Clinical indications associated with new opioid use for pain management in the United Kingdom: using national primary care data.

ABSTRACT: Prescription opioids for noncancer pain in the United Kingdom have increased over the past 2 decades, alongside associated harms. Policies addressing opioid prescribing must be tailored to individual patient needs with specific disease systems. The aim of this study was to evaluate clinical conditions associated with new opioid initiation in noncancer pain using nationally representative UK data. Primary care electronic health records from January 1, 2006, to September 31, 2021, were used from the Clinical Research Practice Datalink to identify incident opioid prescriptions. Patient histories were reviewed using code lists for opioid-related conditions with a 5-year look-back for chronic conditions and a 1-year look-back for surgical indications before opioid initiation. In total, 3,030,077 new opioid use episodes in 2,027,402 patients were identified, with 61% being women, 77% aged 45 years and older, and 48% from the highest deprivation quintile. Ten systems associated with opioid initiation were identified, which were not mutually exclusive, as patients could have opioids prescribed for multiple indications. The most common were musculoskeletal (80.8%), respiratory (57.6%), infections (30.4%), trauma/injury (20.4%), neurology (19.9%), and postsurgical indications (5.5%). Osteoarthritis (60.7%) and low back pain (41.0%) were the most frequent musculoskeletal conditions. Orthopedic surgeries accounted for 41.2% of all postsurgical indications. This is the first study in the United Kingdom evaluating large-scale national data to assess indications associated with opioid initiation. Nearly 3 quarters of new opioid prescriptions for noncancer pain were in patients with musculoskeletal conditions, often for conditions with limited evidence for opioid efficacy. These findings could inform targeted interventions and future policies to support nonpharmacological interventions in the most common conditions where opioid harms outweigh benefits.

Factors associated with long-term opioid use among patients with axial spondyloarthritis or psoriatic arthritis who initiated opioids.

OBJECTIVE: Up to one in five patients with axial spondyloarthritis (AxSpA) or psoriatic arthritis (PsA) newly initiated on opioids transition to long-term use within the first year. This study aimed to investigate individual factors associated with long-term opioid use among opioid new users with AxSpA/PsA. METHODS: Adult patients with AxSpA/PsA and without prior cancer who initiated opioids between 2006-2021 were included from Clinical Practice Research Datalink Gold, a national UK primary care database. Long-term opioid use was defined as having ≥3 opioid prescriptions issued within 90 days, or ≥ 90 days of opioid supply, in the first year of follow-up. Individual factors assessed included sociodemographic, lifestyle factors, medication use and comorbidities. A mixed-effects logistic regression model with patient-level random intercept was used to examine the association of individual characteristics with the odds of long-term opioid use. RESULTS: In total 10 300 opioid initiations were identified from 8,212 patients (3037 AxSpA; 5175 PsA). The following factors were associated with long-term opioid use: being a current smoker (OR : 1.62; 95%CI : 1.38,1.90), substance use disorder (OR : 2.34, 95%CI : 1.05,5.21), history of suicide/self-harm (OR : 1.84; 95%CI : 1.13,2.99), co-existing fibromyalgia (OR : 1.62; 95%CI : 1.11,2.37), higher Charlson Comorbidity Index (OR : 3.61; 95%CI : 1.69,7.71 for high scores), high MME/day at initiation (OR : 1.03; 95%CI : 1.02,1.03) and gabapentinoid (OR : 2.35; 95%CI : 1.75,3.16) and antidepressant use (OR : 1.69; 95%CI : 1.45,1.98). CONCLUSIONS: In AxSpA/PsA patients requiring pain relief, awareness of lifestyle, sociodemographic and prescribing characteristics associated with higher risk of long-term opioid use can prompt timely interventions such as structured medication reviews and smoking cessation to promote safer prescribing and better patient outcomes.

Is there a role for novel supplements in the management of fatigue in rheumatic diseases?

