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. 2015 Oct 27;10(10):e0141394. doi: 10.1371/journal.pone.0141394

Table 4. Net Reclassification Improvement and Integrated Discrimination Improvement by Adding Optimized Thresholds of the CXCR3 Ligands to the Basic Models.

Variables in basic models biomarkers Integrated discrimination improvement Net reclassification improvement
Δ% (95% confidence interval) p Δ% (95% confidence interval) p
NT-pro BNP
    MIG 12.9 (4.01 to 21.8) 0.004 89.7 (45.9 to 133.4) <0.0001
    IP10 7.51 (1.55 to 13.5) 0.014 69.0 (20.7 to 117.3) 0.005
    I–TAC 17.8 (7.67 to 28.0) 0.006 84.3 (36.5 to 132.0) 0.0005
    MIG + IP10 + I–TAC 22.8 (10.4 to 35.2) 0.0003 124.2 (82.0 to 166.6) <0.0001
NT-pro BNP, age and body mass index
    MIG 5.45 (0.29 to 10.6) 0.038 110.3 (68.3 to 152.4) <0.0001
    IP10 0.63 (–0.90 to 2.16) 0.42 69.0 (20.7 to 117.3) 0.005
    I–TAC 9.64 (1.33 to 18.0) 0.023 154.6 (120.3 to 188.8) <0.0001
    MIG + IP10 + I–TAC 18.8 (9.62 to 28.0) <0.0001 192.9 (179.1 to 206.6) <0.0001

Abbreviations of the biomarkers are spelled out in Table 2. The net reclassification improvement is the sum of the percentages of subjects reclassified correctly in cases and controls. The integrated discrimination improvement is the difference between the discrimination slopes of the extended and basic models. The discrimination slope is the difference in predicted probabilities between cases and controls. Cases were patients with subclinical or symptomatic diastolic left ventricular dysfunction. Controls were healthy people.