Rheumatic Disease Comorbidity Index Research Articles

Classifying Multimorbidity Using Drug Concepts via the Rx-Risk Comorbidity Index: Methods and Comparative Cross-Sectional Study.

The study objective was to update a method to identify comorbid conditions using only medication information in circumstances in which diagnosis codes may be undercaptured, such as in single-specialty electronic health records (EHRs), and to compare the distribution of comorbidities across Rx-Risk versus other traditional comorbidity indices. Using First Databank, RxNorm, and its web-based clients, RxNav and RxClass, we mapped Drug Concept Unique Identifiers (RxCUIs), National Drug Codes (NDCs), and Anatomical Therapeutic Chemical (ATC) codes to Rx-Risk, a medication-focused comorbidity index. In established rheumatoid arthritis (RA) and osteoarthritis (OA) cohorts within the Rheumatology Informatics System for Effectiveness registry, we then compared Rx-Risk with other comorbidity indices, including the Charlson Comorbidity Index, Rheumatic Disease Comorbidity Index (RDCI), and Elixhauser. We identified 965 unique ingredient RxCUIs representing the 46 Rx-Risk comorbidity categories. After excluding dosage form and ingredient related RxCUIs, 80,911 unique associated RxCUIs were mapped to the index. Additionally, 187,024 unique NDCs and 354 ATC codes were obtained and mapped to the index categories. When compared to traditional comorbidity indices in the RA cohort, the median score for Rx-Risk (median 6.00 [25th percentile 2, 75th percentile 9]) was much greater than for Charlson (median 0 [25th percentile 0, 75th percentile 0]), RDCI (median 0 [25th percentile 0, 75th percentile 0]), and Elixhauser (median 1 [25th percentile 1, 75th percentile 1]). Analyses of the OA cohort yielded similar results. For patients with a Charlson score of 0 (85% of total), both the RDCI and Elixhauser were close to 1, but the Rx-Risk score ranged from 0 to 16 or more. The misclassification and under-ascertainment of comorbidities in single-specialty EHRs can largely be overcome by using a medication-focused comorbidity index.

Factors in Hand Surgery Access for Rheumatoid Arthritis Before vs After the Patient Protection and Affordable Care Act

Rheumatoid arthritis (RA) has severe functional and economic consequences. The implications of the Patient Protection and Affordable Care Act (ACA) and demographic factors for access to surgical treatment are unclear. To investigate factors associated with time to RA hand surgery, surgical incidence, and cost after implementation of the ACA. This cross-sectional study used insurance data from the IBM MarketScan Research Databases from 2009 through 2020 to compare time to surgery, surgical incidence, and treatment cost for RA of the hand before and after ACA implementations. Included patients were 18 years or older with a new diagnosis for RA of the hand and at least 1 procedural code for arthroplasty, arthrodesis, tenolysis, tendon repair, or tendon transfer. Patients with coexisting inflammatory arthritis diagnoses were excluded. Demographic variables analyzed included patient sex, age at index date, residence within or outside a metropolitan statistical area (MSA; hereafter urban or nonurban), insurance and health plan type, Social Deprivation Index, Elixhauser Comorbidity Index score, and Rheumatic Disease Comorbidity Index. Data analysis occurred from October 2022 to April 2023. Surgery for RA of the hand during the pre-ACA (before 2014) vs post-ACA (2014 or later) periods. Time to surgery, surgical incidence, and cost of treating RA in patients undergoing hand surgery for RA. Among 3643 patients (mean [SD] age, 57.6 [12.3] years) who underwent hand surgery for RA, 3046 (83.6%) were women. Post-ACA passage, 595 (86.2%) patients who resided in urban areas had a significantly lower time to surgery than those who did not (-70.5 [95% CI, -112.6 to -28.3] days; P < .001). Among urban patients, the least socially disadvantaged patients experienced the greatest decrease in time to surgery after ACA but the change was not statistically significant. For all patients, greater social disadvantage (ie, a higher SDI score) was associated with a longer time to surgery in the post-ACA period; for example, compared with the least socially disadvantaged group (SDI decile, 0-10), patients in SDI decile 10 to 20 waited an additional 254.0 days (95% CI, 65.2 to 442.9 days; P = .009) before undergoing surgery. Compared with the pre-ACA period, the mean surgical incidence in the post-ACA period was 83.4% lower (162.3 vs 26.9 surgeries per 1000 person-years; P < .001), and surgical incidence was 86.3% lower in nonurban populations (27.2 vs 3.7 surgeries per 1000 person-years; P < .001) but only 82.8% lower in urban populations (135.1 vs 23.2 surgeries per 1000 person-years; P < .001). Per capita total costs of all treatment related to RA of the hand decreased in the post-ACA period but the change was not statistically significant. Insurer-paid costs were lower in the post-ACA period but the change was not statistically significant. Out-of-pocket expenses did not change. Findings of this cross-sectional study suggest that after ACA passage, disparities exist in access to timely, cost-effective hand surgery for RA. Increased access to surgical hand specialists is needed for nonurban residents and those with greater social deprivation, along with insurance policy reforms to further decrease out-of-pocket spending for RA hand surgery.

Clinical Features Associated With Rate of Fractures in Patients With Systemic Sclerosis: A US Cohort Study.