Fatigue is a common symptom of rheumatic diseases and frequently persists even when patients are in a near-remission state. In seeking options to manage troublesome symptoms such as fatigue, complementary and alternative medicines (CAM) are often used by patients despite a lack of evidence base behind such treatment strategies. CAM use is further promoted by social media and 'influencer' marketing without rigorous process to ensure scientific accuracy. One mechanism of recent interest in the CAM market is enhancing cellular pathways of nicotinamide adenine dinucleotide (NAD+), purported to restore mitochondrial function. However, clinical trials of NAD+ pathway supplements lack rigorous trial design, many declare conflicts of interest, and safety data is limited. Ultimately, CAM use by our patients is unavoidable. To adequately inform patients about CAM, we need to keep updated on both the latest scientific literature and social media trends. In so doing, we can then propose to patients how standard-of-care therapies, evidence-based lifestyle modifications and CAM might safely and effectively integrate to form a treatment plan.

Postoperative opioids administered to inpatients with major or orthopaedic surgery: A retrospective cohort study using data from hospital electronic prescribing systems.

BACKGROUND: Opioids administered in hospital during the immediate postoperative period are likely to influence post-surgical outcomes, but inpatient prescribing during the admission is challenging to access. Modified-release(MR) preparations have been especially associated with harm, whilst certain populations such as the elderly or those with renal impairment may be vulnerable to complications. This study aimed to assess postoperative opioid utilisation patterns during hospital stay for people admitted for major/orthopaedic surgery. METHODS: Patients admitted to a teaching hospital in the North-West of England between 2010-2021 for major/orthopaedic surgery with an admission for ≥1 day were included. We examined opioid administrations in the first seven days post-surgery in hospital, and "first 48 hours" were defined as the initial period. Proportions of MR opioids, initial immediate-release(IR) oxycodone and initial morphine milligram equivalents (MME)/day were calculated and summarised by calendar year. We also assessed the proportion of patients prescribed an opioid at discharge. RESULTS: Among patients admitted for major/orthopaedic surgery, 71.1% of patients administered opioids during their hospitalisation. In total 50,496 patients with 60,167 hospital admissions were evaluated. Between 2010-2017 MR opioids increased from 8.7% to 16.1% and dropped to 11.6% in 2021. Initial use of oxycodone IR among younger patients (≤70 years) rose from 8.3% to 25.5% (2010-2017) and dropped to 17.2% in 2021. The proportion of patients on ≥50MME/day ranged from 13% (2021) to 22.9% (2010). Of the patients administered an opioid in hospital, 26,920 (53.3%) patients were discharged on an opioid. CONCLUSIONS: In patients hospitalised with major/orthopaedic surgery, 4 in 6 patients were administered an opioid. We observed a high frequency of administered MR opioids in adult patients and initial oxycodone IR in the ≤70 age group. Patients prescribed with ≥50MME/day ranged between 13-22.9%. This is the first published study evaluating UK inpatient opioid use, which highlights opportunities for improving safer prescribing in line with latest recommendations.

Machine learning identifies risk factors associated with long-term opioid use in fibromyalgia patients newly initiated on an opioid.

OBJECTIVES: Fibromyalgia is frequently treated with opioids due to limited therapeutic options. Long-term opioid use is associated with several adverse outcomes. Identifying factors associated with long-term opioid use is the first step in developing targeted interventions. The aim of this study was to evaluate risk factors in fibromyalgia patients newly initiated on opioids using machine learning. METHODS: A retrospective cohort study was conducted using a nationally representative primary care dataset from the UK, from the Clinical Research Practice Datalink. Fibromyalgia patients without prior cancer who were new opioid users were included. Logistic regression, a random forest model and Boruta feature selection were used to identify risk factors related to long-term opioid use. Adjusted ORs (aORs) and feature importance scores were calculated to gauge the strength of these associations. RESULTS: In this study, 28 552 fibromyalgia patients initiating opioids were identified of which 7369 patients (26%) had long-term opioid use. High initial opioid dose (aOR: 31.96, mean decrease accuracy (MDA) 135), history of self-harm (aOR: 2.01, MDA 44), obesity (aOR: 2.43, MDA 36), high deprivation (aOR: 2.00, MDA 31) and substance use disorder (aOR: 2.08, MDA 25) were the factors most strongly associated with long-term use. CONCLUSIONS: High dose of initial opioid prescription, a history of self-harm, obesity, high deprivation, substance use disorder and age were associated with long-term opioid use. This study underscores the importance of recognising these individual risk factors in fibromyalgia patients to better navigate the complexities of opioid use and facilitate patient-centred care.

