Positive anti-citrullinated protein antibody status and small joint arthritis are consistent predictors of chronic disease in patients with very early arthritis: results from the NOR-VEAC cohort

Introduction The current 1987 American College of Rheumatology (ACR) classification criteria for rheumatoid arthritis (RA) have proven less useful in early arthritis. The objective of this study was to identify and compare predictors of three relevant outcomes of chronic arthritis in a cohort of very early arthritis patients. Methods The Norwegian Very Early Arthritis Cohort (NOR-VEAC) includes adult patients with at least one swollen joint of ≤16 weeks' duration. Patients are followed for 2 years with comprehensive clinical and laboratory examinations. Logistic regression analyses were performed to determine independent predictors of three outcomes: persistent synovitis, prescription of disease-modifying anti-rheumatic drugs (DMARDs), and established clinical RA diagnosis within one year. Results Of 384 patients eligible for one year follow-up (56.3% females, mean (SD) age 45.8 (14.7) years, median (IQR) duration of arthritis 31 (10-62) days), 14.4% were anti-CCP2 positive, and 11.2% were IgM RF positive. 98 patients (25.5%) had persistent synovitis, 106 (27.6%) had received DMARD treatment during follow-up, while 68 (17.7%) were diagnosed with RA. Consistent independent predictors across all three outcomes were positive anti-citrullinated protein antibody (ACPA) status (odds ratio (OR) 3.2, 5.6 and 19.3), respectively, and small joint arthritis (proximal interphalangeal joint (PIP), metacarpo-phalangeal joint (MCP), and/or metatarso-phalangeal joint (MTP) joint swelling) (OR 1.9, 3.5, and 3.5, respectively). Conclusions Positive ACPA status and small joint arthritis were consistent predictors of three relevant outcomes of chronic arthritis in very early arthritis patients. This consistency supports DMARD prescription as a valid surrogate endpoint for chronic arthritis. Importantly, this surrogate is used in ongoing efforts to develop new diagnostic criteria for early RA

The likelihood of persistent arthritis increases with the level of anti-citrullinated peptide antibody and immunoglobulin M rheumatoid factor: a longitudinal study of 376 patients with very early undifferentiated arthritis

Introduction We wanted to assess the importance of the levels of anti-citrullinated peptide antibody (anti-CCP) and immunoglobulin M (IgM) rheumatoid factor (RF) in predicting development of persistent arthritis from undifferentiated arthritis (UA), and to investigate whether there is an added predictive value for persistent arthritis in testing for both anti-CCP and IgM RF. Methods Patients with UA (exclusion of definite non-rheumatoid arthritis (RA) diagnoses) included in the Norwegian very early arthritis clinic were assessed for development of persistent arthritic disease. The effect of antibody level on the likelihood of persistent arthritis was investigated, and the sensitivity and specificity for persistent arthritis for anti-CCP and IgM RF, separately and combined, was determined. Results A total of 376 UA patients were included (median arthritis duration 32 days). 59 (15.7%) patients were IgM RF positive, and 62 (16.5%) anti-CCP positive. One hundred, seventy-four (46.3%) had persistent disease after one year. Overlap of anti-CCP and IgM RF positivity was 58%. Sensitivity/specificity for persistent arthritis was 28/95% for IgM RF alone, 30/95% for anti-CCP alone, and 37/92% for positivity of both anti-CCP and IgM RF. The likelihood for persistent disease increased with increasing levels of both anti-CCP and IgM RF. Conclusions The likelihood of developing persistent arthritis in UA patients increases with the level of anti-CCP and IgM RF. Testing both anti-CCP and IgM RF has added predictive value in UA patients. This study suggests that antibody level should be taken into account when making risk assessments in patients with UA

Methotrexate Treatment of Newly Diagnosed RA Patients Is Associated With DNA Methylation Differences at Genes Relevant for Disease Pathogenesis and Pharmacological Action

Background: Methotrexate (MTX) is the fi rst line treatment of rheumatoid arthritis (RA), and methylation changes in bulk T cells have been reported after treatment with MTX. We have investigated cell-type speci fi c DNA methylation changes across the genome in naïve and memory CD4 + T cells before and after MTX treatment of RA patients. DNA methylation pro fi les of newly diagnosed RA patients (N=9) were assessed by reduced representation bisul fi te sequencing. Results: We found that MTX treatment signi fi cantly in fl uenced DNA methylation levels at multiple CpG sites in both cell populations. Interestingly, we identi fi ed differentially methylated sites annotated to two genes; TRIM15 and SORC2, previously reported to predict treatment outcome in RA patients when measured in bulk T cells. Furthermore, several of the genes, including STAT3, annotated to the signi fi cant CpG sites are relevant for RA susceptibility or the action of MTX. Conclusion: We detected CpG sites that were associated with MTX treatment in CD4 + naïve and memory T cells isolated from RA patients. Several of these sites overlap genetic regions previously associated with RA risk and MTX treatment outcome

Using observational study data as an external control group for a clinical trial: an empirical comparison of methods to account for longitudinal missing data

