A parallel group cohort to determine the measurement properties of an early inflammatory arthritis detection tool

A scoping review of triage approaches for the referral of patients with suspected inflammatory arthritis, from primary to rheumatology care

We aimed to (1) identify existing triage approaches for referral of patients with suspected inflammatory arthritis (IA) from primary care physicians (PCP) to rheumatologists, (2) describe their characteristics and methodologies for clinical use, and (3) report their level of validation for use in a publicly funded healthcare system. The comprehensive search strategy of multiple databases up to October 2023 identified relevant literature and focussed on approaches applied at the PCP-Rheumatologist referral stage. Primary, quantitative studies, reported in English were included. Triage approaches were grouped into patient conditions as defined by the authors of the reports, including IA, its subtypes and combinations. 13952 records were identified, 425 full text reviewed and 55 reports of 53 unique studies were included. Heterogeneity in disease nomenclature and study sample pretest probability was found. The number of published studies rapidly increased after 2012. Studies were mostly from Europe and North America, in IA and Axial Spondyloarthritis (AxSpa). We found tools ranging the continuum of development with those best performing, indicated by the area under the receiver operating curve (AUC) >0.8), requiring only patient-reported questions. There were AUCs for some tools reported from multiple studies, these were in the outstanding to excellent range for the Early IA Questionnaire (EIAQ) (0.88 to 0.92), acceptable for the Case Finding AxSpa (CaFaSpa) (0.70 to 0.75), and poor to outstanding for the Psoriasis Epidemiology Screening Tool (PEST) (0.61 to 0.91). Given the clinical urgency to improve rheumatology referrals and considering the good.

Barriers to the Diagnosis of Early Inflammatory Arthritis: A Literature Review

The early identification of patients with inflammatory arthritis and their referral to rheumatologists in order to establish a diagnosis and to start treatment plays a crucial role in patient outcomes. However, it is recognized that a large proportion of patients with inflammatory arthritis are diagnosed very late, losing the opportunity to start treatment in the very early stages of disease, resulting in a worse prognosis. This delay depends on several factors related to the patient, the disease, socio-demographic and health system aspects. Over time, several strategies have been developed and implemented at different levels aiming to overcome such barriers and to reduce the time from the onset of the symptoms until the diagnosis and start of adequate treatment. In this non-systematic comprehensive review, we will describe the main barriers in the identification of patients with inflammatory arthritis at different levels. We will also discuss the different strategies that have been implemented with the objective to overcome the recognized barriers and their impact in the reduction of delays.

The value of inquiring about functional impairments for early identification of inflammatory arthritis: a large cross-sectional derivation and validation study from the Netherlands

OBJECTIVES

Healthcare professionals other than rheumatologists experience difficulties in detecting early inflammatory arthritis (IA) by joint examination. Self-reported symptoms are increasingly considered as helpful and could be incorporated in online tools to assist healthcare professionals, but first their discriminative ability must be assessed. As part of this effort, we evaluated whether inquiring about functional impairments could aid early IA identification.

DESIGN

Cross-sectional derivation and validation study.

SETTING

Data from two Early Arthritis Recognition Clinics (EARC) in the Netherlands were studied, which are easy access outpatient rheumatology clinics intermediary between primary and secondary care for patients in whom general practitioners suspect but are unsure about IA presence.

PARTICIPANTS

Between 2010 and 2014, 997 patients consecutively visited the Leiden-EARC (derivation cohort). Patients consecutively visiting the Groningen EARC (2010-2014, n=506) and Leiden-EARC (2015-2018, n=557) served as validation cohorts.

PRIMARY AND SECONDARY OUTCOME MEASURES

Physical functioning was assessed with the Health Assessment Questionnaire Disability-Index (HAQ); IA presence by physical joint examination by rheumatologists. HAQ questions were studied individually regarding discriminative ability for IA presence. For the best discriminating question, ORs and positive predictive values (PPVs) for IA presence were determined.

