OBJECTIVE: Ankylosing spondylitis (AS) diagnosis is often delayed. The availability of effective biologic agents for treating AS has increased the importance of early diagnosis. We tested questions derived from a comprehensive literature review and an advisory board in a case-control study designed to identify patients with AS from among patients with chronic back pain (CBP). METHODS: Question items were cognitively tested among patients with AS, and then in case-control studies for validation and creation of a scoring algorithm and question item reduction. AS cases were recruited from a known database, and CBP subjects (controls) were recruited from clinics, employers, and from the SpineUniverse Web site. We used individual question items in a multivariate framework to discriminate between people with and without AS. RESULTS: Forty-three questions yielded 24 items for analyses; 12 of these were entered into a multivariate regression model. Individual items yielded odds ratios ranging from 0.07 to 30.31. Question items with a significant positive relationship to AS included male sex, neck or hip pain/stiffness, longer pain duration, decreased pain/stiffness with daily physical activity, pain relief within 48 hours of nonsteroidal antiinflammatory drugs, and diagnosis of iritis. The tool demonstrated a sensitivity of 67.4 and a specificity of 94.6. The tool was developed from clinically and radiologically diagnosed AS cases and therefore is designed to distinguish AS cases among CBP subjects. In addition, approximately 54% of the AS cases in the study were treated with biologic agents, which may impact questionnaire responses. CONCLUSION: This tool can identify undiagnosed patients with AS and, potentially, those at an earlier stage in their disease course.
OBJECTIVE:Ankylosing spondylitis (AS) diagnosis is often delayed. The availability of effective biologic agents for treating AS has increased the importance of early diagnosis. We tested questions derived from a comprehensive literature review and an advisory board in a case-control study designed to identify patients with AS from among patients with chronic back pain (CBP). METHODS: Question items were cognitively tested among patients with AS, and then in case-control studies for validation and creation of a scoring algorithm and question item reduction. AS cases were recruited from a known database, and CBP subjects (controls) were recruited from clinics, employers, and from the SpineUniverse Web site. We used individual question items in a multivariate framework to discriminate between people with and without AS. RESULTS: Forty-three questions yielded 24 items for analyses; 12 of these were entered into a multivariate regression model. Individual items yielded odds ratios ranging from 0.07 to 30.31. Question items with a significant positive relationship to AS included male sex, neck or hip pain/stiffness, longer pain duration, decreased pain/stiffness with daily physical activity, pain relief within 48 hours of nonsteroidal antiinflammatory drugs, and diagnosis of iritis. The tool demonstrated a sensitivity of 67.4 and a specificity of 94.6. The tool was developed from clinically and radiologically diagnosed AS cases and therefore is designed to distinguish AS cases among CBP subjects. In addition, approximately 54% of the AS cases in the study were treated with biologic agents, which may impact questionnaire responses. CONCLUSION: This tool can identify undiagnosed patients with AS and, potentially, those at an earlier stage in their disease course.
Authors: Divya Shridharmurthy; Kate L Lapane; Sara Khan; Esther Yi; Jonggyu Baek; Jonathan Kay; Shao-Hsien Liu Journal: PLoS One Date: 2022-07-08 Impact factor: 3.752