Population-based user-perceived experience of Rheumatic?: a novel digital symptom-checker in rheumatology.

OBJECTIVE: Digital symptom-checkers (SCs) have potential to improve rheumatology triage and reduce diagnostic delays. In addition to being accurate, SCs should be user friendly and meet patient's needs. Here, we examined usability and acceptance of Rheumatic?-a new and freely available online SC (currently with >44 000 users)-in a real-world setting. METHODS: Study participants were recruited from an ongoing prospective study, and included people ≥18 years with musculoskeletal complaints completing Rheumatic? online. The user experience survey comprised five usability and acceptability questions (11-point rating scale), and an open-ended question regarding improvement of Rheumatic? Data were analysed in R using t-test or Wilcoxon rank test (group comparisons), or linear regression (continuous variables). RESULTS: A total of 12 712 people completed the user experience survey. The study population had a normal age distribution, with a peak at 50-59 years, and 78% women. A majority found Rheumatic? useful (78%), thought the questionnaire gave them an opportunity to describe their complaints well (76%), and would recommend Rheumatic? to friends and other patients (74%). Main shortcoming was that 36% thought there were too many questions. Still, 39% suggested more detailed questions, and only 2% suggested a reduction of questions. CONCLUSION: Based on real-world data from the largest user evaluation study of a digital SC in rheumatology, we conclude that Rheumatic? is well accepted by women and men with rheumatic complaints, in all investigated age groups. Wide-scale adoption of Rheumatic?, therefore, seems feasible, with promising scientific and clinical implications on the horizon.

The Role of Genetics in Clinically Suspect Arthralgia and Rheumatoid Arthritis Development: A Large Cross-Sectional Study.

OBJECTIVE: To investigate whether established genetic predictors for rheumatoid arthritis (RA) differentiate healthy controls, patients with clinically suspect arthralgia (CSA), and RA patients. METHODS: Using analyses of variance, chi-square tests, and mean risk difference analyses, we investigated the association of an RA polygenic risk score (PRS) and HLA shared epitope (HLA-SE) with all participant groups, both unstratified and stratified for anti-citrullinated protein antibody (ACPA) status. We used 3 separate data sets sampled from the same Dutch population (1,015 healthy controls, 479 CSA patients, and 1,146 early classified RA patients). CSA patients were assessed for conversion to inflammatory arthritis over a period of 2 years, after which they were classified as either CSA converters (n = 84) or CSA nonconverters (n = 395). RESULTS: The PRS was increased in RA patients (mean ± SD PRS 1.31 ± 0.96) compared to the complete CSA group (1.07 ± 0.94) and compared to CSA converters (1.12 ± 0.94). In ACPA- strata, PRS distributions differed strongly when comparing the complete CSA group (mean ± SD PRS 1.05 ± 0.94) and CSA converters (0.97 ± 0.87) to RA patients (1.20 ± 0.94), while in the ACPA+ strata, the complete CSA group (1.25 ± 0.99) differed clearly from healthy controls (1.05 ± 0.94) and RA patients (1.41 ± 0.96). HLA-SE was more prevalent in the RA group (prevalence 0.64) than the complete CSA group (0.45), with small differences between RA patients and CSA converters (0.64 versus 0.60) and larger differences between CSA converters and CSA nonconverters (0.60 versus 0.42). HLA-SE prevalence differed more strongly within the ACPA+ strata as follows: healthy controls (prevalence 0.43), CSA nonconverters (0.48), complete CSA group (0.59), CSA converters (0.66), and RA patients (0.79). CONCLUSION: We observed that genetic predisposition increased across pre-RA participant groups. The RA PRS differed in early classified RA and inflammatory pre-disease stages, regardless of ACPA stratification. HLA-SE prevalence differed between arthritis patients, particularly ACPA+ patients, and healthy controls. Genetics seem to fulfill different etiologic roles.

A framework for employing longitudinally collected multicenter electronic health records to stratify heterogeneous patient populations on disease history.