Abstract Background Observational data are increasingly being used to conduct external comparisons to clinical trials. In this study, we empirically examined whether different methodological approaches to longitudinal missing data affected study conclusions in this setting. Methods We used data from one clinical trial and one prospective observational study, both Norwegian multicenter studies including patients with recently diagnosed rheumatoid arthritis and implementing similar treatment strategies, but with different stringency. A binary disease remission status was defined at 6, 12, and 24 months in both studies. After identifying patterns of longitudinal missing outcome data, we evaluated the following five approaches to handle missingness: analyses of patients with complete follow-up data, multiple imputation (MI), inverse probability of censoring weighting (IPCW), and two combinations of MI and IPCW. Results We found a complex non-monotone missing data pattern in the observational study (N = 328), while missing data in the trial (N = 188) was monotone due to drop-out. In the observational study, only 39.0% of patients had complete outcome data, compared to 89.9% in the trial. All approaches to missing data indicated favorable outcomes of the treatment strategy in the trial and resulted in similar study conclusions. Variations in results across approaches were mainly due to variations in estimated outcomes for the observational data. Conclusions Five different approaches to handle longitudinal missing data resulted in similar conclusions in our example. However, the extent and complexity of missing observational data affected estimated comparative outcomes across approaches, highlighting the need for careful consideration of methods to account for missingness in this setting. Based on this empirical examination, we recommend using a prespecified advanced missing data approach to account for longitudinal missing data, and to conduct alternative approaches in sensitivity analyses. </jats:sec

Using observational study data as an external control group for a clinical trial: an empirical comparison of methods to account for longitudinal missing data

Background Observational data are increasingly being used to conduct external comparisons to clinical trials. In this study, we empirically examined whether different methodological approaches to longitudinal missing data affected study conclusions in this setting. Methods We used data from one clinical trial and one prospective observational study, both Norwegian multicenter studies including patients with recently diagnosed rheumatoid arthritis and implementing similar treatment strategies, but with different stringency. A binary disease remission status was defined at 6, 12, and 24 months in both studies. After identifying patterns of longitudinal missing outcome data, we evaluated the following five approaches to handle missingness: analyses of patients with complete follow-up data, multiple imputation (MI), inverse probability of censoring weighting (IPCW), and two combinations of MI and IPCW. Results We found a complex non-monotone missing data pattern in the observational study (N = 328), while missing data in the trial (N = 188) was monotone due to drop-out. In the observational study, only 39.0% of patients had complete outcome data, compared to 89.9% in the trial. All approaches to missing data indicated favorable outcomes of the treatment strategy in the trial and resulted in similar study conclusions. Variations in results across approaches were mainly due to variations in estimated outcomes for the observational data. Conclusions Five different approaches to handle longitudinal missing data resulted in similar conclusions in our example. However, the extent and complexity of missing observational data affected estimated comparative outcomes across approaches, highlighting the need for careful consideration of methods to account for missingness in this setting. Based on this empirical examination, we recommend using a prespecified advanced missing data approach to account for longitudinal missing data, and to conduct alternative approaches in sensitivity analyses

Using Observational Study Data as an External Control Group for a Clinical Trial: an Empirical Comparison of Methods to Account for Longitudinal Missing Data

Abstract Background: Observational data are increasingly being used to conduct external comparisons to clinical trials. In this study, we empirically examined whether different methodological approaches to longitudinal missing data affected study conclusions in this setting. Methods: We used data from one clinical trial and one prospective observational study, both Norwegian multicenter studies including patients with recently diagnosed rheumatoid arthritis and implementing similar treatment strategies, but with different stringency. A binary disease remission status was defined at 6, 12, and 24 months in both studies. After identifying patterns of longitudinal missing outcome data, we evaluated the following five approaches to handle missingness: analyses of patients with complete follow-up data, multiple imputation (MI), inverse probability of censoring weighting (IPCW), and two combinations of MI and IPCW. Results: We found a complex non-monotone missing data pattern in the observational study (N=328), while missing data in the trial (N=188) was monotone due to drop-out. In the observational study, only 39.0% of patients had complete outcome data, compared to 89.9% in the trial. All approaches to missing data indicated favorable outcomes of the treatment strategy in the trial and resulted in similar study conclusions. Variations in results across approaches were mainly due to variations in estimated outcomes for the observational data. Conclusions: Five different approaches to handle longitudinal missing data resulted in similar conclusions in our example. However, the extent and complexity of missing observational data affected estimated comparative outcomes across approaches, highlighting the need for careful consideration of methods to account for missingness when using observational data as external controls to trial data.</jats:p

Do rheumatologists know best? An outcomes study of inconsistent users of disease-modifying anti-rheumatic drugs

OBJECTIVE: Current recommendations advocate treatment with disease-modifying anti-rheumatic drugs (DMARDs) in all patients with active rheumatoid arthritis (RA). We analyzed short-term disease outcome in patients according to the consistency of DMARD use in a clinical rheumatology cohort. METHODS: Patients in an RA registry (N=617) were studied for DMARD use at semi-annual study time points during the first 18 months of follow-up, and were divided into 4 groups according to the number of study time points with any DMARD use (0–1 study time points (n=31), 2 study time points (n=24), 3 study time points (n=77), and 4 study time points (n=485). The primary outcome analyses were performed at 24 months and included Disease Activity Score 28 (DAS28-CRP), modified Health Assessment Questionnaire (MHAQ) change, Short Form Health Survey-12 physical and mental summary scores (SF-12 PCS, SF-12 MCS), EuroQol 5-Dimensional health index (EQ-5D) and radiographic progression. Unadjusted, adjusted and analyses stratified for seropositivity and disease activity were performed. A secondary analysis investigated 36 month-outcomes. RESULTS: No significant 24-month outcome differences could be found between the DMARD use categories. For seropositive patients there was evidence of a linear trend for SF-12 PCS (p=0.02) and EQ-5D (p=0.01) with worse outcomes for inconsistent DMARD users. At 36 months, there was a linear trend for higher DAS28-CRP scores for inconsistent users (p<0.01) CONCLUSIONS: Overall, we found poor correlation between inconsistent DMARD use and short-term disease outcome. However, outcome in the longer term could be negatively influenced by inconsistent DMARD use, as well as short-term outcome in seropositive patients