The measurement of pain behavior is a key component of the assessment of persons with chronic pain; however few self-reported pain behavior instruments have been developed. We developed a pain behavior item bank as part of the Patient Reported Outcome Measurement Information System (PROMIS). For the Wave I testing, because of the large number of PROMIS items, a complex sampling approach was used where participants were randomly assigned to either respond to two full item banks or to multiple 7-item blocks of items. A web-based survey was designed and completed by 15,528 members of the general population and 967 individuals with different types of chronic pain. Item response theory (IRT) analysis models were used to evaluate item characteristics and to scale both items and individuals on the pain behavior domain. The pain behavior item bank demonstrated good fit to a unidimensional model (Comparative Fit Index = 0.94). Several iterations of IRT analyses resulted in a final 39 item pain behavior bank, and different IRT models were fit to the total sample and to those participants who experienced some pain. The results indicated that these items demonstrated good coverage of the pain behavior construct. Pain behavior scores were strongly related to pain intensity and moderately related to self-reported general health status. Mean pain behavior scores varied significantly by groups based on pain severity and general health status. The PROMIS pain behavior item bank can be used to develop static short-form and dynamic measures of pain behavior for clinical studies.

Background Preference-based health index scores provide a single summary score assessing overall healthrelated quality of life and are useful as an outcome measure in clinical studies, for estimating quality-adjusted life years for economic evaluations, and for monitoring the health of populations. We predicted EuroQoL (EQ-5D) index scores from patient-reported outcomes measurement information system (PROMIS) global items and domain item banks. Methods This was a secondary analysis of health outcome data collected in an internet survey as part of the PROMIS Wave 1 field testing. For this study, we included the 10 global items and the physical function, fatigue, pain impact, anxiety, and depression item banks. Linear regression analyses were used to predict EQ-5D index scores based on the global items and selected domain banks. Results The regression models using eight of the PRO-MIS global items (quality of life, physical activities, mental health, emotional problems, social activities, pain, and fatigue and either general health or physical health items) explained 65% of the variance in the EQ-5D. When the PROMIS domain scores were included in a regression model, 57% of the variance was explained in EQ-5D scores. Comparisons of predicted to actual EQ-5D scores by age and gender groups showed that they were similar. Conclusions EQ-5D preference scores can be predicted accurately from either the PROMIS global items or selected domain banks. Application of the derived regression model allows the estimation of health preference scores from the PROMIS health measures for use in economic evaluations.

Background: Health-related quality of life (HRQOL) outcomes are associated with clinical response to treatment in psoriasis. However, the association between HRQOL outcomes and more substantial degrees of Psoriasis Area and Severity Index (PASI) response and physician and patient global ratings remains ill defined. Objective: This study examined the relationship between achieving a 75% or ≧90% improvement in PASI and HRQOL outcome measures. Methods: Secondary analyses were completed using data for 1,469 patients with moderate to severe plaque psoriasis from two adalimumab clinical trials. HRQOL was measured via the Dermatology Life Quality Index (DLQI) and the Short Form 36 (SF 36) Health Survey. Clinical response was assessed by the PASI, physician’s global assessment and patient’s global assessment status scores. Clinical response was categorized into 6 groups based on PASI response: <25% (n = 332); 25 to <50% (n = 137); 50 to <75% (n = 170); 75 to <90% (n = 288); 90 to <100% (n = 255), and 100% (n = 192). Analysis of covariance models compared baseline measures and 16-week changes in HRQOL scores. Results: Statistically significant differences were observed between PASI response groups in DLQI total scores and in SF 36 summary and scale scores (p < 0.0001). The PASI 100 and PASI 90 to <100 groups demonstrated a >10-point decrease in DLQI total scores. Moreover, these changes were statistically significantly greater than those observed for the PASI 75 to <90 group (p < 0.001) and the other PASI response groups (p < 0.001). For the SF 36, the greatest changes were observed in the PASI 75 to <90, PASI 90 to <100 and PASI 100 groups, which all had improvements of >4 points in the Mental Component and Physical Component Summary (MCS and PCS) scores. Statistically significantly greater differences in DLQI total and SF 36 summary and scale scores were also observed between patient’s global assessment categories (p < 0.0001) and between physician’s global assessment categories (p < 0.0001). Conclusion: Improvement in PASI response of >75% corresponded to improvements in HRQOL outcome measures for patients with moderate to severe psoriasis. PASI 90 or 100 responders had greater improvements in DLQI total score than PASI 75 responders.

The NEI VFQ-25 demonstrated good reliability and construct validity as a measure of vision-related functioning outcomes in patients with AMD.

Introduction We evaluated the three-year impact of adalimumab on patient-reported physical function and healthrelated quality-of-life (HRQOL) outcomes in patients with active ankylosing spondylitis (AS).