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.

Reliability, validity, and responsiveness of a smartphone-based manikin to support pain self-reporting.

Introduction: Many people worldwide suffer from chronic pain. Improving our knowledge on chronic pain prevalence and management requires methods to collect pain self-reports in large populations. Smartphone-based tools could aid data collection by allowing people to use their own device, but the measurement properties of such tools are largely unknown. Objectives: To assess the reliability, validity, and responsiveness of a smartphone-based manikin to support pain self-reporting. Methods: We recruited people with fibromyalgia, rheumatoid arthritis, and/or osteoarthritis and access to a smartphone and the internet. Data collection included the Global Pain Scale at baseline and follow-up, and 30 daily pain drawings completed on a 2-dimensional, gender-neutral manikin. After deriving participants' pain extent from their manikin drawings, we evaluated convergent and discriminative validity, test-retest reliability, and responsiveness and assessed findings against internationally agreed criteria for good measurement properties. Results: We recruited 131 people; 104 were included in the full sample, submitting 2185 unique pain drawings. Manikin-derived pain extent had excellent test-retest reliability (intraclass correlation coefficient, 0.94), moderate convergent validity (ρ, 0.46), and an ability to distinguish fibromyalgia and osteoarthritis from rheumatoid arthritis (F statistics, 30.41 and 14.36, respectively; P < 0.001). Responsiveness was poor (ρ, 0.2; P, 0.06) and did not meet the respective criterion for good measurement properties. Conclusion: Our findings suggest that smartphone-based manikins can be a reliable and valid method for pain self-reporting, but that further research is warranted to explore, enhance, and confirm the ability of such manikins to detect a change in pain over time.

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.

The epidemiology of psoriatic arthritis in the UK: a health intelligence analysis of UK Primary Care Electronic Health Records 1991-2020.

OBJECTIVES: Epidemiological estimates of psoriatic arthritis (PsA) underpin the provision of healthcare, research, and the work of government, charities and patient organizations. Methodological problems impacting prior estimates include small sample sizes, incomplete case ascertainment, and representativeness. We developed a statistical modelling strategy to provide contemporary prevalence and incidence estimates of PsA from 1991 to 2020 in the UK. METHODS: Data from Clinical Practice Research Datalink (CPRD) were used to identify cases of PsA between 1st January 1991 and 31st December 2020. To optimize ascertainment, we identified cases of Definite PsA (≥1 Read code for PsA) and Probable PsA (satisfied a bespoke algorithm). Standardized annual rates were calculated using Bayesian multilevel regression with post-stratification to account for systematic differences between CPRD data and the UK population, based on age, sex, socioeconomic status and region of residence. RESULTS: A total of 26293 recorded PsA cases (all definitions) were identified within the study window (77.9% Definite PsA). Between 1991 and 2020 the standardized prevalence of PsA increased twelve-fold from 0.03 to 0.37. The standardized incidence of PsA per 100,000 person years increased from 8.97 in 1991 to 15.08 in 2020, an almost 2-fold increase. Over time, rates were similar between the sexes, and across socioeconomic status. Rates were strongly associated with age, and consistently highest in Northern Ireland. CONCLUSION: The prevalence and incidence of PsA recorded in primary care has increased over the last three decades. The modelling strategy presented can be used to provide contemporary prevalence estimates for musculoskeletal disease using routinely collected primary care data.

"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.

Remote sampling of biomarkers of inflammation with linked patient generated health data in patients with rheumatic and musculoskeletal diseases: an Ecological Momentary Assessment feasibility study.