Development and evaluation of a text analytics algorithm for automated application of national COVID-19 shielding criteria in rheumatology patients.

INTRODUCTION: At the beginning of the COVID-19 pandemic, the UK's Scientific Committee issued extreme social distancing measures, termed 'shielding', aimed at a subpopulation deemed extremely clinically vulnerable to infection. National guidance for risk stratification was based on patients' age, comorbidities and immunosuppressive therapies, including biologics that are not captured in primary care records. This process required considerable clinician time to manually review outpatient letters. Our aim was to develop and evaluate an automated shielding algorithm by text-mining outpatient letter diagnoses and medications, reducing the need for future manual review. METHODS: Rheumatology outpatient letters from a large UK foundation trust were retrieved. Free-text diagnoses were processed using Intelligent Medical Objects software (Concept Tagger), which used interface terminology for each condition mapped to Systematized Medical Nomenclature for Medicine-Clinical Terminology (SNOMED-CT) codes. We developed the Medication Concept Recognition tool (Named Entity Recognition) to retrieve medications' type, dose, duration and status (active/past) at the time of the letter. Age, diagnosis and medication variables were then combined to calculate a shielding score based on the most recent letter. The algorithm's performance was evaluated using clinical review as the gold standard. The time taken to deploy the developed algorithm on a larger patient subset was measured. RESULTS: In total, 5942 free-text diagnoses were extracted and mapped to SNOMED-CT, with 13 665 free-text medications (n=803 patients). The automated algorithm demonstrated a sensitivity of 80% (95% CI: 75%, 85%) and specificity of 92% (95% CI: 90%, 94%). Positive likelihood ratio was 10 (95% CI: 8, 14), negative likelihood ratio was 0.21 (95% CI: 0.16, 0.28) and F1 score was 0.81. Evaluation of mismatches revealed that the algorithm performed correctly against the gold standard in most cases. The developed algorithm was then deployed on records from an additional 15 865 patients, which took 18 hours for data extraction and 1 hour to deploy. DISCUSSION: An automated algorithm for risk stratification has several advantages including reducing clinician time for manual review to allow more time for direct care, improving efficiency and increasing transparency in individual patient communication. It has the potential to be adapted for future public health initiatives that require prompt automated review of hospital outpatient letters.

Psoriatic arthritis: the role of self-reported non-adherence, non-trough drug levels, immunogenicity and conventional synthetic DMARD co-therapy in adalimumab and etanercept response.

Objective: The aim of this study was to assess the relationship between self-reported non-adherence, non-trough drug levels, immunogenicity and conventional synthetic DMARD (csDMARD) co-therapy in TNF inhibitor (TNF-i) drug response in PsA. Methods: Serum samples and adherence questionnaires were collected at baseline, 3, 6 and 12 months for PsA patients prescribed TNF-i. Non-trough adalimumab (ADL) and etanercept (ETN) drug levels were measured at 3 and 6 months using commercially available ELISAs. Clinical response was assessed using PsA response criteria (PsARC) and change in 28-joint DAS (ΔDAS28) between baseline and 3, 6 and 12 months. Results: In 244 PsA patients (52.5% ADL and 47.5% ETN), self-reported non-adherence was associated with PsARC non-response over 12 months using generalized estimating equation (GEE) modelling (P = 0.037). However, there was no significant difference between non-trough ADL or ETN drug levels based on self-reported non-adherence. Higher ETN levels at 3 months were associated with PsARC response at 3 (P = 0.015), 6 (P = 0.037) and 12 months (P = 0.015) and over 12 months using GEE modelling (P = 0.026). Increased ADL drug levels at 3 months were associated with greater ΔDAS28 at 3 months (P = 0.019). ADL anti-drug antibody-positive status was significantly associated with lower 3- and 6-month ADL levels (P < 0.001) and ΔDAS28 and PsARC response at 3, 6 and 12 months. Meanwhile, MTX co-therapy was associated with a reduction in immunogenicity at 3 and 6 months (P = 0.008 and P = 0.024). Conclusion: Although both were associated with reduced response, the objectively measured non-trough drug levels showed more significant associations with drug response than self-reported non-adherence measures.

