Frequency of Prescription Claims for Drugs that May Interact with Janus Kinase Inhibitors Among Patients with Rheumatoid Arthritis in the US.

INTRODUCTION: This study describes the frequency of prescription claims for drugs that may interact with Janus kinase (JAK) inhibitors among adult patients with rheumatoid arthritis (RA) in a large US claims database. METHODS: This observational, retrospective, cross-sectional study of the IBM® MarketScan® Research Commercial and the Medicare Supplemental Database included adults (≥ 18 years) with ≥ 2 outpatient claims 30 or more days apart or ≥ 1 inpatient visit claim with an RA diagnosis between January 1, 2013 and March 31, 2017 (the index period). During the study period, from January 1, 2013 to March 31, 2018, strong organic anion transporter (OAT3) inhibitors, strong cytochrome P450 (CYP) 3A4 inhibitors, and moderate or strong CYP3A4 inhibitors in combination with strong CYP2C19 inhibitors, were identified as drugs with potential for drug-drug interactions (DDIs) with JAK inhibitors approved for RA treatment in the US. Descriptive statistics were conducted. RESULTS: A total of 152,853 patients met eligibility criteria. Approximately 76% were women and the median age was 57 years. Of these patients, < 0.1% had a claim for a strong OAT3 inhibitor, and 1% had claims for the combination of a strong CYP3A4 and strong CYP2C19 inhibitor; 3% of patients had a claim for a strong CYP3A4 inhibitor and almost 10% had claims for both a moderate CYP3A4 and a strong CYP2C19 inhibitor. CONCLUSIONS: Up to 10% of RA patients have been prescribed a drug with a potential JAK interaction. Rheumatologists should consider potential DDIs when managing patients with RA.

Probabilistic Linkage of Randomized Controlled Trial Data to Administrative Claims: A Case Study of Patients from Baricitinib Clinical Trials.

INTRODUCTION: The aim of this work is to assess the feasibility of probabilistically linking randomized controlled trial (RCT) data to claims data in a real-world setting to inform future rheumatoid arthritis (RA) research. METHODS: This retrospective cohort study utilized IQVIA's Patient Centric Medical Claims (Dx) Database, IQVIA's Longitudinal Prescription Claims (LRx) Database, and Lilly's baricitinib RCT data from a sample of patients that consented to the linkage of their de-identified insurance claims to their de-identified RCT data. Patients were initially matched on age, gender, and three-digit ZIP code of the provider and further matched according to a point scoring system using additional clinical variables. RESULTS: A total of 245 patients from 49 US clinical trial sites were eligible for the study and 78 (31.8%) of these patients consented to participate. Of the 78 consented patients, 69 (88%) were successfully matched on age, gender, and three-digit ZIP code of the provider. Of the 69 patients successfully matched on age, gender, and three-digit ZIP code of the provider, 44 (63.8%) had at least one sufficient match using the point scoring system. Of these 44, 23 (52.3%) patients matched at a ratio of one RCT patient to one Dx/LRx patient, 11 (25.0%) at a ratio of 1:2, 7 (15.9%) at a ratio of 1:3 and three (6.8%) at a ratio of 1:4 or greater. To further improve match ratios, a variable hierarchy was applied to the 18 RCT patients with 2-3 matches. Overall, 38 of the 78 (48.7%) consented RCT patients were successfully matched 1:1 to claims database patients. CONCLUSIONS: This probabilistic linkage methodology demonstrates the feasibility, at a moderate linkage rate, of linking patients from RCTs to real-world data, which can provide a means to assess additional information not usually collected within or following a clinical trial.

Which patient-reported outcomes do rheumatology patients find important to track digitally? A real-world longitudinal study in ArthritisPower.