Systemic sclerosis (SSc) is associated with several specific risk factors for fracture due to the complications of the disease and related medications. The present study was undertaken to examine the relationship between SSc-associated clinical features and fracture rate in a large US cohort. Participants with SSc in FORWARD, The National Databank for Rheumatic Diseases, were included (1998-2019). Age- and sex-matched individuals with osteoarthritis (OA) from the same database were included as comparators. The primary end point was self-reported major osteoporotic fracture. Cox proportional hazards models were used to study the associations between risk factors and fractures. The study included 922 individuals (SSc patients, n=154; OA patients, n=768). Eighty-seven percent were female, with a mean age of 57.8 years. Fifty-one patients developed at least 1 fracture during a median of 4.2 years (0.5-22.0 years) of follow-up. Patients with SSc had more frequent fractures compared to OA comparators (hazard ratio [HR] 2.38 [95% confidence interval (95% CI) 1.47-3.83]). Among patients with SSc, a higher Rheumatic Disease Comorbidity Index score (HR 1.45 [95% CI 1.20-1.75]) and a higher Health Assessment Questionnaire disability index score (HR 3.83 [95% CI 2.12-6.93]) were associated with more fractures. Diabetes mellitus (HR 5.89 [95% CI 2.51-13.82]) and renal disease (HR 2.43 [95% CI 1.10-5.37]) were independently associated with fracture among SSc patients relative to SSc patients without these comorbidities. Our findings highlight factors associated with fracture among patients with SSc. Disability as measured by the HAQ DI is a particularly strong indicator of fracture rate in SSc. Improving SSc patients' functional status, where possible, may lead to better long-term outcomes.

Associations of Cost Sharing With Rheumatoid Arthritis Disease Burden.

To evaluate the regional variation of cost sharing and associations with rheumatoid arthritis (RA) disease burden in the US. Patients with RA from rheumatology practices in Northeast, South, and West US regions were evaluated. Sociodemographics, RA disease status, and comorbidities were collected, and Rheumatic Disease Comorbidity Index (RDCI) score was calculated. Primary insurance types and copay for office visits (OVs) and medications were documented. Univariable pairwise differences between regions were conducted, and multivariable regression models were estimated to evaluate associations of RDCI with insurance, geographical region, and race. In a cohort of 402 predominantly female, White patients with RA, most received government versus private sponsored primary insurance (40% vs. 27.9%). Disease activity and RDCI were highest for patients in the South region, where copays for OVs were more frequently more than $25. Copays for OVs and medications were less than $10 in 45% and 31.8% of observations, respectively, and more prevalent in the Northeast and West patient subsets than in the South subset. Overall, RDCI score was significantly higher for OV copays less than $10 as well as for medication copays less than $25, both independent of region or race. Additionally, RDCI was significantly lower for privately insured than Medicare individuals (RDCI -0.78, 95% CI [-0.41 to -1.15], P < 0.001) and Medicaid (RDCI -0.83, 95% CI [-0.13 to -1.54], P = 0.020), independent of region and race. Cost sharing may not facilitate optimum care for patients with RA, especially in the Southern regions. More support may be required of government insurance plans to accommodate patients with RA with a high disease burden.

High burden of polypharmacy and comorbidity in persons with psoriatic arthritis: an analysis of claims data, stratified by age and sex

ObjectiveTo assess polypharmacy in women and men with psoriatic arthritis (PsA).MethodsFrom the German BARMER health insurance database, 11 984 persons with PsA and disease-modifying antirheumatic drug therapy in 2021 were...

Association between Rheumatic Disease Comorbidity Index and factors of poor prognosis in a cohort of 280 patients with rheumatoid arthritis

BackgroundRheumatoid arthritis (RA) is commonly associated with higher rates of comorbidities. Recent recommendations highlight screening comorbidities during the disease course because of their impact on patients’ ability to function, on disease outcome, but also on treatment choices. Hence the interest of our study that aimed to quantify the impact of comorbidities among RA patients using a validated tool the Rheumatic Disease Comorbidity Index (RDCI) and to explore the association between comorbidities and disease characteristics.MethodsWe conducted a cross-sectional study over 12 months period, including patients followed for an established RA according to the ACR/EULAR 2010 criteria and hospitalized in our rheumatology department. Patients’ characteristics and disease features were collected for each patient. Comorbidities were quantified using the RDCI. We looked for the association between RDCI and patients characteristics and RA parameters. Univariable and multivariable analysis were made.ResultsThey were 280 patients: 233 female (83.2%) and 47 male (16.8%) with a mean age of 58.07 (SD 11.12) years. The mean follow-up period was 14.74 (SD 1.63) years. Comorbidities were noted in 133 patients (47.5%). The mean comorbidity score measured by the RDCI was 1.05 (SD 1.23). RDCI was positively correlated with age (p < 0.001, r = 0.359). RA patients whose age of disease onset exceeds 40 years have significantly higher RDCI (1.8 (SD 1.3) [CI 95%: 1.36–1.88] vs. 1.5 (SD 1.2), p = 0.007). Moreover, RDCI was significantly associated with the presence pulmonary involvement (p < 0.001) and ocular involvement (p = 0.002). RDCI was also associated with erosive RA (p = 0.006), the presence of atlanto-axial dislocation (p = 0.014), and coxitis (p = 0.029). Regarding therapy regimen, RDCI was statistically increased in patients receiving bDMARDs compared to patients under csDMARDs (2.8 (SD 1.6) vs. 1.0 (SD 1.0), p = 0.021).ConclusionIn this study, comorbidity index was associated with signs of poor prognosis such as erosions, coxitis, and atlanto-axial dislocation. This confirmed the hypothesis that comorbidity can be a threat to the improvement in the long-term prognosis in RA patients.