Trends for opioid prescribing and the impact of the COVID-19 pandemic in patients with rheumatic and musculoskeletal diseases between 2006 and 2021.

OBJECTIVE: To investigate opioid prescribing trends and assess the impact of the COVID-19 pandemic on opioid prescribing in rheumatic and musculoskeletal diseases (RMDs). METHODS: Adult patients with RA, PsA, axial spondyloarthritis (AxSpA), SLE, OA and FM with opioid prescriptions between 1 January 2006 and 31 August 2021 without cancer in UK primary care were included. Age- and gender-standardized yearly rates of new and prevalent opioid users were calculated between 2006 and 2021. For prevalent users, monthly measures of mean morphine milligram equivalents (MME)/day were calculated between 2006 and 2021. To assess the impact of the pandemic, we fitted regression models to the monthly number of prevalent opioid users between January 2015 and August 2021. The time coefficient reflects the trend pre-pandemic and the interaction term coefficient represents the change in the trend during the pandemic. RESULTS: The study included 1 313 519 RMD patients. New opioid users for RA, PsA and FM increased from 2.6, 1.0 and 3.4/10 000 persons in 2006 to 4.5, 1.8 and 8.7, respectively, in 2018 or 2019. This was followed by a fall to 2.4, 1.2 and 5.9, respectively, in 2021. Prevalent opioid users for all RMDs increased from 2006 but plateaued or dropped beyond 2018, with a 4.5-fold increase in FM between 2006 and 2021. In this period, MME/day increased for all RMDs, with the highest for FM (≥35). During COVID-19 lockdowns, RA, PsA and FM showed significant changes in the trend of prevalent opioid users. The trend for FM increased pre-pandemic and started decreasing during the pandemic. CONCLUSION: The plateauing or decreasing trend of opioid users for RMDs after 2018 may reflect the efforts to tackle rising opioid prescribing in the UK. The pandemic led to fewer people on opioids for most RMDs, providing reassurance that there was no sudden increase in opioid prescribing during the pandemic.

Non-trough serum drug levels of adalimumab and etanercept are associated with response in patients with psoriatic arthritis.

OBJECTIVES: Up to 40% of psoriatic arthritis (PsA) patients experience first-line Tumour Necrosis Factor inhibitors (TNF-i) failure. Lower serum drug levels (SDL) have been associated with lower response in autoimmune conditions. This study aimed to: (i) establish the relationship between adalimumab (ADL) and etanercept (ETN) SDL and 3-month response; and (ii) identify optimal non-trough SDL thresholds in PsA. METHODS: PsA patients commencing ADL or ETN were recruited to the UK observational study OUTPASS. Patients were seen pre-TNF-i and at 3 months when response was measured, and non-trough serum samples collected. Response was defined according to the PsARC or EULAR criteria. Descriptive statistics and concentration-effect curves established differences in SDL based on response. Receiver operating characteristics and regression identified optimal SDL thresholds. RESULTS: PsA ETN (n = 97) PsARC and EULAR good responders had significantly higher 3-month SDL compared with non-responders (p= 0.006 and p= 0.020 respectively). Non-trough 3-month ETN SDL discriminated PsARC responders from non-responders (AUC = 0.70), with a threshold of 1.8 µg/ml being 63% specific and 69% sensitive. EULAR good and non-/moderate responders were discriminated with an AUC of 0.65 with a threshold of 2.0 µg/ml being 57% specific and 69% sensitive. ADL prescribed (n = 104) EULAR good responders had significantly higher 3-month SDL (p= 0.049). Non-trough 3-month ADL SDL discriminated EULAR good and non-/moderate responders (AUC = 0.63) with a threshold of 3.6 µg/ml being 48% specific and 81% sensitive. CONCLUSION: Higher 3-month SDL were detected in responders. Interventions to optimise SDL may improve treatment response earlier. This study suggests 3-month SDL thresholds which may be useful in clinical practice to optimise treatment response.