BACKGROUND: Patient-reported outcomes (PROs) are increasingly used to track symptoms and to assess disease activity, quality of life, and treatment effectiveness. It is therefore important to understand which PROs patients with rheumatic and musculoskeletal disease consider most important to track for disease management. METHODS: Adult US patients within the ArthritisPower registry with ankylosing spondylitis, fibromyalgia syndrome, osteoarthritis, osteoporosis, psoriatic arthritis, rheumatoid arthritis, and systemic lupus erythematosus were invited to select between 3 and 10 PRO symptom measures they felt were important to digitally track for their condition via the ArthritisPower app. Over the next 3 months, participants (pts) were given the option to continue tracking their previously selected measures or to remove/add measures at 3 subsequent monthly time points (month [m] 1, m2, m3). At m3, pts prioritized up to 5 measures. Measures were rank-ordered, summed, and weighted based on pts rating to produce a summary score for each PRO measure. RESULTS: Among pts who completed initial selection of PRO assessments at baseline (N = 253), 140 pts confirmed or changed PRO selections across m1-3 within the specified monthly time window (28 days ± 7). PROs ranked as most important for tracking were PROMIS Fatigue, Physical Function, Pain Intensity, Pain Interference, Duration of Morning Joint Stiffness, and Sleep Disturbance. Patient's preferences regarding the importance of these PROs were stable over time. CONCLUSION: The symptoms that rheumatology patients prioritized for longitudinal tracking using a smartphone app were fatigue, physical function, pain, and morning joint stiffness.

Prevalence of Renal Impairment in a US Commercially Insured Rheumatoid Arthritis Population: A Retrospective Analysis.

INTRODUCTION: Global prevalence estimates for chronic kidney disease (CKD) in rheumatoid arthritis (RA) vary. This study assessed real-world prevalence estimates of renal impairment, based on estimated glomerular filtration rate (eGFR), among commercially insured patients with RA in the United States (US). METHODS: In this retrospective cohort study, we used administrative claims data from the HealthCore Integrated Research Database (HIRD®) between January 2013 and December 2018. Adult patients with ≥ 2 claims for RA and ≥ 2 serum creatinine (SCr) measurements ≥ 90 days apart on or after the index date were included. eGFR was calculated per the Modification of Diet in Renal Disease equation. Prevalence of eGFR-based renal impairment was estimated for the overall RA population and for two subgroups: patients on advanced therapies (biologic disease-modifying antirheumatic drugs/tofacitinib) and patients stratified based on health plan types. RESULTS: Among 128,062 patients with ≥ 2 RA claims, 42,173 had qualifying SCr measurements, 16,197 were on advanced RA therapies, and 4911 had Medicare Advantage or Supplemental plus Part D coverage. For the overall population and the subgroup on advanced therapies, mild renal impairment was observed in 52% and 51%, moderate renal impairment in 9% and 7%, and severe renal impairment in 0.5% and 0.3% of patients, respectively. Moderate and severe renal impairment was more prevalent in the Medicare Advantage/Supplemental plus Part D population compared to the commercial coverage population. CONCLUSIONS: Approximately 7-10% of commercially insured adult patients in the US with RA had moderate or severe renal impairment. Assessment of renal function is an important consideration for safe treatment.

Patient-reported outcomes from a randomized, double-blind, placebo controlled, phase III study of baricitinib versus placebo in patients with moderately to severely active rheumatoid arthritis and an inadequate response to methotrexate therapy: results from the RA-BALANCE study.

INTRODUCTION: To assess the effect of baricitinib on patient-reported outcomes (PROs) in patients with moderately to severely active rheumatoid arthritis (RA) who had an inadequate response to methotrexate (MTX). METHODS: This was a 52-week, randomized, double-blind, placebo controlled, phase III study in patients with RA who had an inadequate response to MTX. Patients (n = 290) receiving stable background MTX were randomly assigned (1:1) to receive placebo or baricitinib 4 mg once daily with a primary endpoint at week 12. PROs assessed included Health Assessment Questionnaire-Disability Index (HAQ-DI), Patient's Global Assessment of Disease Activity, patient's assessment of pain, Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F), European Quality of Life-5 Dimensions-5 Level index scores and visual analogue scale, and measures collected in electronic patient daily diaries: duration of morning joint stiffness, Worst Tiredness, and Worst Joint Pain. Treatment comparisons were made with logistic regression and analysis of covariance models for categorical and continuous variables, respectively. RESULTS: Statistically significant (p ⩽ 0.05) improvements in all PROs were observed in the baricitinib 4 mg group compared to placebo as early as week 1 to week 4; and were sustained to week 24. These improvements were maintained until week 52 for the baricitinib group. A significantly larger proportion of patients met or exceeded the minimum clinically important difference for HAQ-DI (⩾0.22) and FACIT-F (3.56) profiles in the baricitinib group. CONCLUSION: Baricitinib provided significant improvements in PROs compared to placebo to 52 weeks of treatment in patients with RA who had an inadequate response to MTX.Clinicaltrials.gov identifier: https://clinicaltrials.gov/ct2/show/NCT02265705; NCT02265705; RA-BALANCE. Registered 13 October 2014.