Real-life data on the comorbidities in spondyloarthritis from our multicenter nationwide registry: BioStar.

Considering that the comorbid situations during the management of Spondyloarthritis (SpA) have been underlined in several recommendations, the main objective of this study was to evaluate the comorbid conditions of Turkish patients with SpA. This cross-sectional observational study was conducted with 1,242 SpA patients (844 males, 398 females; mean age: 43.9±11.0 years; range, 19 to 81 years) diagnosed according to the modified New York criteria for ankylosing spondylitis or the Assessment of SpondyloArthritis International Society (ASAS) criteria. The patient data were collected from the Biologic and targeted Synthetic antirheumatic drugs Registry (BioStar) between February 1, 2019, and December 29, 2020. Clinical and demographic data, including, age, sex, disease duration, body mass index (BMI), pain, patient's global assessment, physician's global assessment, Bath Ankylosing Spondylitis Disease Activity Index, Ankylosing Spondylitis Disease Activity Score, Bath Ankylosing Spondylitis Functional Index, Bath Ankylosing Spondylitis Metrology Index, and Maastricht Enthesitis Score, were recorded. Comorbid conditions were recorded by filling out a questionnaire according to the clinical history or medical records. Charlson Comorbidity Index and Rheumatic Disease Comorbidity Index scores were calculated from the gathered comorbidity information. Nine hundred thirteen patients had radiographic axial SpA, 153 had nonradiographic axial SpA, and 176 had peripheral SpA. The most common comorbidities were hypertension (HT) (n=167, 13.4%), diabetes mellitus (DM) (n=83, 6.7%), thyroid disorders (n=64, 5.6%), and depression (n=61, 4.9%). The comorbidities and the calculated comorbidity indices were significantly higher in females, in those with a BMI >25 kg/m2 , and those over 60 years of age. No relationship was found between smoking and alcohol use and comorbidities. A significantly higher prevalence of HT and DM in peripheral SpA patients and a lower prevalence of thyroid disorders in radiographic axial SpA patients were observed. The most commonly reported comorbidities were HT, DM, thyroid disorders, and depression in SpA patients according to the BioStar database. The frequency of comorbidities and composite comorbidity scores were higher among females, older (>60 years) patients, and overweight (BMI >25 kg/m2 ) patients.

Prospective cohort study of psoriatic arthritis risk in patients with psoriasis in a real-world psoriasis registry

The characteristics that predict the onset of psoriatic arthritis (PsA) among patients with psoriasis (PsO) may inform diagnosis and treatment. To develop a model to predict the 2-year risk of developing PsA among patients with PsO. This was a prospective cohort study of patients in the CorEvitas Psoriasis Registry without PsA at enrollment and with 24-month follow-up. Unregularized and regularized logistic regression models were developed and tested using descriptive variables to predict dermatologist-identified PsA at 24months. Model performance was compared using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. A total of 1489 patients were included. Nine unique predictive models were developed and tested. The optimal model, including Psoriasis Epidemiology Screening Tool (PEST), body mass index (BMI), modified Rheumatic Disease Comorbidity Index, work status, alcohol use, and patient-reported fatigue, predicted theonset of PsA within 24months (AUC=68.9%, sensitivity=82.9%, specificity=48.8%). A parsimonious model including PEST and BMI had similar performance (AUC=68.8%; sensitivity=92.7%, specificity=36.5%). PsA misclassification bias by dermatologists. PEST and BMI were important factors in predicting the development of PsA in patients with PsO over 2years and thereby foundational for future PsA risk model development.

ОСОБЛИВОСТІ ПЕРЕБІГУ ПОДАГРИ ТА COVID-19 В УМОВАХ КОМОРБІДНОСТІ

Introduction. Comorbid diseases signifi cantly exacerbate gout burden, represent an even more elevated risk of hospitalization and mortality rates owing to the coronavirus disease 2019 (COVID-19) than gout itself. Objectives. To evaluate the infl uence of the modifi ed Rheumatic Disease Comorbidity Index (mRDCI) on the clinical course of gout and COVID-19. Methods. Using data from 136 male participants with gout, we distributed the cohort according to values of the mRDCI as follows: 0 – without comorbidities, 1-2 – low comorbidity index (CI), 3-4 – moderate CI and ≥5 – high CI. “Treat-to-target” approach for gout, the association of mRDCI with the clinical course of gout, lipid metabolism, and severity of COVID-19 were analyzed. Results. According to mRDCI scores, almost every second gout patient (45.6%) had moderate CI, every fi fth (19.1%) – high CI, and 14.7% – low CI. Greater mRDCI was associated with the higher severity of COVID-19 (p=0.003), limited physical functioning (r=0.5, p&lt;0.001), higher body mass index (r=0.63, p&lt;0.001), hyperuricemia (r=0.37, p&lt;0.001), increased low–density lipoprotein cholesterol (LDL–C) (r=0.38, p&lt;0.001), higher gout activity (r=0.4, p&lt;0.001), more frequent acute fl ares in the preceding year (r=0.39, p&lt;0.001), number of tophi (r=0.31, p&lt;0.001), longer duration of gout (r=0.34, p&lt;0.001), reduced glomerular fi ltration rate (r =–0.39, p&lt;0.001), and daily excretion of uric acid (UA) (r=–0.28, p=0.001). The target level of serum UA was achieved in 22.1%. The majority of patients were not controlled for LDL-C (83.7%), blood pressure (75.5%), and glucose (69.44%) in the cohort with dyslipidemia, hypertension, and diabetes respectively. Conclusion. The high prevalence of comorbidities in gout patients was associated with the severity of COVID-19. We have established the following three patterns of comorbidity predictors: anthropometric, disease-related, and dysmetabolic. The management of gout requires a multidisciplinary approach.

