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Trishna Rathod-Mistry,1 George Peat,2,3 Tuhina Neogi,4 Martin J Thomas2,5 1Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK; 2Primary Care Centre Versus Arthritis, School of Medicine, Keele University, Staffordshire, UK; 3Centre for Applied Health & Social Care Research (CARe), Sheffield Hallam University, Sheffield, UK; 4Department of Medicine, Section of Rheumatology, Boston University School of Medicine, Boston, MA, USA; 5Haywood Academic Rheumatology Centre, Midlands Partnership University NHS Foundation Trust, Haywood Hospital, Staffordshire, UKCorrespondence: Martin J Thomas, Primary Care Centre Versus Arthritis, School of Medicine, Keele University, Staffordshire, ST5 5BG, UK, Tel +44 1782 734874, Fax +44 1782 734719, Email m.thomas@keele.ac.ukObjective: To evaluate bias and precision of exposure-outcome effect estimates from three control sampling strategies in a case-crossover study.Methods: Online case-crossover study investigating eight physical activity-related triggers for acute flares in knee osteoarthritis. Exposures were measured in hazard periods (≤ 24 hours before self-declared flare onset). Control period exposure was measured in three ways: (1) four scheduled questionnaires over 13-weeks, (2) “usual” physical activity levels ascertained at baseline, (3) over three days before flare onset. Derived odds ratios, 95% confidence intervals and standard errors were compared.Results: Of 744 participants (mean age 62.1 [SD 10.2] years; 61% female), 493 reported 714 flares. Selecting controls from scheduled questionnaires, independent of hazard periods, yielded predominantly odds ratios in the expected direction (exposure “a lot” versus exposure “not at all”, range: 0.57– 3.22). When controls were sampled at baseline (range: 0.01– 1.42) or immediately before a flare (range: 0.30– 1.27) most odds ratio estimates were inverted. Standard errors of the log odds ratios were smallest when controls were sampled from scheduled questionnaires (range: 0.264– 0.473) compared to controls sampled at baseline (range: 0.267– 0.589) or immediately before a flare (range: 0.319– 0.621).Conclusion: Our findings are sensitive to control sample selection. Under certain conditions, different patterns could be attributed to over reporting and social desirability bias, where people may want to present themselves more positively about their “usual” physical activity levels, at baseline. Exposure measurement at the time of a flare may be less precise and more susceptible to recall bias due to systematically reporting exposures differently during a flare, compared to control measurement independent of flares.Keywords: osteoarthritis, flare, pain, case-crossover, sampling, knee

Dahai Yu,1 Matthew Missen,1 Kelvin P Jordan,1 John J Edwards,1 James Bailey,1 Ross Wilkie,1 Justine Fitzpatrick,2 Nuzhat Ali,2 Paul Niblett,2 George Peat1 1Primary Care Centre versus Arthritis, School of Medicine, Keele University, Keele, Staffordshire, UK; 2Office for Health Improvement and Disparities, Department of Health and Social Care, London, UKCorrespondence: Dahai Yu, Email d.yu@keele.ac.ukPurpose: To compare estimates of annual person-consulting incidence and prevalence of low back pain (LBP) and osteoarthritis for two national English electronic health record databases (Clinical Practice Research Datalink (CPRD) Aurum and CPRD GOLD).Patients and Methods: Retrospective, population-based, longitudinal cohort study. LBP and osteoarthritis cases were defined using established codelists in people aged ≥ 15 and ≥ 45 years, respectively. Incident cases were new recorded cases in a given calendar year with no relevant consultation in the previous 3 years (denominator = exact person-time in the same calendar year for the at-risk population). Prevalent cases were individuals with ≥ 1 consultation for the condition of interest recorded in a given calendar year, irrespective of prior consultations for the same condition (denominator = all patients with complete registration history in the previous 3 years). We estimated age-sex standardised incidence and annual (12-month period) prevalence for both conditions in 2000– 2019, overall, and by sex, age group, and region.Results: Standardised incidence and prevalence of LBP from Aurum were lower than those from GOLD until 2014, after which estimates were similar. Both databases showed recent declines in incidence and prevalence of LBP: declines began earlier in GOLD (after 2012– 2014) than Aurum (after 2014– 2015). Standardised incidence (after 2011) and prevalence of osteoarthritis (after 2003) were higher in Aurum than GOLD and showed different trends: incidence and prevalence were stable or increasing in Aurum, decreasing in GOLD. Stratified estimates in CPRD Aurum suggested consistently higher occurrence among women, older age groups, and those living in the north of England.Conclusion: Comparative analyses of two English databases produced conflicting estimates and trends for two common musculoskeletal conditions. Aurum estimates appeared more consistent with external sources and may be useful for monitoring population musculoskeletal health and healthcare demand, but they remain sensitive to analytic decisions and data quality.Keywords: musculoskeletal, electronic health records, epidemiologic methods, osteoarthritis, low back pain, primary care

