Author, year | Country | Study Design | Settinga/Data source | Sample Size | Age, mean (SD) | Gender (% males) | AS assessment | Quality assessment score |
---|---|---|---|---|---|---|---|---|
Wu, 2017 [19] | United States | cohort study | administrative health database | AS: 1878 | AS: 52 (16) | AS: 70% | ICD-9 | 7 |
No AS: 156093 | No AS: 54 (16) | No AS: 49% | ||||||
Shen, 2016 [20] | Taiwan | cohort study | administrative health database | AS: 2331 | AS: 36.5 | AS: 65% | A-code, ICD-9 | 8 |
No AS: 9324 | No AS: 36.5 | No AS: 65% | ||||||
Zou, 2016 [21] | China | cross-sectional (no comparator) | outpatient | AS: 40 | AS: 31.5 (10.1) | AS: 70% | ASAS criteria | 6 |
Kilic, 2014 [22] | Turkey | cross-sectional (w comparator) | outpatient | AS: 174 | AS: 38.3 | not reported | ASAS criteria | 6 |
Nr-axSpA: 142 | Nr-axSpA: 33.9 | |||||||
Meesters, 2014 [23] | Sweden | cohort study | administrative health database | AS: 1738 | AS: 54.5 (14.3) | AS: 64% | ICD-10 | 8 |
No AS: 967012 | No AS: not reported | No AS: 48% | ||||||
Sundquist, 2008 [24] | Sweden | cohort study | administrative health database | AS: 5253 | Men: 43 | AS: 71% | ICD 8–10 | 8 |
Women: 43 |