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

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.

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.

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.

Hypermobile Ehlers-Danlos syndrome/hypermobility spectrum disorders in older women: A feasibility study

INTRODUCTION

Hypermobile Ehlers-Danlos syndrome and hypermobility spectrum disorders cause joint instability, chronic pain, fatigue and progressive multisystemic dysfunction, increasing symptom burden and decreasing quality of life. Researchers know little about how these disorders progress in women as they age.

OBJECTIVE

This research aimed to determine the feasibility of an internet-based study to understand the clinical characteristics, symptom burden and health-related quality of life in older women with symptomatic hypermobility disorders.

METHODS

This cross-sectional, internet-based survey studied recruitment methods, suitability and usability of survey instruments and obtained baseline data on women aged 50 and older with hEDS/HSD. Researchers recruited participants from a Facebook group for older adults with Ehlers-Danlos syndrome. Outcome measures included health history, the Multidimensional Health Assessment Questionnaire and the RAND Short Form 36 health survey.

RESULTS

Researchers recruited 32 participants from a single Facebook group within 2 weeks. Nearly all participants were satisfied with the survey length, clarity and navigation, with 10 participants providing free-text recommendations for survey improvement. The survey suggests a high symptom burden and poor quality of life in older women with hEDS/HSD.

CONCLUSION

The results support the feasibility and importance of a future internet-based comprehensive study about hEDS/HSD in older women.

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.

Cross-cultural and clinical validation of the MDHAQ/RAPID3 questionnaire in electronic format for a Brazilian population of patients with rheumatoid arthritis

BACKGROUND

Patients with rheumatologic diseases are monitored fundamentally through metric tools or index calculated from clinical data and patient exams, which allow us to assess the severity of the disease and guide the therapeutic decision. In rheumatoid arthritis (RA), for treatment to be optimized and considered effective, periodic assessment with composite disease activity index and a 'treat-to-target' approach is required. The Routine Assessment of Patient Index Data 3 (RAPID3) in the Multidimensional Health Assessment Questionnaire (MDHAQ) includes only three measures based on the central patient self-reported dataset and can be used in a 'treat-to-target' approach analogous to the Clinical Disease Activity Index (CDAI) and the Disease Activity Score 28-joints (DAS28). This tool, however, has not undergone cross-cultural or clinical validation in Brazil. In this research, we performed the MDHAQ cross-cultural and clinical validation for the Brazilian population of RA patients.

METHODS

The Portuguese version of the MDHAQ was created identically in an electronic questionnaire and underwent a cross-cultural validation process with 38 participants. Test-retest was performed in 29 patients. Further, a clinical validation with 129 Rheumatoid Arthritis patients was performed. Electronic MDHAQ was answered through an online platform. We also collected socioeconomic data as well as other clinical (CDAI, SDAI, DAS28) and functional (HAQ) scores during the face-to-face assessment of patients.

RESULTS

MDHAQ/RAPID3 maintained semantic, idiomatic, as well as conceptual and experience equivalence for the Brazilian population, with 92% acceptance of participants. It showed test-retest reliability, adequate internal consistency (Cronbach's α 0.85) and correlation of the scores obtained with adequate association with the DAS28 gold standard. RAPID3 also had high sensitivity (98%), adequate specificity (48%), high negative predictive value (92%) and negative post-test probability of 8%, attributes expected for a test tool for population screening.

CONCLUSION

The use of MDHAQ/RAPID3 associated with traditional clinical measures can adequately allow for remote follow-up based on the 'treat-to-target' approach with performance comparable to the gold standard DAS28, being a viable tool in the sample of Brazilian patients with RA in the current context of telehealth.

A Self-Report Multidimensional Health Assessment Questionnaire (MDHAQ) for Face-To-Face or Telemedicine Encounters to Assess Clinical Severity (RAPID3) and Screen for Fibromyalgia (FAST) and Depression (DEP)

Purpose of Review

To update the clinical value of a patient self-report multidimensional health assessment questionnaire (MDHAQ).

Recent Findings

The MDHAQ includes 10 individual quantitative scores for physical function, pain, patient global assessment, fatigue, sleep, anxiety, depression, morning stiffness, change in status, and exercise status, and 5 indices, RAPID3 (routine assessment of patient index data) to assess clinical status in all diseases studied, FAST3 (fibromyalgia assessment screening tool) and MDHAQ-Dep (depression) to screen for fibromyalgia and/or depression, RADAI self-report of specific painful joints and joint count, and a symptom checklist for review of systems, and recognition of flares and medication adverse events. The MDHAQ also uniquely queries traditional “medical” information concerning comorbidities, falls, trauma, new symptoms, illnesses, surgeries, hospitalizations, emergencies, medication changes, and medication side effects. Three MDHAQ versions include long for new patients, short for new and return patients, and telemedicine. An electronic MDHAQ (eMDHAQ) has been developed with software that can interface with any electronic medical record (EMR) through the HL7 FHIR standard. However, EMR collaboration and implementation have proven difficult.

Summary

An MDHAQ provides a quantitative overview of patient status with far more information and documentation than an interview, involving minimal extra work for the physician.

Fibromyalgia Detection Based on EEG Connectivity Patterns

Objective: The identification of a complementary test to confirm the diagnosis of FM. The diagnosis of fibromyalgia (FM) is based on clinical features, but there is still no consensus, so patients and clinicians might benefit from such a test. Recent findings showed that pain lies in neuronal bases (pain matrices) and, in the long term, chronic pain modifies the activity and dynamics of brain structures. Our hypothesis is that patients with FM present lower levels of brain activity and therefore less connectivity than controls. Methods: We registered the resting state EEG of 23 patients with FM and compared them with 23 control subjects’ resting state recordings from the PhysioBank database. We measured frequency, amplitude, and functional connectivity, and conducted source localization (sLORETA). ROC analysis was performed on the resulting data. Results: We found significant differences in brain bioelectrical activity at rest in all analyzed bands between patients and controls, except for Delta. Subsequent source analysis provided connectivity values that depicted a distinct profile, with high discriminative capacity (between 91.3–100%) between the two groups. Conclusions: Patients with FM show a distinct neurophysiological pattern that fits with the clinical features of the disease.

Chronic Pain Diagnosis Using Machine Learning, Questionnaires, and QST: A Sensitivity Experiment

In the last decade, machine learning has been widely used in different fields, especially because of its capacity to work with complex data. With the support of machine learning techniques, different studies have been using data-driven approaches to better understand some syndromes like mild cognitive impairment, Alzheimer’s disease, schizophrenia, and chronic pain. Chronic pain is a complex disease that can recurrently be misdiagnosed due to its comorbidities with other syndromes with which it shares symptoms. Within that context, several studies have been suggesting different machine learning algorithms to classify or predict chronic pain conditions. Those algorithms were fed with a diversity of data types, from self-report data based on questionnaires to the most advanced brain imaging techniques. In this study, we assessed the sensitivity of different algorithms and datasets classifying chronic pain syndromes. Together with this assessment, we highlighted important methodological steps that should be taken into account when an experiment using machine learning is conducted. The best results were obtained by ensemble-based algorithms and the dataset containing the greatest diversity of information, resulting in area under the receiver operating curve (AUC) values of around 0.85. In addition, the performance of the algorithms is strongly related to the hyper-parameters. Thus, a good strategy for hyper-parameter optimization should be used to extract the most from the algorithm. These findings support the notion that machine learning can be a powerful tool to better understand chronic pain conditions.

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.