenneth H
KH
Carpenter
Charles C J
CC
Thyagarajan
S P
SP
Solomon
Suniti
S
D017088:AIDS-Related Opportunistic Infections / Q000276:immunology / Q000517:prevention & control*; D018791:CD4 Lymphocyte Count / Q000191:economics; D003365:Costs and Cost Analysis; D003906:Developing Countries; D005260:Female; D015658:HIV Infections / Q000276:immunology*; D006801:Humans; D007194:India; D018655:Lymphocyte Count / Q000191:economics; D008297:Male; D011237:Predictive Value of Tests; D014376:Tuberculosis / Q000276:immunology / Q000517:prevention & control; D014397:Tuberculosis, Pulmonary / Q000276:immunology / Q000517:prevention & control