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.

Conclusion: 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.