BACKGROUND: People with rheumatic diseases experience troublesome fluctuations in fatigue. Debated causes include pain, mood and inflammation. To determine the relationships between these potential causes, serial assessments are required but are methodologically challenging. This mobile health (mHealth) study explored the viability of using a smartphone app to collect patient-reported symptoms with contemporaneous Dried Blood Spot Sampling (DBSS) for inflammation. METHODS: Over 30 days, thirty-eight participants (12 RA, 13 OA, and 13 FM) used uMotif, a smartphone app, to report fatigue, pain and mood, on 5-point ordinal scales, twice daily. Daily DBSS, from which C-reactive Protein (CRP) values were extracted, were completed on days 1-7, 14 and 30. Participant engagement was determined based on frequency of data entry and ability to calculate within- and between-day symptom changes. DBSS feasibility and engagement was determined based on the proportion of samples returned and usable for extraction, and the number of days between which between-day changes in CRP which could be calculated (days 1-7). RESULTS: Fatigue was reported at least once on 1085/1140 days (95.2%). Approximately 65% of within- and between-day fatigue changes could be calculated. Rates were similar for pain and mood. A total of 287/342 (83.9%) DBSS, were returned, and all samples were viable for CRP extraction. Fatigue, pain and mood varied considerably, but clinically meaningful (≥ 5 mg/L) CRP changes were uncommon. CONCLUSIONS: Embedding DBSS in mHealth studies will enable researchers to obtain serial symptom assessments with matched biological samples. This provides exciting opportunities to address hitherto unanswerable questions, such as elucidating the mechanisms of fatigue fluctuations.

Using patient-generated health data in clinical practice: How timing influences its function in rheumatology outpatient consultations.

OBJECTIVE: Utilizing patient-generated health data (PGHD) in clinical consultations and informing clinical and shared decision-making processes has the potential to improve clinical practice but has proven challenging to implement. Looking at consultations between people with rheumatoid arthritis (RA) and rheumatologists, this study examines when and how daily PGHD was discussed in outpatient consultations. METHODS: We conducted a secondary qualitative analysis of 17 audio-recorded research outpatient consultations using thematic and interactional approaches. RESULTS: Clinicians decided when to look at the PGHD and what symptoms to prioritise during the consultation. When PGHD was introduced early in consultations, it was usually used to invite patients to collaborate (elicit new information). When introduced later, PGHD was used to corroborate patient accounts and to convince the patient about proposed actions and treatments. Clinicians occasionally disregarded PGHD if it did not fit into their clinical assessment. CONCLUSION: The time that PGHD is introduced may influence how PGHD is used in consultations. Further research is needed to understand how best to empower patients to discuss PGHD. PRACTICE IMPLICATIONS: Educating patients and clinicians about the importance of timing and strategies when using PGHD in consultations may help promote shared decision-making.

Opioid prescribing among new users for non-cancer pain in the USA, Canada, UK, and Taiwan: A population-based cohort study.

BACKGROUND: The opioid epidemic in North America has been driven by an increase in the use and potency of prescription opioids, with ensuing excessive opioid-related deaths. Internationally, there are lower rates of opioid-related mortality, possibly because of differences in prescribing and health system policies. Our aim was to compare opioid prescribing rates in patients without cancer, across 5 centers in 4 countries. In addition, we evaluated differences in the type, strength, and starting dose of medication and whether these characteristics changed over time. METHODS AND FINDINGS: We conducted a retrospective multicenter cohort study of adults who are new users of opioids without prior cancer. Electronic health records and administrative health records from Boston (United States), Quebec and Alberta (Canada), United Kingdom, and Taiwan were used to identify patients between 2006 and 2015. Standard dosages in morphine milligram equivalents (MMEs) were calculated according to The Centers for Disease Control and Prevention. Age- and sex-standardized opioid prescribing rates were calculated for each jurisdiction. Of the 2,542,890 patients included, 44,690 were from Boston (US), 1,420,136 Alberta, 26,871 Quebec (Canada), 1,012,939 UK, and 38,254 Taiwan. The highest standardized opioid prescribing rates in 2014 were observed in Alberta at 66/1,000 persons compared to 52, 51, and 18/1,000 in the UK, US, and Quebec, respectively. The median MME/day (IQR) at initiation was highest in Boston at 38 (20 to 45); followed by Quebec, 27 (18 to 43); Alberta, 23 (9 to 38); UK, 12 (7 to 20); and Taiwan, 8 (4 to 11). Oxycodone was the first prescribed opioid in 65% of patients in the US cohort compared to 14% in Quebec, 4% in Alberta, 0.1% in the UK, and none in Taiwan. One of the limitations was that data were not available from all centers for the entirety of the 10-year period. CONCLUSIONS: In this study, we observed substantial differences in opioid prescribing practices for non-cancer pain between jurisdictions. The preference to start patients on higher MME/day and more potent opioids in North America may be a contributing cause to the opioid epidemic.