Dactylitis and Early Onset Psoriasis in Psoriatic Arthritis: Are they Markers of Disease Severity? A Clinical Study.

ObjectivesTo stratify psoriatic arthritis (PsA) patients based on psoriasis (PsO) onset age: early onset psoriasis (EOP) vs. late onset psoriasis (LOP), and to assess if there are differences in disease characteristics, activity/function/impact of the disease, and comorbidity indices.MethodsCross-sectional analysis of a longitudinal PsA cohort. Patients were stratified based on PsO onset age.ResultsOne hundred and sixty PsA patients were enrolled (84 in EOP and 76 in LOP group) in the study. EOP PsA patients seem to have an increased probability to have dactylitis rather than LOP ones, OR 9.64 (3.77–24.6). Comorbidity indices (Rheumatic Disease Comorbidity Index and Charlson Comorbidity Index) were higher in LOP PsA patients, but these data were not confirmed when adjusted by age and sex. There are also differences in the treatment regimen: EOP PsA patients were more frequently treated with anti-interleukin (IL) 17; instead, LOP patients were more frequently treated with non-steroid anti-inflammatory drugs and conventional synthetic disease-modifying anti-rheumatics drugs. There were no differences in the disease activity, function, or impact of the disease.ConclusionsThere are some clinical and therapeutic differences in PsA patients linked to the PsO onset age, namely dactylitis in EOP. Other characteristics found were: a “comorbidities trend” in LOP patients and a more frequent use of anti-IL17 in EOP.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40744-022-00468-3.

AB0954 Concordance between different comorbidities scores in patients with psoriatic arthritis

BackgroundPatients with psoriatic arthritis (PA) are more likely to suffer from other chronic medical conditions, associated comorbidities having significant impact upon both quality of life and survival. As disorders like the cardiovascular disease, metabolic syndrome, hepatic or renal pathologies were shown to be more prevalent in PA [1], assessment of comorbidities is important in these patients [2].ObjectivesTo investigate the concordance of different comorbidities scores in patients with PA.MethodsProspective inclusion of patients diagnosed with PA according to the CASPAR (ClASsification criteria for Psoriatic ARthritis) criteria. Associated comorbidities were prospectively assessed using the Psoriatic arthritis comorbidity index (PsACI) with a cut-off of 8 points as previously defined [2]. Also, the following comorbidities scores were completed in all patients: Charlson comorbidity index (CCI), Rheumatoid Arthritis Comorbidity Index (RACI), Rheumatic Diseases comorbidity index (RDCI), Functional comorbidity index (FCI).ResultsA total of 56 patients were included: 27 (48.2%) were female, with a med (q1;q3) disease duration of 17.5 (12.7; 26.5) years for the cutaneous disease and 6.0 (4.0; 13.0) years for the articular one. At inclusion, the results of the comorbidities scores assessed were as follow: PsACI 3.2 (2.0; 6.5), CCI 1.0 (0.0; 2.0), RACI 3.5 (1.5; 6.5), RDCI 1.0 (0.0; 2.0), and FCI 2.0 (0.0; 2.0), respectively. According to PsACI, hypertension, hyperlipidemia, osteoarthritis, liver disease, and diabetes mellitus were the most frequent associated comorbidities in PA patients, in 53.6%, 44.6%, 41.1%, 37.5%, and 28.6% cases, respectively (see Table 1).Table 1.Comorbidities according to the Psoriatic Arthritis Comorbidity IndexParametern (%)Parametern (%)Diabetes mellitus16 (28.6)Cerebrovascular disease1 (1.8)Metabolic syndrome8 (14.3)Peripheral vascular disease2 (3.6)Ischemic heart disease9 (16.1)Osteoporosis4 (7.1)Myocardial infarction1 (1.8)Fracture3 (5.4)Hypertension30 (53.6)Fall1 (1.8)Hyperlipidemia25 (44.6)Liver disease21 (37.5)Arrhythmia2 (3.6)Renal disease2 (3.6)Depression6 (10.7)Pulmonary disease6 (10.7)Anxiety10 (17.9)Gastrointestinal tract2 (3.6)Endocrine7 (12.5)Osteoarthritis23 (41.1)Periodontitis1 (1.8)Fibromyalgia3 (5.4)Smoking6 (10.7)Amyloidosis1 (1.8)Infection0 (0.0)Eyes inflame/ uveitis0 (0.0)Vasculitis0 (0.0)Tumor3 (5.4)In bivariate analysis, we found significant correlations between the results of PsACI and those of the other comorbidities scores used: CCI (p&lt;0.001, rho=0.668), RACI (p&lt;0.001, rho=0.792), RDCI (p&lt;0.001, rho=0.691), and FCI (p&lt;0.001, rho=0.697), respectively.The ability of the comorbidities scores assessed to discriminate a PsACI high value is presented in Figure 1, AUC (95%CI): CCI 0.743 (0.601- 0.886) p=0.017, RACI 0.815 (0.634 - 0.996) p=0.002, RDCI 0.818 (0.657-0.980) p=0.002, and FCI 0.837 (0.725-0.948) p=0.001, respectively.Figure 1.The Area Under the curve of the Receiver Operating Characteristic (AUROC) for high PsACI results (PsACI &gt; 8)ConclusionThe composite indexes offer the advantage of reducing all associated comorbidities as long with their severity into a single score. We herein identified good correlations between the results of the comorbidities scores analyzed, PsACI, CCI, RDCI, RACI, and FCI, respectively.

