Skip to main content
. 2019 Aug 20;71(1):53–62. doi: 10.1093/cid/ciz786

Table 4.

Prediction of Infection in the Thai and US Cohorts

A. Model Results for the Thai Cohort B. Model Results for the US Cohort
Model 4 Estimate Odds P Value Model 4 Estimate Odds P Value
Intercept 17.93 0.00 .00 Intercept 25.11 0.00 .00
1-log increase in NFI at previous visit 1.29 3.63 .01 1-log increase in NFI at previous visit 0.76 2.14 .32
1-log increase in NFI at current visit 1.09 2.98 .01 1-log increase in NFI at current visit 2.38 10.85 .01
Model 5 Estimate Odds P Value Model 5 Estimate Odds P Value
Intercept 2.85 0.06 .00 Intercept 38.33 0 .00
Antibiotics at previous visit 2.14 8.54 .00 Antibiotics at previous visit −8.88 0.0001 .00
Model 6 Estimate Odds P Value Model 6 Estimate Odds P Value
Intercept 1.27 0.28 .00 Intercept 1.77 0.17 .00
Cyclophosphamide at previous visit 0.34 0.71 .79 Rituximab at previous visit 1.35 3.84 .04
Cyclophosphamide at current visit 1.27 3.57 .17 Rituximab at current visit 0.60 1.83 .48

The odds of infection based on anti-interferon-γ autoantibody levels (model 1), antibiotic use alone (model 2), and cyclophosphamide or rituximab use (model 3) was assessed using a model that included a term for lagged NFI or treatment (NFI or treatment at a previous visit).

Abbreviation: NFI, neat fluorescence intensity.