Time trends and prescribing patterns of opioid drugs in UK primary care patients with non-cancer pain: A retrospective cohort study.

BACKGROUND: The US opioid epidemic has led to similar concerns about prescribed opioids in the UK. In new users, initiation of or escalation to more potent and high dose opioids may contribute to long-term use. Additionally, physician prescribing behaviour has been described as a key driver of rising opioid prescriptions and long-term opioid use. No studies to our knowledge have investigated the extent to which regions, practices, and prescribers vary in opioid prescribing whilst accounting for case mix. This study sought to (i) describe prescribing trends between 2006 and 2017, (ii) evaluate the transition of opioid dose and potency in the first 2 years from initial prescription, (iii) quantify and identify risk factors for long-term opioid use, and (iv) quantify the variation of long-term use attributed to region, practice, and prescriber, accounting for case mix and chance variation. METHODS AND FINDINGS: A retrospective cohort study using UK primary care electronic health records from the Clinical Practice Research Datalink was performed. Adult patients without cancer with a new prescription of an opioid were included; 1,968,742 new users of opioids were identified. Mean age was 51 ± 19 years, and 57% were female. Codeine was the most commonly prescribed opioid, with use increasing 5-fold from 2006 to 2017, reaching 2,456 prescriptions/10,000 people/year. Morphine, buprenorphine, and oxycodone prescribing rates continued to rise steadily throughout the study period. Of those who started on high dose (120-199 morphine milligram equivalents [MME]/day) or very high dose opioids (≥200 MME/day), 10.3% and 18.7% remained in the same MME/day category or higher at 2 years, respectively. Following opioid initiation, 14.6% became long-term opioid users in the first year. In the fully adjusted model, the following were associated with the highest adjusted odds ratios (aORs) for long-term use: older age (≥75 years, aOR 4.59, 95% CI 4.48-4.70, p < 0.001; 65-74 years, aOR 3.77, 95% CI 3.68-3.85, p < 0.001, compared to <35 years), social deprivation (Townsend score quintile 5/most deprived, aOR 1.56, 95% CI 1.52-1.59, p < 0.001, compared to quintile 1/least deprived), fibromyalgia (aOR 1.81, 95% CI 1.49-2.19, p < 0.001), substance abuse (aOR 1.72, 95% CI 1.65-1.79, p < 0.001), suicide/self-harm (aOR 1.56, 95% CI 1.52-1.61, p < 0.001), rheumatological conditions (aOR 1.53, 95% CI 1.48-1.58, p < 0.001), gabapentinoid use (aOR 2.52, 95% CI 2.43-2.61, p < 0.001), and MME/day at initiation (aOR 1.08, 95% CI 1.07-1.08, p < 0.001). After adjustment for case mix, 3 of the 10 UK regions (North West [16%], Yorkshire and the Humber [15%], and South West [15%]), 103 practices (25.6%), and 540 prescribers (3.5%) had a higher proportion of patients with long-term use compared to the population average. This study was limited to patients prescribed opioids in primary care and does not include opioids available over the counter or prescribed in hospitals or drug treatment centres. CONCLUSIONS: Of patients commencing opioids on very high MME/day (≥200), a high proportion stayed in the same category for a subsequent 2 years. Age, deprivation, prescribing factors, comorbidities such as fibromyalgia, rheumatological conditions, recent major surgery, and history of substance abuse, alcohol abuse, and self-harm/suicide were associated with long-term opioid use. Despite adjustment for case mix, variation across regions and especially practices and prescribers in high-risk prescribing was observed. Our findings support greater calls for action for reduction in practice and prescriber variation by promoting safe practice in opioid prescribing.

Remote symptom monitoring integrated into electronic health records: A systematic review.

