Minimal Detectable Changes of the Health Assessment Questionnaire–Disability Index, Patient-Reported Outcomes Measurement Information System-29 Profile Version 2.0 Domains, and Patient Health Questionnaire-8 in People With Systemic Sclerosis: A Scleroderma Patient-Centered Intervention Network Cohort Cross-Sectional Study

Objective: Systemic sclerosis (SSc) is a rare, chronic autoimmune disorder associated with disability, diminished physical function, fatigue, pain, and mental health concerns. We assessed minimal detectable changes (MDCs) of the Health Assessment Questionnaire–Disability Index (HAQ-DI), Patient-Reported Outcomes Measurement Information System-29 Profile version 2.0 (PROMIS-29v2.0) domains, and Patient Health Questionnaire (PHQ)-8 in people with SSc. Methods: Scleroderma Patient-Centered Intervention Network Cohort participants completed the HAQ-DI, PROMIS-29v2.0 domains, and PHQ-8 at baseline assessments from April 2014 until August 2023. We estimated MDC95 (smallest change that can be detected with 95% certainty) and MDC90 (smallest change that can be detected with 90% certainty) with 95% confidence intervals (CIs) generated via the percentile bootstrapping method resampling 1,000 times. We compared MDC estimates by age, sex, and SSc subtype. Results: A total of 2,571 participants were included. Most were female (n = 2,241; 87%), and 38% (n = 976) had diffuse SSc. Mean (±SD) age was 54.9 (±12.7) years and duration since onset of first non-Raynaud phenomenon symptom was 10.8 (±8.7) years. MDC95 estimate was 0.41 points (95% CI 0.40–0.42) for the HAQ-DI, between 4.88 points (95% CI 4.72–5.05) and 9.02 points (95% CI 8.80–9.23) for the seven PROMIS-29v2.0 domains, and 5.16 points (95% CI 5.06–5.26) for the PHQ-8. MDC95 estimates were not materially different across subgroups. Conclusion: MDC95 and MDC90 estimates were precise and similar across age, sex, and SSc subtype groups. HAQ-DI MDC95 and MDC90 were substantially larger than previous estimates of HAQ-DI minimal important difference from several small studies. Minimally important differences of all measures should be evaluated in large studies using anchor-based methods.