Prospective International Study of Incidence and Predictors of Immune Reconstitution Inflammatory Syndrome and Death in People Living With Human Immunodeficiency Virus and Severe Lymphopenia

Abstract

Background: Patients living with human immunodeficiency virus (PLWH) with low CD4 counts are at high risk for immune reconstitution inflammatory syndrome (IRIS) and death at antiretroviral therapy (ART) initiation.

Methods: We investigated the clinical impact of IRIS in PLWH and CD4 counts <100 cells/μL starting ART in an international, prospective study in the United States, Thailand, and Kenya. An independent review committee adjudicated IRIS events. We assessed associations between baseline biomarkers, IRIS, immune recovery at week 48, and death by week 48 with Cox models.

Results: We enrolled 506 participants (39.3% were women). Median age was 37 years, and CD4 count was 29 cells/μL. Within 6 months of ART, 97 (19.2%) participants developed IRIS and 31 (6.5%) died. Participants with lower hemoglobin at baseline were at higher IRIS risk (hazard ratio [HR], 1.2; P = .004). IRIS was independently associated with increased risk of death after adjustment for known risk factors (HR, 3.2; P = .031). Being female (P = .004) and having a lower body mass index (BMI; P = .003), higher white blood cell count (P = .005), and higher D-dimer levels (P = .044) were also significantly associated with increased risk of death. Decision-tree analysis identified hemoglobin <8.5 g/dL as predictive of IRIS and C-reactive protein (CRP) >106 μg/mL and BMI <15.6 kg/m2 as predictive of death.

Conclusions: For PLWH with severe immunosuppression initiating ART, baseline low BMI and hemoglobin and high CRP and D-dimer levels may be clinically useful predictors of IRIS and death risk.

Keywords: AIDS; HIV; biomarkers; death; immune reconstitution inflammatory syndrome (IRIS).

Figure 1.

Immune recovery in participants who experienced IRIS compared with participants who did not experience IRIS. CD4 T-cell counts of the surviving participants are displayed for each study time point, with color differentiating those who are still at risk of IRIS (blue) from those who were experiencing or had experienced IRIS (red) at that time point. Lines indicate median values of the 2 groups. Abbreviations: ART, antiretroviral therapy; IRIS, immune reconstitution inflammatory syndrome.

Figure 2.

Results of multivariate Cox regression models with IRIS and death as outcomes. A, HRs with 95% CIs for IRIS before 6 months of antiretroviral therapy (ART). Participants who died or dropped out prior to 6 months were censored at time of death or dropout. B, HRs with 95% CIs for death before 6 months of ART. Participants who dropped out prior to 6 months were excluded from this model. Abbreviations: BMI, body mass index; CI, confidence interval; CRP, C-reactive protein; GLC, glucose; HGB, hemoglobin; HIV, human immunodeficiency virus; IRIS, immune reconstitution inflammatory syndrome; PLT, platelets; WBC, white blood cell count.

Figure 3.

Cumulative incidence of IRIS or death by weeks since ART initiation through week 24. Abbreviations: ART, antiretroviral therapy; IRIS, immune reconstitution inflammatory syndrome.

Figure 4.

Decision tree analysis for predicting immune reconstitution inflammatory syndrome (IRIS). To create the conditional inference decision tree for predicting IRIS, we used 10 baseline biomarkers (body mass index, CD4 and CD8 T-cell counts, human immunodeficiency virus RNA, HGB, white blood cell count, platelets, glucose, D-dimer, and C-reactive protein) and site excluding patients who died without experiencing IRIS, using R the party package (version 3.5). Potential splits are included in the tree model if they met a Bonferroni-adjusted threshold for statistical significance. Ovals indicate a split in the prediction rule on a specific variable, along with the corresponding P value. Each square shows the percentage of observations within that branch that met the decisional criteria (in this case HGB value) followed by the proportion of those patients who experienced IRIS. The darkest shaded square indicates a higher proportion of patients with IRIS. The lightest shade shaded square indicates the lowest proportion of patients with IRIS. Abbreviation: HGB, hemoglobin.

Figure 5.

Decision tree analysis for predicting death. To create the conditional inference tree for predicting death, we used 10 baseline biomarkers (BMI, CD4 and CD8 T-cell counts, human immunodeficiency virus RNA, hemoglobin, white blood cell count, platelets, glucose, D-dimer, and CRP) and site, using the R party package (version 3.5). Potential splits are included in the tree model if they met a Bonferroni-adjusted threshold for statistical significance. Ovals indicate a split in the prediction rule on a specific variable, along with the corresponding P value. Each square shows the percentage of observations within that branch that met the decisional criteria followed by the proportion of those patients who subsequently died. The shading of the squares indicates the proportion of patients who died, with darker shading indicating the highest proportion. Abbreviations: BMI, body mass index; CRP, C-reactive protein.