OBJECTIVE: People with long-term conditions require serial clinical assessments. Digital patient-reported symptoms collected between visits can inform these, especially if integrated into electronic health records (EHRs) and clinical workflows. This systematic review identified and summarized EHR-integrated systems to remotely collect patient-reported symptoms and examined their anticipated and realized benefits in long-term conditions. MATERIALS AND METHODS: We searched Medline, Web of Science, and Embase. Inclusion criteria were symptom reporting systems in adults with long-term conditions; data integrated into the EHR; data collection outside of clinic; data used in clinical care. We synthesized data thematically. Benefits were assessed against a list of outcome indicators. We critically appraised studies using the Mixed Methods Appraisal Tool. RESULTS: We included 12 studies representing 10 systems. Seven were in oncology. Systems were technically and functionally heterogeneous, with the majority being fully integrated (data viewable in the EHR). Half of the systems enabled regular symptom tracking between visits. We identified 3 symptom report-guided clinical workflows: Consultation-only (data used during consultation, n = 5), alert-based (real-time alerts for providers, n = 4) and patient-initiated visits (n = 1). Few author-described anticipated benefits, primarily to improve communication and resultant health outcomes, were realized based on the study results, and were only supported by evidence from early-stage qualitative studies. Studies were primarily feasibility and pilot studies of acceptable quality. DISCUSSION AND CONCLUSIONS: EHR-integrated remote symptom monitoring is possible, but there are few published efforts to inform development of these systems. Currently there is limited evidence that this improves care and outcomes, warranting future robust, quantitative studies of efficacy and effectiveness.

Ability to Predict New-Onset Psychological Distress Using Routinely Collected Health Data: A Population-Based Cohort Study of Women Diagnosed With Breast Cancer.

Objectives: The primary objective of this study was to identify the predictors of new-onset psychological distress available in routinely collected administrative health databases for women diagnosed with breast cancer. The secondary objective was to explore whether the predictors vary based on the period of cancer care. Methods: A population-based cohort study followed 16,495 female patients with newly diagnosed breast cancer who did not experience psychological distress during the 14 months before breast cancer surgery. The incidence of psychological distress was reported overall and by type of mental health problem. Time-varying Cox proportional hazards models were developed to identify predictors of new-onset psychological distress during 2 key periods of cancer care: (1) hospital-based treatment during which women undergo treatment with breast surgery, chemotherapy, and/or radiation, and (2) 1-year transitional survivorship when women begin follow-up care. Results: The incidence of psychological distress was 16% within each period. Anxiety was present in 85.1% and 65.5% of new cases during hospital-based treatment and transitional survivorship, respectively. Predictors during both periods were younger age, receipt of axillary lymph node dissection, rheumatologic disease, and baseline menopausal symptoms, as well as new opioid dispensations, emergency department visits, and hospital contacts that occurred during follow-up. Other predictors varied based on the period of cancer care. More advanced breast cancer and type of treatment were associated with onset of psychological distress during hospital-based treatment. Psychological distress during transitional survivorship was predicted by diagnosis of localized breast disease, shorter duration of hospital-based treatment, receipt of additional hospital-based treatment in survivorship, and newly diagnosed comorbidities or symptoms. Conclusions: This study identified the predictors of new-onset psychological distress available in routinely collected administrative health databases, and showed how predictors change between hospital-based treatment and transitional survivorship periods. The results highlight the importance of developing predictive models tailored to the period of cancer care.

Drug safety and immunogenicity of tumour necrosis factor inhibitors: the story so far.

TNF-α inhibitor (TNFi) therapies have transformed the treatment of several rheumatic musculoskeletal diseases. However, the majority of TNFi's are immunogenic and consequent anti-drug antibodies formation can impact on both treatment efficacy and safety. Several controversies exist in the area of immunogenicity of TNFis and drug safety. While anti-drug antibodies to TNFis have been described in association with infusion reactions; serious adverse events (AEs) such as thromboembolic events, lupus-like syndrome, paradoxical AEs, for example, vasculitis-like events and other autoimmune manifestations have also been reported. The expansion of the biologic armamentarium, new treatment strategies such as introduction/switching to biosimilars and cost-saving approaches such as TNFi tapering, may all have a potential impact on immunogenicity and clinical sequelae. In this review we evaluate how evolution of biologics relates to drug safety and immunogenicity, appraise relevant evidence from trials, spontaneous pharmacovigilance and observational studies and outline the areas of uncertainty that still exist.