"Take up to eight tablets per day": Incorporating free-text medication instructions into a transparent and reproducible process for preparing drug exposure data for pharmacoepidemiology.

PURPOSE: Routinely collected prescription data provides drug exposure information for pharmacoepidemiology, informing start/stop dates and dosage. Prescribing information includes structured data and unstructured free-text instructions, which can include inherent variability, such as "one to two tablets up to four times a day". Preparing drug exposure data from raw prescriptions to a research ready dataset is rarely fully reported, yet assumptions have considerable implications for pharmacoepidemiology. This may have bigger consequences for "pro re nata" (PRN) drugs. Our aim was, using a worked example of opioids and fracture risk, to examine the impact of incorporating narrative prescribing instructions and subsequent drug preparation assumptions on adverse event rates. METHODS: R-packages for extracting free-text medication prescription instructions in a structured form (doseminer) and an algorithm for transparently processing drug exposure information (drugprepr) were developed. Clinical Practice Research Datalink GOLD was used to define a cohort of adult new opioid users without prior cancer. A retrospective cohort study was performed using data between January 1, 2017 and July 31, 2018. We tested the impact of varying drug preparation assumptions by estimating the risk of opioids on fracture risk using Cox proportional hazards models. RESULTS: During the study window, 60 394 patients were identified with 190 754 opioid prescriptions. Free-text prescribing instruction variability, where there was flexibility in the number of tablets to be administered, was present in 42% prescriptions. Variations in the decisions made during preparing raw data for analysis led to marked differences impacting the event number (n = 303-415) and person years of drug exposure (5619-9832). The distribution of hazard ratios as a function of the decisions ranged from 2.71 (95% CI: 2.31, 3.18) to 3.24 (2.76, 3.82). CONCLUSIONS: Assumptions made during the drug preparation process, especially for those with variability in prescription instructions, can impact results of subsequent risk estimates. The developed R packages can improve transparency related to drug preparation assumptions, in line with best practice advocated by international pharmacoepidemiology guidelines.

EULAR points to consider for therapeutic drug monitoring of biopharmaceuticals in inflammatory rheumatic and musculoskeletal diseases.

OBJECTIVE: To develop EULAR points-to-consider for therapeutic drug monitoring (TDM) of biopharmaceuticals in inflammatory rheumatic and musculoskeletal diseases (RMDs). METHODS: The points-to-consider were developed in accordance with EULAR standardised operation procedures by a multidisciplinary task force from eight European countries, based on a systematic literature review and expert consensus. Level of evidence and strength of the points-to-consider were determined, and mean levels of agreement among the task force were calculated using a 10-point rating scale. RESULTS: Six overarching principles and 13 points-to-consider were formulated. The level of agreement among the task force for the overarching principles and points-to-consider ranged from 8.4 to 9.9.The overarching principles define TDM and its subtypes, and reinforce the underlying pharmacokinetic/pharmacodynamic principles, which are relevant to all biopharmaceutical classes. The points-to-consider highlight the clinical utility of the measurement and interpretation of biopharmaceutical blood concentrations and antidrug antibodies in specific clinical scenarios, including factors that influence these parameters. In general, proactive use of TDM is not recommended but reactive TDM could be considered in certain clinical situations. An important factor limiting wider adoption of TDM is the lack of both high quality trials addressing effectiveness and safety of TDM and robust economic evaluation in patients with RMDs. Future research should focus on providing this evidence, as well as on further understanding of pharmacokinetic and pharmacodynamic characteristics of biopharmaceuticals. CONCLUSION: These points-to-consider are evidence-based and consensus-based statements for the use of TDM of biopharmaceuticals in inflammatory RMDs, addressing the clinical utility of TDM.

Non-trough adalimumab and certolizumab drug levels associated with a therapeutic EULAR response in adherent patients with rheumatoid arthritis.