Tocilizumab as a first-line biologic treatment in rheumatoid arthritis patients – the impact of concomitant methotrexate treatment and Rheumatic Disease Comorbidity Index on the clinical response – results from the multicenter observational ACT-POL study

ObjectivesAccording to the EULAR recommendations, remission or low disease activity (LDA) in rheumatoid arthritis should be achieved by a maximum of 6 months (M6) of treatment. Data on the use of tocilizumab (TCZ) as first-line biologic treatment in rheumatoid arthritis (RA) in routine clinical practice in Poland are lacking.Material and methodsThis multicenter, non-interventional, prospective, observational study recruited adults, presenting with moderate-to-severe RA, showing an inadequate response or intolerance to disease-modifying antirheumatic drugs, where TCZ was the first-line biologic treatment. The effectiveness of TCZ was assessed by the proportion of patients achieving remission and low disease activity following 6 months of treatment with intravenous TCZ. The impact of comorbidities on treatment outcomes was measured using the Rheumatic Disease Comorbidity Index (RDCI).ResultsTotal remission rates at months 3 and 6 were 6% and 31%, respectively. Low disease activity was reported in 10% and 92% of the patients at 3 and 6 months, respectively. The response was comparable between TCZ as monotherapy and in combination with methotrexate. Mean DAS28 decreased from 6.61 at baseline to 4.27 at the scheduled time of the assessment (3 and 6 months). The Rheumatic Disease Comorbidity Index was not correlated with the number of patients achieving LDA at M3 and M6 or remission rates at M6. Remission rates correlated with RDCI at M3. A total of 114 adverse events were reported in 61 patients, among which five were considered as serious.ConclusionsThe study confirms the effectiveness and safety of TCZ in real-world settings as a first-line biologic treatment in patients with moderate-to-severe RA. Importantly, comorbidities do not affect the results of 6-month treatment with TCZ, that is, the optimal time to achieve at least LDA. Our results may improve the effects of RA therapy in Poland, especially in patients with comorbidities and those who, for various reasons, cannot receive optimal treatment with methotrexate.

P198 The role of comorbidities alongside patient and disease characteristics on long-term disease activity in RA using UK inception cohort data

Abstract Background/Aims Control of disease activity in Rheumatoid Arthritis (RA) is crucial to prevent long-term joint damage and disability. European Alliance of Associations for Rheumatology (EULAR) guidelines recommend focus on disease activity when measuring health outcomes in people living with RA. Particularly, one of their four overarching principles targets clinical remission, defined as the absence of significant inflammatory disease activity, or low disease activity an acceptable alternative. In EULAR’s most recent guidelines (2014), attention was drawn to the role of comorbidities in RA disease management noting the “potential to preclude treatment intensification”. Besides this, recent work by the EULAR Task Force on difficult-to-treat RA recognises that comorbidities can influence the assessment of inflammatory activity in individuals with RA. This study aimed to identify early predictors of poor disease activity at five and 10 years, focussing on comorbidities alongside clinical/sociodemographic factors at first presentation. Methods Patients were recruited from two UK-based RA cohorts; Early Rheumatoid Arthritis Study (ERAS, 1986-2001) and Early Rheumatoid Arthritis Network (ERAN, 2002-2012). Participants were classified into two groups; low (&amp;lt;3.2) and moderate/high (≥3.2) Disease Activity Score (DAS28) at 5/10 years. Clinical information (e.g., rheumatoid nodules, erosions), sociodemographic factors (e.g., ethnicity, deprivation) and comorbidity burden (measured using the Rheumatic Diseases Comorbidity Index [RDCI]) were recorded at baseline and yearly thereafter. Multivariable logistic regression models (outcome; low versus DAS28≥3.2) were fitted using multiple imputation. Results 2,701 patients with RA were recruited (mean age 56.1 years, 66.9% female); 5-year follow-up data were available for 1,718 (63.4%) and 10-year for 820 (30.4%) patients. A higher proportion of individuals had DAS28≥3.2 values at 10 years than five (65.6% vs 59.7%). In multivariable analyses, baseline RDCI was not associated with DAS28 at five (OR 1.05, 95% CI 0.91 to 1.22) or 10 years (OR 0.99, 95% CI 0.75 to 1.31). Sociodemographic factors (female gender, worse deprivation) and poorer baseline HAQ were associated with DAS28≥3.2 at both timepoints, with no association found with age at onset. Being seropositive was associated with DAS28≥3.2 at 5 but not 10 years of follow-up. Conversely, a relationship existed between presence of erosions at baseline and 10-year DAS28 (OR 1.82, 95% CI 1.16 to 2.85). Conclusion This study found no association between baseline comorbidity burden and long-term RA disease activity. However, in models adjusted for comorbidity burden, associations with sociodemographic and clinical factors were demonstrated. These results build upon those relating to functional outcome and will accelerate the identification of those RA patients at increased risk of worse outcomes at initial rheumatology appointment. Additionally, these findings suggest that tailored intervention can be implemented in a timely manner, in line with national and international recommendations, potentially limiting permanent joint damage and disability to improve quality of life for individuals with RA. Disclosure A.D. Busby: None. J. Wason: None. A.G. Pratt: None. A. Young: None. J. Isaacs: None. E. Nikiphorou: None.