2017 EULAR recommendations for a core data set to support observational research and clinical care in rheumatoid arthritis.

Personalised medicine, new discoveries and studies on rare exposures or outcomes require large samples that are increasingly difficult for any single investigator to obtain. Collaborative work is limited by heterogeneities, both what is being collected and how it is defined. To develop a core set for data collection in rheumatoid arthritis (RA) research which (1) allows harmonisation of data collection in future observational studies, (2) acts as a common data model against which existing databases can be mapped and (3) serves as a template for standardised data collection in routine clinical practice to support generation of research-quality data. A multistep, international multistakeholder consensus process was carried out involving voting via online surveys and two face-to-face meetings. A core set of 21 items ('what to collect') and their instruments ('how to collect') was agreed: age, gender, disease duration, diagnosis of RA, body mass index, smoking, swollen/tender joints, patient/evaluator global, pain, quality of life, function, composite scores, acute phase reactants, serology, structural damage, treatment and comorbidities. The core set should facilitate collaborative research, allow for comparisons across studies and harmonise future data from clinical practice via electronic medical record systems.

Risks of smoking and benefits of smoking cessation on hospitalisations for cardiovascular events and respiratory infection in patients with rheumatoid arthritis: a retrospective cohort study using the Clinical Practice Research Datalink.

OBJECTIVES: To investigate the associations between smoking status, smoking cessation and hospitalisations for cardiovascular events (CVE) and respiratory tract infections (RTI) in an inception cohort of patients with rheumatoid arthritis (RA). METHODS: The study was set within UK primary care electronic health records (the Clinical Practice Research Datalink) linked to hospital inpatient data (Hospital Episode Statistics). Patients with RA were followed from diagnosis to hospitalisation with a record of CVE or RTI, leaving their general practice, death, or 10 January 2012, whichever was earliest. Smoking status (never, current, former) was defined using primary care data and could vary over time. Survival analysis was performed using Cox regression (first event) and conditional risk set models (multiple RTIs). RESULTS: 5677 patients were included in the cohort: 68% female, median age 61 years. The age-adjusted and sex-adjusted risks of hospitalisation for CVE or RTI were more than twice as high in current vs never smokers (CVE HR (95% CI) 2.19 (1.44 to 3.31); RTI 2.18 (1.71 to 2.78)). The risks for both outcomes were significantly higher in current compared with former smokers (CVE 1.51 (1.04 to 2.19), RTI 1.29 (1.04 to 1.61)). For each additional year of smoking cessation, the risk of first CVE and RTI hospitalisation fell significantly, approximately 25% and 15% respectively in the adjusted models. CONCLUSIONS: Patients with RA who smoke have an increased risk of hospitalisation with CVE or RTI compared with never and former smokers. The risk decreases for each additional year of smoking cessation. Patients with RA who smoke should be advised to stop smoking.

Spectrum of lymphomas across different drug treatment groups in rheumatoid arthritis: a European registries collaborative project.

