Physician estimate of inflammation vs global assessment in explaining variations in swollen joint counts in rheumatoid arthritis patients.

Objective: To analyse patients with RA for inflammatory activity by physician estimate of global assessment (DOCGL) vs an estimate of inflammatory activity (DOCINF) to explain variation in the swollen joint count (SJC). Methods: Patients with RA were studied at routine care visits. Patients completed a multidimensional health assessment questionnaire (MDHAQ) and the physician completed a 28-joint count for swollen (SJC), tender (TJC) and deformed (DJC) joints and a RheuMetric checklist with a 0-10 DOCGL visual numeric scale (VNS) and 0-10 VNS estimates of inflammation (DOCINF), damage (DOCDAM) and patient distress (DOCSTR). The disease activity score in 28 joints with ESR (DAS28-ESR), Clinical Disease Activity Index (CDAI) and Routine Assessment of Patient Index Data 3 (RAPID3) were calculated. Individual scores and RA indices were compared according to Spearman correlation coefficients and regression analyses. Results: A total of 104 unselected patients were included, with a median age and disease duration of 54.5 and 5 years, respectively. The median DAS28-ESR was 2.9 (Q1-Q3: 2.0-3.7), indicating low activity. DOCINF was correlated significantly with DOCGL (ρ = 0.775). Both DOCGL and DOCINF were correlated significantly with most other measures; correlations with DOCGL were generally higher than with DOCINF other than for SJC. In regression analyses, DOCINF was more explanatory of variation in SJC than DOCGL and other DAS28-ESR components. Conclusions: Variation in SJC is explained more by a 0-10 DOCINF VNS than the traditional DOCGL or any other measure in RA patients seen in routine care. DOCINF on a RheuMetric checklist can provide informative quantitative scores concerning inflammatory activity in RA patients monitored over long periods.

Elevated DAS28-ESR in patients with rheumatoid arthritis who have comorbid fibromyalgia is associated more with tender joint counts than with patient global assessment or swollen joint counts: implications for assessment of inflammatory activity.

OBJECTIVES: More than 20% of rheumatoid arthritis (RA) patients have comorbid fibromyalgia (FM+), which may elevate DAS28-ESR (disease activity score 28-erythrocyte sedimentation rate) and other indices, resulting in challenges to assess inflammatory disease activity. Although several reports indicate that elevated patient global assessment (PATGL) may elevate DAS28 in the absence of inflammatory activity, less information is available concerning the other three components, tender joint count (TJC), swollen joint count (SJC), and erythrocyte sedimentation rate (ESR), to possibly elevate DAS28 in FM+ vs. FM- RA patients. METHODS: A PubMed search identified 14 reports which presented comparisons of DAS28-ESR and its four components in RA FM+ vs. FM- groups. Median DAS28, component arithmetic differences, pooled effect sizes and 95% confidence intervals were analysed in the FM+ vs. FM- groups. RESULTS: In FM+ vs. FM- groups, median DAS28 was 5.3 vs. 4.2, SJC 4.0 vs. 3.0, TJC 13.2 vs. 5.3, PATGL 61.6 vs. 39.9, ESR 26.3 vs. 26.5. DAS28-ESR was classified as "high" (>5.1) in 11/14 FM+ groups and "moderate" (3.2-5.1) in all 14 FM- groups. Effect sizes in FM+ vs. FM- groups for DAS28-ESR, SJC, TJC, PATGL, and ESR were large (≥0.8) in 10/14, 1/13, 12/13, 7/13, and 1/13 comparisons, respectively, and pooled effect sizes 0.84 (0.3, 1.4), 0.33 (-0.4, 1.0), 1.27 (0.01, 2.5), 0.91 (-0.6, 2.4), and 0.07 (-0.6, 0.7), respectively. CONCLUSIONS: DAS28-ESR is elevated significantly in FM+ vs. FM- RA patients; pooled effect sizes were highest for TJC, followed by PATGL, SJC and ESR. The findings appear relevant to response and remission criteria, treat-to-target, and general management of RA.