The role of comorbidities alongside patient and disease characteristics in long-term disease activity in RA using UK inception cohort data.

Control of disease activity in RA is a crucial part of its management to prevent long-term joint damage and disability. This study aimed to identify early predictors of poor disease activity at 5 and 10 years, focusing on comorbidities and clinical/sociodemographic factors at first presentation. Patients from two UK-based RA cohorts were classified into two groups; low (&lt;3.2) and moderate/high (≥3.2) DAS using 28 joint counts (DAS28) at 5/10 years. Clinical variables (e.g. rheumatoid nodules, erosions), sociodemographic factors (e.g. ethnicity, deprivation) and comorbidities were recorded at baseline and yearly thereafter. The Rheumatic Diseases Comorbidity Index quantified patient comorbidity burden. Binary logistic regression models (outcome low vs moderate/high DAS28) were fitted using multiple imputation. A total of 2701 patients living with RA were recruited (mean age 56.1 years, 66.9% female); 5-year data were available for 1718 (63.4%) patients and 10-year data for 820 (30.4%). Baseline Rheumatic Diseases Comorbidity Index was not associated with DAS28 at 5 [odds ratio (OR) 1.05, 95% CI 0.91, 1.22] or 10 years (OR 0.99, 95% CI 0.75, 1.31) in multivariable analyses. Sociodemographic factors (female gender, worse deprivation) and poorer baseline HAQ-Disability Index were associated with DAS28 ≥3.2 at both timepoints. Being seropositive was associated with 5-year DAS28 ≥3.2. This study demonstrates an association between sociodemographic and clinical factors and long-term RA disease activity, in models adjusting for comorbidity burden. The findings call for more holistic and targeted patient management in patients with RA and provide insights for more individualized management plans even on first presentation to rheumatology.

Comparison of Indexes to Measure Comorbidity Burden and Predict All-Cause Mortality in Rheumatoid Arthritis.

Objectives: To examine the comorbidity burden in patients with rheumatoid arthritis (RA) patients using a nationwide population-based cohort by assessing the Charlson Comorbidity Index (CCI), Elixhauser Comorbidity Index (ECI), Multimorbidity Index (MMI), and Rheumatic Disease Comorbidity Index (RDCI) scores and to investigate their predictive ability for all-cause mortality. Methods: We identified 24,767 RA patients diagnosed from 1998 to 2008 in Taiwan and followed up until 31 December 2013. The incidence of comorbidities was estimated in three periods (before, during, and after the diagnostic period). The incidence rate ratios were calculated by comparing during vs. before and after vs. before the diagnostic period. One- and 5-year mortality rates were calculated and discriminated by low and high-score groups and modified models for each index. Results: The mean score at diagnosis was 0.8 in CCI, 2.8 in ECI, 0.7 in MMI, and 1.3 in RDCI, and annual percentage changes are 11.0%, 11.3%, 9.7%, and 6.8%, respectively. The incidence of any increase in the comorbidity index was significantly higher in the periods of “during” and “after” the RA diagnosis (incidence rate ratios for different indexes: 1.33–2.77). The mortality rate significantly differed between the high and low-score groups measured by each index (adjusted hazard ratios: 2.5–4.3 for different indexes). CCI was slightly better in the prediction of 1- and 5-year mortality rates. Conclusions: Comorbidities are common before and after RA diagnosis, and the rate of accumulation accelerates after RA diagnosis. All four comorbidity indexes are useful to measure the temporal changes and to predict mortality.

Predictors of poor function in RA based on two prospective UK inception cohorts. Do comorbidities matter?

ObjectivesEvidence suggests that factors beyond disease activity associate with functional disability in RA. The primary study objective was to explore associations between comorbidities, sociodemographic factors and functional outcomes at five and 10 years.MethodsRA patients from two UK prospective cohorts were grouped into low (<1.5) and high (≥1.5) five- and 10-year health assessment questionnaire (HAQ) score. Clinical variables (e.g. disease activity, rheumatoid nodules, erosions) and sociodemographic factors (e.g. ethnicity, deprivation) were recorded at baseline and yearly thereafter. Comorbidity was measured using the Rheumatic Diseases Comorbidity Index (RDCI). Binary logistic regression models were fitted using multiple imputation.ResultsIn total, 2701 RA patients were recruited (mean age 56.1 years, 66.9% female). A total of 1718 (63.4%) had five-year and 820 (30.4%) 10-year follow-up data. In multivariable analysis, no association was found between RDCI and HAQ ≥ 1.5 at five or 10 years. Sociodemographic factors (increased age at disease onset, female gender, minority ethnicity) were associated with higher odds of HAQ ≥ 1.5 at five and 10 years, with worse deprivation additionally associated with HAQ ≥ 1.5 at 10 years (OR 0.79, 95% CI: 0.69, 0.90).ConclusionComorbidities at baseline have not been found to be associated with worse RA functional outcome in the long-term. On the other hand, sociodemographic factors, independently of disease measures, are associated with worse functional outcome in RA at five and 10 years, in models adjusting for comorbidity burden. Tailoring management interventions according to not only clinical disease parameters but also patient sociodemographic factors may improve long-term outcomes including functional disability.