BACKGROUND: Lymphomas comprise a heterogeneous group of malignant diseases with highly variable prognosis. Rheumatoid arthritis (RA) is associated with a twofold increased risk of both Hodgkin's lymphoma (HL) and non-Hodgkin's lymphoma (NHL). It is unknown whether treatment with biologic disease-modifying antirheumatic drugs (bDMARDs) affect the risk of specific lymphoma subtypes. METHODS: Patients never exposed to (bionaïve) or ever treated with bDMARDs from 12 European biologic registers were followed prospectively for the occurrence of first ever histologically confirmed lymphoma. Patients were considered exposed to a bDMARD after having received the first dose. Lymphomas were attributed to the most recently received bDMARD. RESULTS: Among 124 997 patients (mean age 59 years; 73.7% female), 533 lymphomas were reported. Of these, 9.5% were HL, 83.8% B-cell NHL and 6.8% T-cell NHL. No cases of hepatosplenic T-cell lymphoma were observed. Diffuse large B-cell lymphoma (DLBCL) was the most frequent B-cell NHL subtype (55.8% of all B-cell NHLs). The subtype distributions were similar between bionaïve patients and those treated with tumour necrosis factor inhibitors (TNFi). For other bDMARDs, the numbers of cases were too small to draw any conclusions. Patients with RA developed more DLBCLs and less chronic lymphocytic leukaemia compared with the general population. CONCLUSION: This large collaborative analysis of European registries has successfully collated subtype information on 533 lymphomas. While the subtype distribution differs between RA and the general population, there was no evidence of any modification of the distribution of lymphoma subtypes in patients with RA treated with TNFi compared with bionaïve patients.

Predictors of distress in female breast cancer survivors: a systematic review.

PURPOSE: Unmanaged distress has been shown to adversely affect survival and quality of life in breast cancer survivors. Fortunately, distress can be managed and even prevented with appropriate evidence-based interventions. Therefore, the objective of this systematic review was to synthesize the published literature around predictors of distress in female breast cancer survivors to help guide targeted intervention to prevent distress. METHODS: Relevant studies were located by searching MEDLINE, Embase, PsycINFO, and CINAHL databases. Significance and directionality of associations for commonly assessed candidate predictors (n ≥ 5) and predictors shown to be significant (p ≤ 0.05) by at least two studies were summarized descriptively. Predictors were evaluated based on the proportion of studies that showed a significant and positive association with the presence of distress. RESULTS: Forty-two studies met the target criteria and were included in the review. Breast cancer and treatment-related predictors were more advanced cancer at diagnosis, treatment with chemotherapy, longer primary treatment duration, more recent transition into survivorship, and breast cancer recurrence. Manageable treatment-related symptoms associated with distress included menopausal/vasomotor symptoms, pain, fatigue, and sleep disturbance. Sociodemographic characteristics that increased the risk of distress were younger age, non-Caucasian ethnicity, being unmarried, and lower socioeconomic status. Comorbidities, history of mental health problems, and perceived functioning limitations were also associated. Modifiable predictors of distress were lower physical activity, lower social support, and cigarette smoking. CONCLUSIONS: This review established a set of evidence-based predictors that can be used to help identify women at higher risk of experiencing distress following completion of primary breast cancer treatment.

Drug-specific risk and characteristics of lupus and vasculitis-like events in patients with rheumatoid arthritis treated with TNFi: results from BSRBR-RA.

OBJECTIVE: To compare the risk of lupus-like events (LLEs) and vasculitis-like events (VLEs) in tumour necrosis factor-α inhibitor (TNFi)-treated patients with rheumatoid arthritis (RA) to those receiving non-biological disease-modifying antirheumatic drugs (nbDMARDs). METHODS: Patients were recruited to the British Society for Rheumatology Biologics Register-RA, a national prospective cohort study. Two cohorts recruited between 2001 and 2015: (1) patients starting first TNFi (adalimumab, etanercept, infliximab and certolizumab) (n=12 937) and (2) biological-naïve comparison cohort receiving nbDMARDs (n=3673). The risk of an event was compared between the two cohorts using Cox proportional-hazard models, adjusted using propensity scores. Rates of LLE/VLE were compared between TNFi and nbDMARD patients. RESULTS: The crude incidence rates for LLEs were: TNFi 10/10 000 patient-years (pyrs) (95% CI 8 to 13) and nbDMARD 2/10 000 pyrs (95% CI 1 to 6); for VLEs: TNFi 15/10 000 pyrs (95% CI 12 to 19) and nbDMARD 7/10 000 pyrs (95% CI 4 to 12). The risk of both events was highest in the first year of TNFi treatment. After adjusting for differences in baseline characteristics, there was no difference in risk of LLEs (adjHR 1.86; 95% CI 0.52 to 6.58) or VLEs (adjHR 1.27; 95% CI 0.40 to 4.04) for TNFi compared to nbDMARD-treated patients. Infliximab conferred the highest overall risk, followed by etanercept, although 95% CIs overlapped following adjustment. CONCLUSIONS: In one of the largest biological registers, the absolute risk of both events is low. The addition of TNFi to nbDMARD does not alter the risk of either event in patients with RA selected for TNFi. This is the first study to assess the risk of these outcomes in a prospective, observational cohort.

