Table 2.
Biomarkers | Healthy controls (N=80) | SSc patients (N=80) | Effect size1 | p-values2 | p-values adjusted for FDR3 |
---|---|---|---|---|---|
Positive RF, n (%) | 8 (10%) | 44 (55%) | 12.68 (4.78; 33.61) | <0.0001 | <0.0001 |
β2-microglobulin (mg/L), median (Q1;Q3) | 1.55 (1.34; 1.74) | 2.09 (1.76; 2.64) | 0.61 (0.35; 0.87) | <0.0001 | <0.0001 |
IgA (g/L), median (Q1;Q3) | 1.82 (1.31; 2.45) | 2.03 (1.64; 2.91) | 0.36 (0.05; 0.68) | 0.02 | 0.06 |
IgG (g/L), median (Q1;Q3) | 9.30 (7.96; 10.31) | 9.66 (8.30; 12.04) | 0.55 (0.25; 0.86) | 0.0004 | 0.001 |
IgM (g/L), median (Q1;Q3) | 0.81 (0.61; 1.20) | 1.01 (0.62; 1.57) | 0.12 (-0.17; 0.41) | 0.42 | 0.53 |
BAFF (pg/ml), median (Q1;Q3) | 534 (446; 624) | 620 (478; 864) | 0.02 (-0.28; 0.32) | 0.90 | 0.90 |
APRIL (pg/ml), median (Q1;Q3) | 1911 (1619; 2236) | 1958 (1425; 2313) | 0.03 (-0.28; 0.34) | 0.83 | 0.90 |
sBCMA (pg/ml), median (Q1;Q3) | 37344 (29070; 47014) | 44019 (24470; 59028) | 0.24 (-0.07; 0.55) | 0.13 | 0.23 |
sTACI (pg/ml), median (Q1;Q3) | 3.79 (1.64; 7.18) | 5.05 (1.79; 10.62) | 0.24 (-0.07; 0.55) | 0.14 | 0.90 |
sCD21 (pg/ml), median (Q1;Q3) | 51516 (39990; 64006) | 45520 (30635; 58414) | -0.17 (-0.47; 0.13) | 0.27 | 0.42 |
sCD23 (pg/ml), median (Q1;Q3) | 1952 (1405; 3168) | 1803 (984.8; 3144) | -0.13 (-0.44; 0.18) | 0.40 | 0.53 |
sCD25 (pg/ml), median (Q1;Q3) | 305 (246; 391) | 327.7 (248; 569) | 0.24 (-0.07; 0.55) | 0.13 | 0.23 |
sCD27 (pg/ml), median (Q1;Q3) | 4440 (3615; 5658) | 4906 (4191; 7395) | 0.28 (-0.02; 0.59) | 0.07 | 0.16 |
CXCL13 (pg/ml), median (Q1;Q3) | 36.95 (24.46; 55.77) | 81.73 (46.58; 120.5) | 1.01 (0.69; 1.33) | <0.0001 | <0.0001 |
APRIL, a proliferation-inducing ligand; BAFF, B-cell-activating factor; BCMA, B-cell maturation antigen; CD, cluster of differentiation; CXCL13, C-X-C motif chemokine 13; FDR, false discovery rate; Ig, immunoglobulin; Q, quartile; RF, rheumatoid factor; s, soluble; SSc, systemic sclerosis; TACI, transmembrane activator and CAML interactor.
Results are expressed as median (first quartile; third quartile) for quantitative biomarkers and as frequency (percentage) otherwise.
All analyses were adjusted for age and gender.
1 For quantitative biomarkers, effect sizes were calculated on log transformed variables using the Cohen d. Absolute values of 0.20–0.49 represent a small change; values of 0.50–0.79 a medium change; and values of ≥ 0.80 a large change. For the binary biomarker, effect size is the odds ratio of the status for the risk of positive RF with the status control as reference value.
2 p-values calculated on log-transformed variables for quantitative biomarkers.
3 p-values corrected for multiplicity using the False Discovery Rate (FDR) method (Benjamini Hochberg procedure).