Comorbidity burden in the first three years after diagnosis in patients with rheumatoid arthritis, psoriatic arthritis or spondyloarthritis: a general practice registry-based study

ObjectivesRheumatoid arthritis (RA), psoriatic arthritis (PsA) and spondyloarthritis (SpA) are chronic inflammatory rheumatic conditions with high levels of comorbidity requiring additional therapeutic attention. We aimed to compare the 3-year comorbidity...

OP0098 POLYPHARMACY IS ASSOCIATED WITH A POORER TREATMENT RESPONSE AND INCREASED RISK OF ADVERSE EVENTS IN EARLY RHEUMATOID ARTHRITIS

Background:Polypharmacy is steadily increasing in patients with rheumatoid arthritis (RA). They may interfere with treatment response and the occurrence of serious adverse events. Medications taken by a patient may reflect active comorbidities, whereas comorbidity indices usually used include past or current diseases.Objectives:To evaluate whether polypharmarcy is associated with treatment response and adverse events in an early RA cohort and to establish whether polypharmacy could represent a substitute of comorbidities.Methods:We used data from the French cohort ESPOIR, including 813 patients with early onset arthritis. Patients included the current study had to start their first disease modifying anti-rheumatic drug (DMARD) within 24 months of inclusion in the cohort. Disease activity data were collected at one, five and ten years from the initiation of the first DMARD. For each patient, treatments were collected at baseline and at five years. Medications count included all specialties other than background RA therapy, analgesics/NSAIDs and topicals. Polypharmacy was defined as a categorical variable based on the median and tertiles of distribution in the cohort. Treatment response was assessed by achieving DAS28 ESR remission (REM) at 1 year, 5 years and 10 years from the initiation of the first DMARD. The occurrence of severe adverse events (SAE) was measured by the occurrence of severe infection, hospitalization, or death during the 10-year follow-up. The association between patient’s characteristics and achievement of REM and occurrence of SAE were tested in univariate analysis. A logistic regression model was used to evaluate associations between polypharmacy and REM at 1 year, 5 years and 10 years (we used baseline polypharmacy for the 1-year analysis and five years polypharmacy for the 5- and 10-years analyses). Multivariate adjustment was made for age, sex, BMI, duration of disease, initial DAS28 ESR, initial HAQ, smoking status, rheumatic disease comorbidity index (RDCI).Results:The proportion of patients who achieved REM one year after the initiation of the first DMARD was 32.1% in the polypharmacy according to the median group (patients taken ≥2 medication) versus 67.9% in the non-polypharmacy group (p=0.07). At 5 years after the first DMARD, the proportion of patients with REM was 45.0% in the polypharmacy group versus 56.3% in the non-polypharmacy group (p=0.03). At 10 years the proportion of patients with REM was 32.5% in the polypharmacy group versus 67.5% (p=0.06). Patients who take greater or equal to 2 medications had a 40% lower probability of achieving REM (OR = 0.60 [0.38-0.94] p = 0.03) at 5 years from the first DMARD (if RDCI index was not included in the model). At 10 years, patients receiving multiple medications had a 43% lower probability of achieving REM (OR = 0.57 [0.34-0.94] p = 0.02). SAE incidence was 61 per 1000 patient-years. For patients who developed SAE all causes 71.4% where in the polypharmacy group versus 57.8% were in the non-polypharmacy group (p = 0.03; univariate analysis). These results are no longer significant after adjustment for comorbidities indices.Conclusion:In this early RA cohort, polypharmacy is associated with a poorer treatment response and increased risk of adverse events. Polypharmacy may represent a good substitute of comorbidities for epidemiological studies.Acknowledgements:We are grateful to Nathalie Rincheval (Montpellier) who did expert monitoring and data management and all theinvestigators who recruited and followed the patients (F. Berenbaum, Paris-Saint Antoine; MC. Boissier, Paris-Bobigny; A. Cantagrel, Toulouse; B. Combe, Montpellier; M. Dougados, Paris-Cochin; P. Fardellone and P. Boumier, Amiens; B. Fautrel, Paris-La Pitié; RM. Flipo, Lille; Ph. Goupille, Tours; F. Liote, Paris- Lariboisière; O. Vittecoq, Rouen; X. Mariette, Paris-Bicêtre; P. Dieude, Paris Bichat; A. Saraux, Brest; T. Schaeverbeke, Bordeaux; and J. Sibilia, Strasbourg).The work reported on in the manuscript did not benefit from any financial support. The ESPOIR cohort is sponsored by the French Society for Rheumatology. An unrestricted grant from Merck Sharp and Dohme (MSD) was allocated for the first 5 years. Two additional grants from INSERM were obtained to support part of the biological database. Pfizer, Abbvie, Lilly and more recently Fresenius and Biogen also supported the ESPOIR cohort.Disclosure of Interests:Soraya Benamar: None declared, Cédric Lukas Speakers bureau: Abbvie, Amgen, Janssen, Lilly, MSD, Novartis, Pfizer, Roche-Chugai, UCB, Consultant of: Abbvie, Amgen, Janssen, Lilly, MSD, Novartis, Pfizer, Roche-Chugai, UCB, Grant/research support from: Pfizer, Novartis and Roche-Chugai, Claire Daien Speakers bureau: AbbVie, Abivax, BMS, MSD, Roche, Chugai, Novartis, Pfizer, Sandoz, Lilly, Consultant of: AbbVie, Abivax, BMS, MSD, Roche, Chugai, Novartis, Pfizer, Sandoz, Lilly, Cécile Gaujoux-Viala Speakers bureau: Abbvie, BMS, Celgene, Janssen, Medac, MSD, Nordic Pharma, Novartis, Pfizer, Sanofi, Roche-Chugai, UCB, Consultant of: Abbvie, BMS, Celgene, Janssen, Medac, MSD, Nordic Pharma, Novartis, Pfizer, Sanofi, Roche-Chugai, UCB, Grant/research support from: Pfizer, Laure Gossec Speakers bureau: AbbVie, Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sandoz, Sanofi-Aventis et UCB, Consultant of: AbbVie, Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sandoz, Sanofi-Aventis et UCB, Anne-Christine Rat Speakers bureau: Pfizer, Lilly, Consultant of: Pfizer, Lilly, Bernard Combe Speakers bureau: AbbVie; Bristol-Myers Squibb; Gilead; Janssen; Lilly; Merck; Novartis; Pfizer; Roche-Chugai; and Sanofi;, Consultant of: AbbVie; Bristol-Myers Squibb; Gilead; Janssen; Lilly; Merck; Novartis; Pfizer; Roche-Chugai; and Sanofi;, Grant/research support from: Novartis, Pfizer, and Roche-Chugai., Jacques Morel Speakers bureau: Abbvie, BMS, Lilly, Médac, MSD, Nordic Pharma, Pfizer, UCB, Consultant of: Abbvie, BMS, Lilly, Médac, MSD, Nordic Pharma, Pfizer, UCB, Grant/research support from: BMS, Pfizer