RESULTS

IA was ascertained in 43% (derivation cohort), 53% and 35% (validation cohorts). In the derivation cohort, IA presence associated with higher mean HAQ scores (0.84 vs 0.73, p=0.003). One question on difficulties with dressing equalled discriminative ability of the total HAQ score. 'Difficulties with dressing' yielded ORs for IA presence of 1.8 (95% CI 1.4 to 2.4) in the derivation cohort; 2.0 (1.4 to 2.9) and 2.1 (1.5 to 3.1) in the validation cohorts. After adjustments for clinical characteristics these were 1.7 (1.3 to 2.3), 1.6 (1.1 to 2.5) and 1.9 (1.2 to 2.9). PPVs (probabilities of IA for positive answers) ranged 42%-60% and negative predictive values (probabilities of no IA for negative answers) ranged 57%-74%.

CONCLUSIONS

Patient-reported difficulties with dressing in patients with suspected IA associated with actual IA presence. Although further validation is required, for example, in primary care, this simple question could be of help in future early IA detection tools for healthcare professionals with limited experience in joint examination.

Symptoms associated with inflammatory arthritis are common in the primary care population: results from the joint symptoms survey

OBJECTIVES

To describe the prevalence of self-reported inflammatory joint symptoms, such as joint pain, stiffness and swelling, in UK primary care patients consulting for both musculoskeletal (MSK) and non-musculoskeletal (non-MSK) complaints.

METHODS

A joint symptoms questionnaire survey was sent to 10 161 individuals, of whom 5050 had consulted for MSK problems. These were matched by age, gender and general practice to non-MSK consulters. Participants provided data on relevant symptoms such as joint pain, stiffness and swelling. The prevalence of these symptoms, their severity and impact were compared between MSK and non-MSK consulters.

RESULTS

A total of 4549 adults responded to the survey (adjusted response 45.8%) of whom 52.3% consulted for a MSK problem. The mean (s.d.) age was 61.6 (14.8) years and 58.9% were female. Persistent (on at least half of the days in the last month) inflammatory symptoms were common even in non-MSK consulters, with 42% reporting joint pain, 36% reporting joint stiffness and 18% reporting joint swelling. This is in comparison with 62% reporting joint pain, 50% stiffness and 24% swelling among MSK consulters.

CONCLUSIONS

Although symptoms such as persistent joint pain, swelling and stiffness are predictive of inflammatory arthritis, large numbers of people consulting primary care for non-MSK reasons report these symptoms when asked by questionnaire. This compounds the challenges of diagnosing inflammatory arthritis in a non-specialist setting where new approaches are needed to ensure accurate, early diagnosis, facilitating a treat-to-target approach.

Suspected very early inflammatory rheumatic diseases in primary care

As primary care clinicians are typically the first point of contact for patients with musculoskeletal problems, they are crucial to the early diagnosis and treatment of patients with an incident inflammatory arthritis, like rheumatoid arthritis. Current UK and international guidelines recognise this, recommending the prompt referral of patients with suspected persistent synovitis to secondary care. In England and Wales, this is advised to occur within 3 working days. However, recent audit data suggests this recommendation is infrequently met, with some patients waiting many months for referral. In this review article we will discuss the various challenges to achieving the early referral of patients with a new-onset inflammatory arthritis from primary to secondary care. We will also describe how these challenges could potentially be overcome, with the ultimate goal of ensuring that the right patients are referred to the right services, and at the right time.

Development and validation of a clinical rule for recognition of early inflammatory arthritis

OBJECTIVES

National and international guidelines recommend prompt referral of patients presenting with inflammatory arthritis (IA), but general practitioners (GPs) feel uncertain in their proficiency to detect synovitis through joint examination, the method of choice to identify IA. Our objective was to develop and validate a rule composed of clinical characteristics to assist GPs and other physicians in identifying IA when in doubt.

DESIGN

Split-sample derivation and validation study.

SETTING

The Leiden Early Arthritis Recognition Clinic (EARC), a screening clinic for patients in whom GPs suspected but were unsure of the presence of IA.

PARTICIPANTS

1288 consecutive patients visiting the EARC.

PRIMARY AND SECONDARY OUTCOME MEASURES

Associations of clinical characteristics with presence of IA were determined using logistic regression in 644 patients, while validating the results in the other 644 patients (split-sample validation). To facilitate application in clinical practice, a simplified rule (with scores ranging from 0 to 7.5) was derived and validated.