Estimation of Minimally Important Differences and Patient Acceptable Symptom State Scores for the Patient-Reported Outcomes Measurement Information System Pain Interference Short Form in Rheumatoid Arthritis.

OBJECTIVE: Studies have supported the validity of the Patient-Reported Outcomes Measurement Information System (PROMIS) Pain Interference (PI) scale in rheumatoid arthritis (RA). Here, we characterize minimally important differences (MIDs) and patient acceptable symptom state (PASS) values. METHODS: PROMIS PI scores were collected in four periods at 6-month intervals from patients with RA (n > 3200 per period). Both anchor- and distribution-based methods estimated MIDs. Anchors were pain comparisons, pain interference, and general health. Time responses for each anchor-response group (four administrations, each with three change periods) were averaged. The mean changes of the "somewhat worse" and "somewhat better" groups were used as estimates for MID for worsening and improvement, respectively. Distribution-based MID analyses used standardized error of measurement (SEM) and SD. PASS was estimated with the question "If your health was to remain for the rest of your life as it has been in the past 48 hours, would this be acceptable?" MIDs and PASS values were also estimated by baseline pain levels. RESULTS: Anchor-based methods yielded estimates of 1.65 to 1.84 for worsening and -1.29 to -1.73 for improvement. The SEM estimate was 1.84. The PASS estimate for the entire group was 41.6. Substantial differences in MIDs and PASS were noted among baseline pain groups. CONCLUSION: The best estimate of a group-level MID was approximately 2 points, similar to MIDs suggested in other conditions. The PASS value for the entire group was almost an SD better than the population mean. Results should enhance use of PROMIS PI in RA by facilitating interpretation of scores and changes.

Digital Tracking of Rheumatoid Arthritis Longitudinally (DIGITAL) Using Biosensor and Patient-Reported Outcome Data: Protocol for a Real-World Study.

BACKGROUND: Rheumatoid arthritis (RA) is a condition with symptoms that vary over time. The typical 3- to 6-month interval between physician visits may lead to patients failing to recall or underreporting symptoms experienced during the interim. Wearable digital technology enables the regular passive collection of patients' biometric and activity data. If it is shown to be strongly related to data captured by patient-reported outcome (PRO) measures, information collected passively from wearable digital technology could serve as an objective proxy or be complementary to patients' subjective experience of RA symptoms. OBJECTIVE: The goal of this study is to characterize the extent to which digital measures collected from a consumer-grade smartwatch agree with measures of RA disease activity and other PROs collected via a smartphone app. METHODS: This observational study will last 6 months for each participant. We aim to recruit 250 members of the ArthritisPower registry with an RA diagnosis who will receive a smartwatch to wear for the period of the study. From the ArthritisPower mobile app on their own smartphone device, participants will be prompted to answer daily and weekly electronic PRO (ePRO) measures for the first 3 months. RESULTS: The study was launched in December 2018 and will require up to 18 months to complete. Study results are expected to be published by the end of 2021. CONCLUSIONS: The completion of this study will provide important data regarding the following: (1) the relationship between passively collected digital measures related to activity, heart rate, and sleep collected from a smartwatch with ePROs related to pain, fatigue, physical function, and RA flare entered via smartphone app; (2) determine predictors of adherence with smartwatch and smartphone app technology; and (3) assess the effect of study-specific reminders on adherence with the smartwatch. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14665.