PROMIS-29 in rheumatoid arthritis patients who screen positive or negative for fibromyalgia on MDHAQ FAST4 (fibromyalgia assessment screening tool) or 2011 fibromyalgia criteria.

BACKGROUND: PROMIS-29 T-scores query health-related quality of life (HRQL) in 7 domains, physical function, pain, fatigue, anxiety, depression, sleep quality, and social participation, to establish population norms. An MDHAQ (multidimensional health assessment questionnaire) scores these 7 domains and includes medical information such as a FAST4 (fibromyalgia assessment screening tool) index. We analyzed PROMIS-29 T-scores in rheumatoid arthritis (RA) patients vs population norms and for positive vs negative fibromyalgia (FM) screens and compared PROMIS-29 T-scores to MDHAQ scores to assess HRQL. METHODS: A cross-sectional study was performed at one routine visit of 213 RA patients, who completed MDHAQ, PROMIS-29, and reference 2011 FM Criteria. PROMIS-29 T-scores were compared in RA vs population norms and in FM+ vs FM- RA patients, based on MDHAQ/FAST4 and reference criteria. Possible associations between PROMIS-29 T-scores and corresponding MDHAQ scores were analyzed using Spearman correlations and multiple regressions. RESULTS: Median PROMIS-29 T-scores indicated clinically and statistically significantly poorer status in 26-29% FM+ vs FM- RA patients, with larger differences than in RA patients vs population norms for 6/7 domains. MDHAQ scores were correlated significantly with each of 7 corresponding PROMIS-29 domains (|rho|≥0.62, p<0.001). Linear regressions explained 55-73% of PROMIS-29 T-score variation by MDHAQ scores and 56%-70% of MDHAQ score variation by PROMIS-29 T-scores. CONCLUSIONS: Scores for 7 PROMIS-29 domains and MDHAQ were highly correlated. The MDHAQ is effective to assess HRQL and offers incremental medical information, including FAST4 screening. The results indicate the importance of assessing comorbidities such as fibromyalgia screening in interpreting PROMIS-29 T-scores.

RheuMetric Quantitative 0 to 10 Physician Estimates of Inflammation, Damage, and Distress in Rheumatoid Arthritis: Validation Against Reference Measures.

OBJECTIVE: To analyze a RheuMetric checklist, which includes four feasible physician 0 to 10 scores for DOCGL, inflammation (DOCINF), damage (DOCDAM), and distress (DOCSTR) for criterion and discriminant validity against standard reference measures. METHODS: A prospective, cross-sectional assessment was performed at one routine care visit at Liverpool Hospital, Sydney, Australia. Rheumatologists recorded DOCGL, DOCINF, DOCDAM, DOCSTR, and 28 joint counts for swelling (SJC), tenderness (TJC), and limited motion/deformity (DJC). Patients completed a multidimensional health assessment questionnaire (MDHAQ), which includes routine assessment of patient index data (RAPID3), fibromyalgia assessment screening tool (FAST4), and MDHAQ depression screen (MDS2). Laboratory tests and radiographic scores were recorded. RheuMetric estimates of inflammation, damage, and distress were compared with reference and other measures using correlations and linear regressions. RESULTS: In 173 patients with RA, variation in RheuMetric DOCINF was explained significantly by SJC and inversely by disease duration; variation in DOCDAM was explained significantly by DJC, radiographic scores, and physical function; and variation in DOCSTR was explained significantly by fibromyalgia and depression. CONCLUSION: RheuMetric DOCINF, DOCDAM, and DOCSTR estimates were correlated significantly and specifically with reference measures of inflammation, damage, and distress, documenting criterion and discriminant validity.

Patient global assessment is elevated by up to 5 of 10 units in patients with inflammatory arthritis who screen positive for fibromyalgia (by FAST4) and/or depression (by MDS2) on a single MDHAQ.

