Table 2

Prediction of disease severity using standard multiple regression: contribution of serological and histological parameters

Prediction modelAnti-SSAAnti-SSBLFS ≥3IgA+ plasma cell ≤40%IgM+ plasma cell ≥25%
βββββ
NHL8%0.030
p=0.799
0.028
p=0.243
0.244*
p=0.017
0.037
p=0.742
0.112
p=0.278
Cumulative ESSDAI19%0.114
p=0.304
0.143
p=0.194
0.221*
p=0.021
0.080
p=0.451
0.163
p=0.092
Total EGM score20%0.135
p=0.221
0.230*
p=0.037
0.183
p=0.054
0.016
p=0.883
0.177
p=0.067
Cumulative ESSDAI –NHL related22%0.074
p=0.494
0.314*
p=0.004
0.072
p=0.437
0.104
p=0.314
0.137
p=0.148
Total EGM score –NHL related24%0.096
p=0.369
0.366*
p=0.001
0.103
p=0.262
0.022
p=0.832
0.165
p=0.078
  • ‘Prediction model’ in the left column represents the percentage of variance in the clinical score or NHL prevalence that is explained by the whole model (based on R square). In the other five columns at the right the β and p values are stated per parameter included in the standard multiple regression model.

  • *Statistically significantly p values.

  • Anti-SSA, anti-Sjögren syndrome A antibodies; anti-SSB, anti-Sjögren syndrome B antibodies; EGM, extra-glandular manifestations; ESSDAI, EULAR Sjögren syndrome disease activity index; EULAR, European League against Rheumatism; LFS, lymphocytic focus score; NHL, non-Hodgkin lymphoma; –NHL related, not counting NHL and manifestations during its course.