RESULTS

IA was identified by a rheumatologist in 41% of patients. In univariable analysis, male gender, age ≥60 years, symptom duration <6 weeks, morning stiffness >60 min, a low number of painful joints (1-3 joints), presence of patient-reported joint swelling and difficulty with making a fist were associated with IA in the derivation data set. Using multivariable analysis, a simplified rule consisting of these seven items was derived and validated, yielding an area under the receiver operator characteristic curve (AUC) of 0.74 (95% CI 0.70 to 0.78) in the derivation data set. Validation yielded an AUC of 0.71 (95% CI 0.67 to 0.75). Finally, the model was repeated to study predicted probabilities with a lower prevalence of inflammatory arthritis to simulate performance in primary care settings.

CONCLUSIONS

Our rule, composed of clinical parameters, had reasonable discriminative ability for IA and could assist physicians in decision-making in patients with suspected IA, increasing appropriateness of healthcare utilisation.

Clinimetric properties of the Chinese version of the early inflammatory arthritis detection tool

BACKGROUND

Timely rheumatologic referral and management are crucial for patients with potential inflammatory arthritis. To meet this need, tools such as the early inflammatory arthritis (EIA) detection tool was developed and has been evaluated in Western populations. The aims of this study were to translate the English version of the EIA detection tool to Chinese and to determine its clinimetric properties in Taiwanese patients.

METHODS

Twenty controls and 111 patients with established diagnosis of osteoarthritis, rheumatoid arthritis, systemic autoimmune diseases, psoriatic arthritis, and ankylosing spondylitis were recruited from a regional hospital in south Taiwan. Multivariate logistic regression analysis was used to evaluate the independent and significant variables associated with diagnosis by rheumatologists. A prediction model was also developed for differentiating between patients with inflammatory arthritis and those with non-inflammatory arthritis musculoskeletal conditions.

RESULTS

The Chinese version of the EIA detection tool showed acceptable internal consistency (KR-20 coefficient 0.78) and test-retest reliability (κ statistic ranged from 0.43 to 0.94). A prediction model consisting of three EIA detection tool items (joint pain, swelling in hands or wrists, and ever been told to have rheumatoid arthritis) and sex was able to differentiate inflammatory arthritis and non-inflammatory arthritis musculoskeletal conditions with a sensitivity of 0.84, a specificity of 0.86, a positive predictive value of 0.92, and a negative predictive value of 0.76.

CONCLUSIONS

The Chinese version of the EIA detection tool showed good clinimetric properties in this study population and it can be used to differentiate Taiwanese patients with inflammatory arthritis and non-inflammatory arthritis musculoskeletal conditions.

Validation of a Self-administered Inflammatory Arthritis Detection Tool for Rheumatology Triage

Objective.

The benefits of early intensive treatment of inflammatory arthritis (IA) are dependent on timely and accurate case identification. In our study, a scoring algorithm for a self-administered IA detection tool was developed and validated for the rheumatology triage clinical setting.

Methods.

A total of 143 consecutive consenting adults, newly referred to 2 outpatient rheumatology practices, completed the tool. A scoring algorithm was derived from the best-fit logistic regression model using age, sex, and responses to the 12 tool items as candidate predictors of the rheumatologists' blinded classification of IA. Bootstrapping was used to internally validate and refine the model.

Results.

The 30 IA cases were younger than the 113 non-cases (p < 0.0001) and included clinical diagnoses of early IA (n = 10), rheumatoid arthritis (n = 9), and spondyloarthropathies (n = 11). Non-cases included osteoarthritis (n = 46), pain syndromes (n = 19), systemic lupus erythematosus (n = 5), and miscellaneous, noninflammatory musculoskeletal complaints (n = 43). The best-fit model included younger age, male sex, “trouble making a fist,” “morning stiffness,” “ever told you have RA,” and “psoriasis diagnosis.” The overall predictive performance (standard error, SE) of the derivation model was 0.91 (0.03). Internal validation of the derivation model across 200 bootstrap samples resulted in a mean predictive performance (SE) of 0.904 (0.002). The refined tool had a mean predictive performance (SE) of 0.915 (0.002), a sensitivity of 0.855 (0.005), and specificity of 0.873 (0.003).

Conclusion.

A simple, self-administered tool was developed and internally validated for the sensitive and specific detection of IA in a rheumatology waiting list sample. The tool may be used to triage IA from rheumatology referrals.