OBJECTIVES: Interventions aimed at increasing TNF-α inhibitor serum drug levels (SDLs) may improve treatment response; however, previous studies suggesting SDL cut-offs have not accounted for treatment adherence. The aim of this study was to establish the relationship between adalimumab/certolizumab SDLs and EULAR good vs non-/moderate response and to define SDL cut-offs associated with good response in fully adherent patients. METHODS: In a prospective observational study, 475 patients with RA were treated with certolizumab (n = 192) or adalimumab (n = 283). At baseline and 3, 6 and 12 months, patients had 28-joint DAS, self-reported treatment adherence and SDLs measured. Fully adherent patients were analysed as a subgroup. Follow-up data at 3, 6 and 12 months were analysed separately. Median SDLs were compared in good vs non-/moderate response patients and receiver operating characteristics (ROC) curves were used to establish cut-off SDLs. RESULTS: Fully adherent good responders had significantly higher median adalimumab/certolizumab SDLs compared with non-/moderate responders (P = 0.04 and P = 0.0005, respectively). ROC analysis reported 3 month non-trough adalimumab SDLs discriminated good vs non-/moderate response with an area under the curve (AUC) of 0.63 (95% CI 0.52, 0.75), with a cut-off of 7.5 mg/l being 39.1% specific and 80.9% sensitive. Similarly, 3 month non-trough certolizumab SDLs discriminated good vs non-/moderate response with an AUC of 0.65 (95% CI 0.51, 0.78), with a cut-off of 26.0 mg/l being 43.9% specific and 77.8% sensitive. CONCLUSION: In fully adherent patients, higher SDLs are detected in good responders, suggesting that interventions to improve SDLs, such as encouraging adherence, could improve treatment response. The 3 month non-trough SDL cut-offs of 7.5 mg/l for adalimumab and 26.0 mg/l for certolizumab may be useful in clinical practice.

Assessing Immunogenicity of Biologic Drugs in Inflammatory Joint Diseases: Progress Towards Personalized Medicine.

Biologic drugs have greatly improved treatment outcomes of inflammatory joint diseases, but a substantial proportion of patients either do not respond to treatment or lose response over time. Drug immunogenicity, manifested as the formation of anti-drug antibodies (ADAb), constitute a significant clinical problem. Anti-drug antibodies influence the pharmacokinetics of the drug, are associated with reduced clinical efficacy, and an increased risk of adverse events such as infusion reactions. The prevalence of ADAb differs among drugs and diseases, and the detection of ADAb also depends on the assay format. Most data exist for the tumor necrosis factor-alpha inhibitors infliximab and adalimumab, with a frequency of ADAb that ranges from 10 to 60% across studies. Measurement of ADAb and serum drug concentrations, therapeutic drug monitoring, has been suggested as a strategy to optimize therapy with biologic drugs. Although the recent randomized clinical Norwegian Drug Monitoring (NOR-DRUM) trials show promise towards a personalized medicine prescribing approach by therapeutic drug monitoring, several challenges remain. A plethora of assay formats, with widely differing properties, is currently used for measuring ADAb. Comparing results between different assays and laboratories is difficult, which complicates the development of cut-offs necessary for guidelines and the implementation of ADAb measurements in clinical practice. With the possible exception of infliximab, limited data on clinical relevance and cost effectiveness exist to support therapeutic drug monitoring as a routine clinical strategy to monitor biologic drugs in inflammatory joint diseases. The aim of this review is to provide an overview of the characteristics and prevalence of ADAb, predisposing factors to ADAb formation, commonly used assessment methods, clinical consequences of ADAb, and the potential implications of ADAb assessments for everyday treatment of inflammatory joint diseases.

Therapeutic drug monitoring of biopharmaceuticals in inflammatory rheumatic and musculoskeletal disease: a systematic literature review informing EULAR points to consider.

