Utility of an algorithm of surrogate markers for Cd4 count to determine eligibility for haart among HIV infected pregnant women.
Background: CD4 count is an important marker of disease progression in patients with HIV. But CD4 count testing is not always readily available in developing countries like Kenya. Studies have shown significant correlation between CD4 count and Total Lymphocyte Count (TLC) including two studies done in Kenya among children and non-pregnant adults. Various TLC cut-offs including WHO TLC cut-off of 1200 have had low predictive value for identifying subjects with low CD4 count. Both WHO and Kenya PMTCT programme recommends HAART for CD4 count <350celllmm3.There was need therefore to revise the TLC cut-off for CD4 Count <350cell/mm3 and develop clinical algorithms using biomarkers like haemoglobin level and BMI to raise the predictive value of TLC. Methods and Data analysis: This was a retrospective analysis of cross-sectional data from HIV infected pregnant, ARV naive women. Data was extracted from patients' charts and entered into a data proforma. The relationship between CD4 and TLC, BMI, HB and WHO Clinical Stage (WCS) was calculated using Pearson's Correlation and linear regression. Two by two tables were constructed to determine performance of various TLC thresholds using the Sensitivity, Specificity, PPV and NPV. These were used to compute Receiver Operating Curves (ROC) to determine the predictive accuracy for each of the biomarkers singly and in various combinations. Data was be analysed by SPSS version 15 and Stata 10. Results: Of 362 HIV positive pregnant women, 160(44.5%) had CD4 count <350 cells/rnrn". Using linear regression optimal cut-off points for TLC. HB, BMI were 850cell/mm3 . 8Ag/dl and 15.5kg/m2 respectively. These cut-off points were highly specific but with very low sensitivity. The best cut-off point using generated sensitivity and specificity values was TLC~2200 with Sensitivity of 68% and Specificity of 51% A 3-step algorithm of WCS 11&111, TLC~1000 and HB~12g/dl; in that order was the most optimal with a Sensitivity, Specificity, PPV, NPV . Youden's indexiJ) and ROC A,UC of 86.21 %,9200%, 94.3%. 74.20%,7200% and 89% respectively Conclusion: TLC, HB, WCS and BMI have low predictive accuracy for CD4 co nt c 350cell/mm3 when used alone Our data suggests that HB, BM!. and WCS increased the Sensitivity of TLC at all thresholds These markers combined in an algorithm are useful surrogate markers for CD4 Count and can be usee in .esource poor settings to determine eligibility for H.t,ART