BACKGROUND: Patient global assessment (PATGL) is a component of rheumatoid arthritis (RA) and spondyloarthritis (SpA) activity indices, reflecting inflammation in selected clinical trial patients. In routine care, PATGL often may be elevated independently of inflammatory activity by fibromyalgia (FM) and/or depression, leading to complexities in interpretation. A feasible method to screen for FM and/or depression could help to clarify interpretation of high PATGL and index scores, including explanation of apparent limited responses to anti-inflammatory therapies. PATIENTS AND METHODS: Patients with RA or SpA in routine care in Barcelona, Chicago, and Sydney complete a 2-page multidimensional health assessment questionnaire (MDHAQ) in 5-10 min. The MDHAQ includes PATGL and three indices, RAPID3 (routine assessment of patient index data) to assess clinical status, FAST4 (0-4 fibromyalgia assessment screening tool) and MDS2 (0-2 MDHAQ depression screen). PATGL was compared for each diagnosis at each site and pooled data in FAST4 positive (+) vs negative (-) and/or MDS2+ vs MDS2- patients using medians and median regressions. RESULTS: Median PATGL was 5.0 in 393 RA and 175 SpA patients; 2.0-3.0 in 305 (58.9%) FAST4-,MDS2- patients, 5.5-6.0 in 71 (13.7%) FAST4-,MDS2+ patients, 7.0-7.5 in 50 (9.7%) FAST4+,MDS2- patients, and 7.0-8.0 in 92 (17.8%) FAST4+,MDS2+ patients. Positive FAST4 and/or MDS2 screens were seen in 41% of patients. Results were similar in RA and SpA at 3 settings on 3 continents. CONCLUSION: Median 0-10 PATGL varied from 2-3/10 to 5.5-8/10, according to negative vs positive screening for FM and/or depression on a single MDHAQ for busy clinical settings.

Satisfaction With a Virtual Learning Collaborative Aimed at Implementing Treat-to-Target in Rheumatoid Arthritis.

OBJECTIVE: Limited information is available concerning experiences of participants in a virtual learning collaborative (LC), and little qualitative data or participant feedback on how this format can be improved. One prior in-person LC in rheumatology successfully improved adherence with treat-to-target (TTT) for RA. We conducted a virtual LC on TTT and herein report on participant satisfaction. METHODS: We conducted a virtual LC with 18 rheumatology practices from across the United States during 2020 to 2021. The LC included a virtual kickoff meeting and monthly videoconferences, accompanied by data submission and feedback. At the conclusion of the LC, we surveyed the 45 LC participants concerning individual experience and satisfaction. RESULTS: All sites and 78% of participants responded to the surveys. The LC included small and large practices, 14 academic and 4 nonacademic, and respondents ranged in their roles: 24 physicians, 5 nurses or nurse practitioners, 3 administrators, and 3 other roles. Overall, 94% of respondents indicated they were either somewhat or very satisfied with the LC, and 94% said they would recommend a similar LC to a colleague. Aspects of the LC described as "very useful" included a kickoff meeting, intersite discussion, and monthly speakers; however, digital tools such as the Web site and meeting recordings were not found useful. CONCLUSIONS: Virtual LCs are feasible, and participants reported strong satisfaction. Virtual LCs were highly valued by rheumatologists, trainees, and their practice staffs. Potential topics were identified for future LCs that could improve the quality of care delivered to rheumatology patients.

Implementing a Treat-to-Target Approach for Rheumatoid Arthritis During the COVID-19 Pandemic: Results of a Virtual Learning Collaborative Program.