The objectives of this review were to collect and summarise evidence on therapeutic drug monitoring (TDM) of biopharmaceuticals in inflammatory rheumatic and musculoskeletal diseases and to inform the EULAR Task Force for the formulation of evidence-based points to consider. A systematic literature review (SLR) was performed, covering technical aspects and (clinical) utility of TDM, to answer 13 research questions. MEDLINE, Embase and Cochrane were searched until July 2020. American College of Rheumatology and EULAR abstracts were also considered for inclusion. Data were extracted in evidence tables and risk of bias assessment was performed. For the search on technical aspects, 678 records were identified, of which 22 papers were selected. For the clinical utility search, 3846 records were identified, of which 108 papers were included. Patient-related factors associated with biopharmaceutical blood concentrations included body weight, methotrexate comedication and disease activity. The identification of a target range was hampered by study variability, mainly disease activity measures and study type. Evidence was inconsistent for multiple clinical situations in which TDM is currently applied. However, for some particular scenarios, including prediction of future treatment response, non-response to treatment, tapering and hypersensitivity reactions, robust evidence was found. There is currently no evidence for routine use of proactive TDM, in part because published cost-effectiveness analyses do not incorporate the current landscape of biopharmaceutical costs and usage. This SLR yields evidence in favour of TDM of biopharmaceuticals in some clinical scenarios, but evidence is insufficient to support implementation of routine use of TDM.

Development and external validation of prediction models for adverse health outcomes in rheumatoid arthritis: A multinational real-world cohort analysis.

BACKGROUND: Identification of rheumatoid arthritis (RA) patients at high risk of adverse health outcomes remains a major challenge. We aimed to develop and validate prediction models for a variety of adverse health outcomes in RA patients initiating first-line methotrexate (MTX) monotherapy. METHODS: Data from 15 claims and electronic health record databases across 9 countries were used. Models were developed and internally validated on Optum® De-identified Clinformatics® Data Mart Database using L1-regularized logistic regression to estimate the risk of adverse health outcomes within 3 months (leukopenia, pancytopenia, infection), 2 years (myocardial infarction (MI) and stroke), and 5 years (cancers [colorectal, breast, uterine] after treatment initiation. Candidate predictors included demographic variables and past medical history. Models were externally validated on all other databases. Performance was assessed using the area under the receiver operator characteristic curve (AUC) and calibration plots. FINDINGS: Models were developed and internally validated on 21,547 RA patients and externally validated on 131,928 RA patients. Models for serious infection (AUC: internal 0.74, external ranging from 0.62 to 0.83), MI (AUC: internal 0.76, external ranging from 0.56 to 0.82), and stroke (AUC: internal 0.77, external ranging from 0.63 to 0.95), showed good discrimination and adequate calibration. Models for the other outcomes showed modest internal discrimination (AUC < 0.65) and were not externally validated. INTERPRETATION: We developed and validated prediction models for a variety of adverse health outcomes in RA patients initiating first-line MTX monotherapy. Final models for serious infection, MI, and stroke demonstrated good performance across multiple databases and can be studied for clinical use. FUNDING: This activity under the European Health Data & Evidence Network (EHDEN) has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 806968. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA.

2022 EULAR points to consider for remote care in rheumatic and musculoskeletal diseases.

BACKGROUND: Remote care and telehealth have the potential to expand healthcare access, and the COVID-19 pandemic has called for alternative solutions to conventional face-to-face follow-up and monitoring. However, guidance is needed on the integration of telehealth into clinical care of people with rheumatic and musculoskeletal diseases (RMD). OBJECTIVE: To develop EULAR points to consider (PtC) for the development, prioritisation and implementation of telehealth for people with RMD. METHODS: A multidisciplinary EULAR task force (TF) of 30 members from 14 European countries was established, and the EULAR standardised operating procedures for development of PtC were followed. A systematic literature review was conducted to support the TF in formulating the PtC. The level of agreement among the TF was established by anonymous online voting. RESULTS: Four overarching principles and nine PtC were formulated. The use of telehealth should be tailored to patient's needs and preferences. The healthcare team should have adequate equipment and training and have telecommunication skills. Telehealth can be used in screening for RMD as preassessment in the referral process, for disease monitoring and regulation of medication dosages and in some non-pharmacological interventions. People with RMD should be offered training in using telehealth, and barriers should be resolved whenever possible.The level of agreement to each statement ranged from 8.5 to 9.8/10. CONCLUSION: The PtC have identified areas where telehealth could improve quality of care and increase healthcare access. Knowing about drivers and barriers of telehealth is a prerequisite to successfully establish remote care approaches in rheumatologic clinical practice.