301 Psoriatic arthritis risk in psoriasis patients in the Corrona® Psoriasis Registry

Background: Understanding characteristics that predict the onset of psoriatic arthritis (PsA) in psoriasis (PsO) patients would help effectively direct treatment. We aimed to develop a model to predict the 2-year PsA risk for real-world PsO patients. Methods: Patients in the prospective, multicenter, non-interventional Corrona Psoriasis Registry without PsA at enrollment and with a 24-month follow-up visit (FU) were included. Demographic and clinical variables collected at enrollment were used to construct logistic regression models to predict PsA diagnosis at FU. Data were randomly partitioned into training (70%) and testing (30%) sets. Models were developed using stepwise forward selection, backward elimination, and elastic net to select predictors. Performance was compared using area under the receiver-operating-characteristic curve (AUC), sensitivity (SE), and specificity (SP). Results: 1489 patients were analyzed (n=1042, training; n=447, test). In the training set, mean age was 49 years, 43% were female, and 119 (11%) developed PsA; those who developed PsA had higher mean Psoriasis Epidemiology Screening Tool (PEST) scores (2.8 vs 1.8), and patient-reported fatigue (33 vs 25, VAS-100) and skin pain (23 vs 19, VAS-100) at enrollment vs those who did not. Nine unique models were constructed; PEST and BMI were common in all. In the testing set, the most predictive model included PEST, BMI, modified Rheumatic Disease Comorbidity Index, work status, alcohol use, and fatigue (AUC= 68.9%, SE=82.9%, SP=48.8%). A more parsimonious model (PEST and BMI only) performed similarly (AUC=68.8%; SE=92.7%, SP=36.5%). Conclusions: While predictive ability was limited, and further refinement and external validation are needed, our findings provide insight for developing a tool to evaluate PsA risk in PsO patients.

Characteristics of patients with difficult-to-treat rheumatoid arthritis in clinical practice.

The aim of this study was to investigate the clinical characteristics of patients with difficult-to-treat RA (D2T RA) and the usefulness of switching to drugs with different modes of action in real-world. We reviewed all consecutive patients with RA treated at Keio University Hospital between 2016 and 2017 with a definition of D2T RA. We analysed clinical characteristics and evaluated the usefulness of changing drugs according to mode of action. Among 1709 patients with RA, 173 (10.1%) were D2T RA. The reason for the D2T RA was multi-drug resistance in 59 patients (34.1%), comorbidity in 17 (9.8%), and socio-economic reasons in 97 (56.1%). The multi-drug-resistance group had significantly higher tender joint count and evaluator global assessment than the other groups, despite receiving the most intensive treatment. The comorbidity group showed a significantly older age and higher rheumatic disease comorbidity index. Although changing the drug to another with a different mode of action was useful, the proportion of patients who achieved remission or low disease activity decreased as the number of switches increased. Of the patients with RA, 10.1% were still difficult to treat in clinical practice, despite intensive treatment. Their characteristics were distinct by the reasons of D2T RA, which suggests the need for a personalized approach to D2T RA.