Relationship between exposure to tumour necrosis factor inhibitor therapy and incidence and severity of myocardial infarction in patients with rheumatoid arthritis.

OBJECTIVES: Patients with rheumatoid arthritis (RA) are at increased risk of myocardial infarction (MI) compared with subjects without RA, with the increased risk driven potentially by inflammation. Tumour necrosis factor inhibitors (TNFi) may modulate the risk and severity of MI. We compared the risk and severity of MI in patients treated with TNFi with that in those receiving synthetic disease-modifying antirheumatic drugs (sDMARDs). METHODS: This analysis included patients with RA recruited from 2001 to 2009 to the British Society for Rheumatology Biologics Register for Rheumatoid Arthritis starting TNFi (etanercept/infliximab/adalimumab) and a biologic-naïve comparator cohort receiving sDMARD. All patients were followed via physician and patient questionnaires and national death register linkage. Additionally, all patients were linked to the Myocardial Ischaemia National Audit Project, a national registry of hospitalisations for MI. Patients were censored at first verified MI, death, 90 days following TNFi discontinuation, last physician follow-up or 20 April 2010, whichever came first. The risk of first MI was compared between cohorts using COX regression, adjusted with propensity score deciles (PD). MI phenotype and severity were compared using descriptive statistics. 6-month mortality post MI was compared using logistic regression. RESULTS: 252 verified first MIs were analysed: 58 in 3058 patients receiving sDMARD and 194 in 11 200 patients receiving TNFi (median follow-up per person 3.5 years and 5.3 years, respectively). The PD-adjusted HR of MI in TNFi referent to sDMARD was 0.61 (95% CI 0.41 to 0.89). No statistically significant differences in MI severity or mortality were observed between treatment groups. CONCLUSIONS: Patients with RA receiving TNFi had a decreased risk of MI compared with patients with RA receiving sDMARD therapy over the medium term. This might be attributed to a direct action of TNFi on the atherosclerotic process or better overall disease control.

Risk of invasive melanoma in patients with rheumatoid arthritis treated with biologics: results from a collaborative project of 11 European biologic registers.

OBJECTIVES: Some studies have reported a possible association between exposure to tumour necrosis factor (TNF) inhibitors and an increased risk of melanoma. The aim of this study was to investigate the incidence of invasive cutaneous melanomas in patients with rheumatoid arthritis (RA) treated with TNF inhibitors (TNFi), other biologic disease modifying drugs and non-biologic therapy. METHODS: Eleven biologic registers from nine European countries participated in this collaborative project. According to predefined exposure definitions, cohorts of patients with RA were selected. Using the country-specific general population of each register as reference, age, sex and calendar year standardised incidence ratios (SIRs) of invasive histology-confirmed cutaneous melanoma were calculated within each register. Pooled SIR and incidence rate ratios (IRRs) comparing biologic cohorts to biologic-naïve were calculated across countries by taking the size of the register into account. RESULTS: Overall 130 315 RA patients with a mean age of 58 years contributing 579 983 person-years were available for the analysis and 287 developed a first melanoma. Pooled SIRs for biologic-naïve, TNFi and rituximab-exposed patients were 1.1 (95% CI 0.9 to 1.4), 1.2 (0.99 to 1.6) and 1.3 (0.6 to 2.6), respectively. Incidence rates in tocilizumab and abatacept-exposed patients were also not significantly increased. IRR versus biologic-naïve patients were: TNFi 1.1 (95% CI 0.8 to 1.6); rituximab 1.2 (0.5 to 2.9). CONCLUSIONS: This large European collaborative project did not confirm an overall increased risk of melanoma following exposure to TNFi.