OBJECTIVE: To facilitate patient disease subset and risk factor identification by constructing a pipeline which is generalizable, provides easily interpretable results, and allows replication by overcoming electronic health records (EHRs) batch effects. MATERIAL AND METHODS: We used 1872 billing codes in EHRs of 102 880 patients from 12 healthcare systems. Using tools borrowed from single-cell omics, we mitigated center-specific batch effects and performed clustering to identify patients with highly similar medical history patterns across the various centers. Our visualization method (PheSpec) depicts the phenotypic profile of clusters, applies a novel filtering of noninformative codes (Ranked Scope Pervasion), and indicates the most distinguishing features. RESULTS: We observed 114 clinically meaningful profiles, for example, linking prostate hyperplasia with cancer and diabetes with cardiovascular problems and grouping pediatric developmental disorders. Our framework identified disease subsets, exemplified by 6 "other headache" clusters, where phenotypic profiles suggested different underlying mechanisms: migraine, convulsion, injury, eye problems, joint pain, and pituitary gland disorders. Phenotypic patterns replicated well, with high correlations of ≥0.75 to an average of 6 (2-8) of the 12 different cohorts, demonstrating the consistency with which our method discovers disease history profiles. DISCUSSION: Costly clinical research ventures should be based on solid hypotheses. We repurpose methods from single-cell omics to build these hypotheses from observational EHR data, distilling useful information from complex data. CONCLUSION: We establish a generalizable pipeline for the identification and replication of clinically meaningful (sub)phenotypes from widely available high-dimensional billing codes. This approach overcomes datatype problems and produces comprehensive visualizations of validation-ready phenotypes.

Determining in which pre-arthritis stage HLA-shared epitope alleles and smoking exert their effect on the development of rheumatoid arthritis.

OBJECTIVES: The human leukocyte antigen-shared epitope (HLA-SE) alleles and smoking are the most prominent genetic and environmental risk factors for rheumatoid arthritis (RA). However, at which pre-arthritis stage (asymptomatic/symptomatic) they exert their effect is unknown. We aimed to determine whether HLA-SE and smoking are involved in the onset of autoantibody positivity, symptoms (clinically suspect arthralgia (CSA)) and/or progression to clinical arthritis. METHODS: We performed meta-analyses on results from the literature on associations of HLA-SE and smoking with anti-citrullinated protein antibodies (ACPAs) in the asymptomatic population. Next, we studied associations of HLA-SE and smoking with autoantibody positivity at CSA onset and with progression to clinical inflammatory arthritis (IA) during follow-up. Associations in ACPA-positive patients with CSA were validated in meta-analyses with other arthralgia cohorts. Analyses were repeated for rheumatoid factor (RF), anti-carbamylated protein antibodies (anti-CarP) and anti-acetylated protein antibodies (AAPA). RESULTS: Meta-analyses showed that HLA-SE is not associated with ACPA positivity in the asymptomatic population (OR 1.06 (95% CI:0.69 to 1.64)), whereas smoking was associated (OR 1.37 (95% CI: 1.15 to 1.63)). At CSA onset, both HLA-SE and smoking associated with ACPA positivity (OR 2.08 (95% CI: 1.24 to 3.49), OR 2.41 (95% CI: 1.31 to 4.43)). During follow-up, HLA-SE associated with IA development (HR 1.86 (95% CI: 1.23 to 2.82)), in contrast to smoking. This was confirmed in meta-analyses in ACPA-positive arthralgia (HR 1.52 (95% CI: 1.08 to 2.15)). HLA-SE and smoking were not associated with RF, anti-CarP or AAPA-positivity at CSA onset. Longitudinally, AAPA associated with IA development independent from ACPA and RF (HR 1.79 (95% CI: 1.02 to 3.16)), anti-CarP did not. CONCLUSIONS: HLA-SE and smoking act at different stages: smoking confers risk for ACPA and symptom development, whereas HLA-SE mediates symptom and IA development. These data enhance the understanding of the timing of the key risk factors in the development of RA.