OBJECTIVE: A treat-to-target (TTT) approach improves outcomes in rheumatoid arthritis (RA). In prior work, we found that a learning collaborative (LC) program improved implementation of TTT. We conducted a shorter virtual LC to assess the feasibility and effectiveness of this model for quality improvement and to assess TTT during virtual visits. METHODS: We tested a 6-month virtual LC in ambulatory care. The LC was conducted during the 2020-2021 COVID-19 pandemic when many patient visits were conducted virtually. All LC meetings used videoconferencing and a website to share data. The LC comprised a 6-hour kickoff session and 6 monthly webinars. The LC discussed TTT in RA, its rationale, and rapid cycle improvement as a method for implementing TTT. Practices provided de-identified patient visit data. Monthly webinars reinforced topics and demonstrated data on TTT adherence. This was measured as the percentage of TTT processes completed. We compared TTT adherence between in-person visits versus virtual visits. RESULTS: Eighteen sites participated in the LC, representing 45 rheumatology clinicians. Sites inputted data on 1,826 patient visits, 78% of which were conducted in-person and 22% of which were held in a virtual setting. Adherence with TTT improved from a mean of 51% at baseline to 84% at month 6 (P for trend < 0.001). Each aspect of TTT also improved. Adherence with TTT during virtual visits was lower (65%) than during in-person visits (79%) (P < 0.0001). CONCLUSION: Implementation of TTT for RA can be improved through a relatively low-cost virtual LC. This improvement in TTT implementation was observed despite the COVID-19 pandemic, but we did observe differences in TTT adherence between in-person visits and virtual visits.

Multidimensional Health Assessment Questionnaire as an Effective Tool to Screen for Depression in Routine Rheumatology Care.

OBJECTIVE: To analyze the use of the Multidimensional Health Assessment Questionnaire (MDHAQ) to screen for depression, as compared to 2 reference standards, the Patient Health Questionnaire 9 (PHQ-9) and the Hospital Anxiety and Depression Scale depression domain (HADS-D). METHODS: Patients from Barcelona with a primary diagnosis of rheumatoid arthritis (RA) or spondyloarthritis (SpA) completed the MDHAQ, the PHQ-9 (depression ≥10), and the HADS-D (depression ≥8) measures. The MDHAQ includes 2 depression items, 1 in the patient-friendly HAQ, scored in a 4-point format from 0 to 3.3, and a yes/no item on a 60-symptom checklist. Percentage agreement and kappa statistics quantified the agreement between 6 screening criteria: yes on the 60-symptom checklist, a score of ≥1.1, a score of ≥2.2 on a 4-point scale, and either a response of yes on the 60-symptom checklist or scores of ≥2.2, PHQ-9 ≥10, and HADS-D ≥8. RESULTS: Depression screening was positive according to 6 criteria in 19.6-32.4% of 102 patients with RA, and 27.9-44.8% of 68 with SpA (total = 170). All MDHAQ scores, including depression items, were higher in patients with SpA compared to patients with RA, and within each diagnostic group in patients who met PHQ-9 ≥10 and HADS-D ≥8 depression screening criteria. The highest percentage agreement between an MDHAQ screening criterion versus PHQ-9 ≥10 was 83.3% for either an answer of yes on the 60-symptom checklist or a score of ≥2.2 on a 4-point scale, which we have termed MDHAQ-Dep. The agreement of MDHAQ-Dep versus HADS-D ≥8 was 81.7%, similar to the agreement of PHQ-9 ≥10 versus HADS-D ≥8, which was 82.2%. Kappa measures of agreement were 0.63 for MDHAQ-Dep versus PHQ-9 ≥10, 0.60 for MDHAQ-Dep versus HADS-D ≥8, and 0.62 for PHQ-9 ≥10 versus HADS-D ≥8. CONCLUSION: A positive MDHAQ-Dep response (either an answer of yes on a 60-symptom checklist or a score of ≥2.2 on a 4-point scale) yielded similar results to PHQ-9 ≥10 or HADS-D ≥8 to screen for depression in these RA and SpA patients.

Reliability, Feasibility, and Patient Acceptance of an Electronic Version of a Multidimensional Health Assessment Questionnaire for Routine Rheumatology Care: Validation and Patient Preference Study.

