Prioritizing CD4 Count Monitoring in Response to ART in Resource-Constrained Settings: A Retrospective Application of Prediction-Based Classification

Luis Montaner and colleagues retrospectively apply a potential capacity-saving CD4 count prediction tool to a cohort of HIV patients on antiretroviral therapy

Distribution of CD4 count.

<p>The distribution of CD4 count at 6-mo time intervals was assessed for both Cohort 1 (left) and Cohort 2 (right). Means were calculated for patients with multiple CD4 count assessments in the same interval.</p

Observed and predicted values resulting from application of PCB to Cohort 1.

<p>Data are expressed as number of observations (percent of total).</p>a<p>Prioritized CD4 testing recommended for this group.</p

Cohort description.

<p>Data are expressed as number of individuals (number of observations over time). Cohort 1 is composed of individuals with complete data—between one and six assessments (CD4⁺ T cell count, WBCC, and Lymph% measured at the same time) within each 6-mo interval—for 1 y of follow-up. Cohort 2 is composed of individuals with complete data for 3 y of follow-up.</p

PBC predictive model application.

<p>The PBC predictive model (FPR 10%, CD4 threshold = 200 cells/µl) was applied to six patients form Cohort 2 (cases 1–6), selected to represent a range of baseline CD4⁺ T cell counts (low, case 1 and 2; medium, case 3–5; and high, case 6). The red and green lines represent assessed WBCC (WBC) and Lymph%, respectively; the blue line represents assessed CD4⁺ T cell count. The PBC algorithm application prediction at the corresponding visits is represented by red dots (predicted CD4⁺ T cell count ≤200 cells/µl, requiring laboratory-based testing) or green dots (predicted CD4⁺ T cell count >200 cells/µl, no laboratory-based testing required).</p

Summary of model performance.

<p>(A) Cross-validated estimates of FPRs. The bars represent the number of observed post-baseline observations below the thresholds indicated on the <i>x-</i>axis and at the indicated FPRs for Cohort 1 (left) and Cohort 2 (right). The dark shading indicates the number of observations correctly identified for laboratory-based CD4 testing (i.e., CD4 counts predicted to be and observed to be below threshold); lighter shading represents false positives (CD4 count incorrectly predicted as above threshold); cross-validated estimates of the FPRs are indicated above each bar. (B) Capacity savings (CS) estimates. Dark shading indicates the number of observations in Cohort 1 (left) and Cohort 2 (right) predicted to require laboratory-based CD4 testing (i.e., CD4 count predicted to be below threshold), and light shading the number of observations predicted to not require laboratory testing (i.e., CD4 count predicted to be above threshold) at the CD4 count threshold and FPR indicated below each bar.</p

Mixed-effects change-point modeling results for Cohort 1.

a<p>[Time−1]+ indicates the positive component of [Time−1], given as follow-up time after the first month for Time >1 mo, and 0 for Time ≤1 mo.</p>b<p>WBCC is scaled by (divided by) a factor of ten.</p

Re-substitution and CV counts and estimates for the PBC model.

a<p>K: CD4⁺ T cell count threshold (cells/µl).</p>b<p>FPR, assigned.</p>c<p>Re-substitution estimate (mean CV estimate; SD of cross-validated estimates).</p>d<p>Fixed, as determined by FPR.</p><p>NPV, negative predictive value; PPV, positive predictive value.</p

Baseline characteristics.

a<p>Percent of patients with one or more post-baseline visits with CD4 count >1.2×baseline CD4.</p><p>IRQ, interquartile range (25^th percentile, 75^th percentile).</p