Figure 1.
Flowchart of the study selection.
Table 1.
Data extracted from the included studies.
Table 2.
The results of an assessment for bias in accordance with Hayden's criteria.
Figure 2.
Forest graphs of the meta-analysis of RF status and response to anti-TNFα agents.
The overall analysis of RF status showed a pooled RR of 0.98 (95% CI: 0.91–1.05, p = 0.54) and an I2 of 43%. Subgroup analyses on different response criteria revealed no significant differences.
Table 3.
Subgroup meta-analysis of RF and RA patient response according to different anti-TNFα agents, follow-up periods, response criteria, and ethnic groups.
Figure 3.
Forest graphs of the meta-analysis of anti-CCP antibody status and response to anti-TNFα agents.
The overall analysis of anti-CCP antibody status showed a pooled RR of 0.88 (95% CI: 0.76–1.03, p = 0.11) and an I2 of 67%. Subgroup analyses on different response criteria revealed no significant differences.
Table 4.
Subgroup meta-analysis of anti-CCP and RA patient response according to different anti-TNFα agents, follow-up periods, response criteria, and ethnic groups.
Figure 4.
Overall analysis of publication bias on the effect of RF status on the response to anti-TNFα treatment.
Egger's linear regression test was performed to quantify publication bias. The p values of the RF status analysis were 0.777. The funnel plot showed no significant evidence of asymmetry.
Figure 5.
Overall analysis of publication bias on the effect of anti-CCP antibody status on the response to anti-TNFα treatment.
Egger's linear regression test was performed to quantify publication bias. The p values of the anti-CCP antibody status analysis were 0.422. The funnel plot showed no significant evidence of asymmetry.