BACKGROUND: A multidimensional health assessment questionnaire (MDHAQ) that was developed primarily for routine rheumatology care has advanced clinical research concerning disease burden, disability, and mortality in rheumatic diseases. Routine Assessment of Patient Index Data 3 (RAPID3), an index within the MDHAQ, is the most widely used index to assess rheumatoid arthritis (RA) in clinical care in the United States, and it recognizes clinical status changes in all studied rheumatic diseases. MDHAQ physical function scores are far more significant in the prognosis of premature RA mortality than laboratory or imaging data. However, electronic medical records (EMRs) generally do not include patient questionnaires. An electronic MDHAQ (eMDHAQ), linked by fast healthcare interoperability resources (FIHR) to an EMR, can facilitate clinical and research advances. OBJECTIVE: This study analyzed the reliability, feasibility, and patient acceptance of an eMDHAQ. METHODS: Since 2006, all Rush University Medical Center rheumatology patients with all diagnoses have been asked to complete a paper MDHAQ at each routine care encounter. In April 2019, patients were invited to complete an eMDHAQ at the conclusion of the encounter. Analyses were conducted to determine the reliability of eMDHAQ versus paper MDHAQ scores, arithmetically and by intraclass correlation coefficient (ICC). The feasibility of the eMDHAQ was analyzed based on the time for patient completion. The patient preference for the electronic or paper version was analyzed through a patient paper questionnaire. RESULTS: The 98 study patients were a typical routine rheumatology patient group. Seven paper versus eMDHAQ scores were within 2%, differences neither clinically nor statistically significant. ICCs of 0.86-0.98 also indicated good to excellent reliability. Mean eMDHAQ completion time was a feasible 8.2 minutes. The eMDHAQ was preferred by 72% of patients; preferences were similar according to age and educational level. CONCLUSIONS: The results on a paper MDHAQ versus eMDHAQ were similar. Most patients preferred an eMDHAQ.

Fibromyalgia Assessment Screening Tool: Clues to Fibromyalgia on a Multidimensional Health Assessment Questionnaire for Routine Care.

OBJECTIVE: To develop feasible indices as clues to comorbid fibromyalgia (FM) in routine care of patients with various rheumatic diseases based only on self-report multidimensional Health Assessment Questionnaire (MDHAQ) scores, which are informative in all rheumatic diagnoses studied. METHODS: All patients with all diagnoses complete an MDHAQ at each visit; the 2011 FM criteria questionnaire was added to the standard MDHAQ between February 2013 and August 2016. The proportion of patients who met 2011 FM criteria or had a clinical diagnosis of FM was calculated. Individual candidate MDHAQ measures were compared to 2011 FM criteria using receiver-operating characteristic (ROC) curves; cutpoints to recognize FM were selected from the area under the curve (AUC) for optimal tradeoff between sensitivity and specificity. Cumulative indices of 3 or 4 MDHAQ measures were analyzed as fibromyalgia assessment screening tools (FAST). RESULTS: In 148 patients, the highest AUC in ROC analyses versus 2011 FM criteria were seen for MDHAQ symptom checklist, self-report painful joint count, pain visual analog scale (VAS), and fatigue VAS. The optimal cutpoints were ≥ 16/60 for symptom checklist, ≥ 16/48 for self-report painful joint count, and ≥ 6/10 for both pain and fatigue VAS. Cumulative FAST indices of 2/3 or 3/4 MDHAQ measures correctly classified 89.4-91.7% of patients who met 2011 FM criteria. CONCLUSION: FAST3 and FAST4 cumulative indices from only MDHAQ scores correctly identify most patients who meet 2011 FM criteria. FAST indices can assist clinicians in routine care as clues to FM with a general rheumatology rather than FM-specific questionnaire.

Fibromyalgia Assessment Screening Tools (FAST) Based on Only Multidimensional Health Assessment Questionnaire (MDHAQ) Scores as Clues to Fibromyalgia.

