Table 2.
Linear regression models showed unadjusted and adjusted association between RANKL concentration and ACPA
Least square mean of RANKL pmol/L | Coefficient | p value | R2 | ||
---|---|---|---|---|---|
(95% CI) | (adj R2) | ||||
ACPA- | ACPA- | ||||
positive | negative | ||||
Model A. (n = 59) | 290 | 130 | 0.21 | ||
(201–417) | (106–160) | (0.19) | |||
ACPA | 0.35 | <0.001 | |||
(positive vs. negative) | |||||
Intercept | 2.12 | ||||
Model B. (n = 59) | 232 | 140 | 0.36 | ||
(155–346) | (114–171) | (0.31) | |||
ACPA | 0.22 | 0.04 | |||
(positive vs. negative) | |||||
Age | -0.005 | 0.17 | |||
(per 1-year increase) | |||||
DAS28-ESR | 0.07 | 0.06 | |||
BMI | -0.02 | 0.04 | |||
Intercept | 2.53 |
R2: proportion of variance explained by the variables in the statistical model
adj R2: adjusted R2, similar to R2 but takes into account the number of variables in the model
RANKL receptor activator of nuclear factor kappa B ligand, ACPA anti-citrullinated protein antibodies, DAS28 disease activity score 28, ESR erythrocyte sedimentation rate, BMI body mass index