OBJECTIVE: The study was designed to develop fibromyalgia assessment screening tool (FAST) indices based only on multidimensional health assessment questionnaire (MDHAQ) scores as clues to fibromyalgia (FM), analyzed for possible agreement with the 2011 FM criteria. METHODS: All patients with all diagnoses complete an MDHAQ at each visit in routine care. The MDHAQ includes scores for physical function, pain, global assessment, fatigue, self-report painful joint count, and a 60-symptom checklist. MDHAQ items similar or identical to the 2011 FM criteria symptom severity scale (SSS) and widespread pain index (WPI) components of a polysymptomatic distress scale (PSD) were compiled into continuous MDHAQ-FM-SSS, MDHAQ-FM-WPI, and MDHAQ-FM-PSD indices. Ten candidate MDHAQ scores were analyzed against the 2011 FM criteria using descriptive statistics, Spearman correlations, kappa statistics, and receiver operating characteristic curves for the area under the curve (AUC). MDHAQ candidate variables with the highest AUC were compiled into cumulative MDHAQ-FAST indices of three (FAST3) or four (FAST4) scores. RESULTS: The highest AUCs among MDHAQ scores were seen for symptom checklist, painful joint count, fatigue, and pain, which are included in FAST4; FAST3-F excludes pain, and FAST3-P excludes fatigue. AUCs for FAST3-P, FAST3-F, and FAST4, as well as continuous MDHAQ-FM scores, all were greater than 0.92, indicating excellent criterion validity. Kappa statistics versus the 2011 criteria were 0.63-0.68, higher than 0.41-0.47 versus physician ICD-10 diagnoses. CONCLUSION: Pragmatic FAST3, FAST4, and MDHAQ-FM indices are similar to FM criteria to screen for FM in routine care. It is more feasible to collect the same MDHAQ, which is informative in all rheumatic diseases studied, from each patient than to ask different patients with different diagnoses to complete different questionnaires.

Low socioeconomic status and patient questionnaires in osteoarthritis: challenges to a "biomedical model" and value of a complementary "biopsychosocial model".

Modern medical care is based largely on a paradigm known as a "biomedical model," in which "objective," high-technology biomarkers guide clinical care, and most health outcomes are determined by health professionals rather than individuals, using drugs as the primary therapy. The biomedical model is spectacularly effective in the acute care inpatient hospital, the setting for 95% of medical education and training, and to guide management of many chronic diseases, such as hypertension and diabetes, for which a "gold standard" biomarker is a major determinant of clinical decisions. This model also has contributed importantly to knowledge of biomarkers, biochemical and structural abnormalities in osteoarthritis (OA) and other rheumatic diseases. However, a biomedical model has many limitations in understanding the long-term course of OA and many chronic diseases in outpatient medicine, the setting of 95% of activities that determine long-term health outcomes. Patient self-report questionnaires provide the most informative data concerning OA patient status and changes in status, and more significant data in the prognosis of outcomes such as mortality than laboratory or radiographic measures. Furthermore, the incidence, prevalence, morbidity, and mortality of OA is considerably greater in individuals of low versus high socioeconomic status. These associations are not unique to OA, and are seen in many diseases, including comorbid conditions which are the acute causes of death in OA. Associations of low socioeconomic and poor health are explained only in small part by limited access to medical services, the conventional explanation. Strong evidence suggests that socioeconomic status is a surrogate marker for patient self-management, actions and environment, in addition to actions of health professionals, in the pathogenesis, course and outcomes of chronic diseases. These observations suggest the value of a complementary "biopsychosocial model" to better understand pathogenesis, principles of treatments, and outcomes in OA and other chronic diseases. Inclusion of clinical information from patient questionnaires and socioeconomic status variables in clinical and research settings could add new understanding of biomarkers and pain in OA for both basic and clinical investigators. Furthermore, the data indicate that poor physical function assessed on a self-report questionnaire might be regarded as an important reversible risk factor in public health and research agendas, for which the OA community might be strong advocates.