Dahai Yu, Kelvin P Jordan, George Peat Arthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Newcastle, UK Purpose: Primary care electronic health records are increasingly used to estimate the occurrence of osteoarthritis (OA). We aimed to estimate the extent and trend over time of underrecording of severe OA patients in UK primary care electronic health records using first primary total hip and knee replacements (THR/TKR) – >90% of which are performed for OA – as the reference population.Patients and methods: We identified patients with a first primary THR or TKR recorded in the UK Clinical Practice Research Datalink between 2000 and 2015. We then searched for a diagnostic/problem code for OA up to 10 years prior to THR/TKR using 3 definitions: “diagnosed OA (joint-specific),” “diagnosed OA (any joint),” “clinical OA” (diagnosed OA or relevant peripheral joint pain symptom code).Results: Among 34,299 THR patients identified, 28.1%, 53.4%, and 74.4% had a prior record of diagnosed OA (hip), diagnosed OA (any), and clinical OA, respectively. Among 47,588 TKR patients, the corresponding figures were, 25.5% (diagnosed OA [knee]), 43.7%, and 74.8%. In the UK Clinical Practice Research Datalink, the proportion of patients with prior recorded OA decreased between 2000 and 2015.Conclusion: An increasing trend of underrecording of OA or joint pain among patients with THR or TKR (severe OA patients) between 2000 and 2015 was identified. An underestimate health care demand could be derived based on consultation incidence and prevalence of OA from electronic health record data that relies on osteoarthritis diagnostic codes. Further studies are warranted to investigate the validity of OA or joint pain recorded in primary care settings, which might be used to correct the consultation incidence and prevalence of OA. Keywords: joint pain, total knee replacement, total hip replacement, sensitivity

ObjectiveThere are few guidelines for clinical trials of interventions for prevention of post-traumatic osteoarthritis (PTOA), reflecting challenges in this area. An international multi-disciplinary expert group including patients was convened to generate points to consider for the design and conduct of interventional studies following acute knee injury.DesignAn evidence review on acute knee injury interventional studies to prevent PTOA was presented to the group, alongside overviews of challenges in this area, including potential targets, biomarkers and imaging. Working groups considered pre-identified key areas: eligibility criteria and outcomes, biomarkers, injury definition and intervention timing including multi-modality interventions. Consensus agreement within the group on points to consider was generated and is reported here after iterative review by all contributors.ResultsThe evidence review identified 37 studies. Study duration and outcomes varied widely and 70% examined surgical interventions. Considerations were grouped into three areas: justification of inclusion criteria including the classification of injury and participant age (as people over 35 may have pre-existing OA); careful consideration in the selection and timing of outcomes or biomarkers; definition of the intervention(s)/comparator(s) and the appropriate time-window for intervention (considerations may be particular to intervention type). Areas for further research included demonstrating the utility of patient-reported outcomes, biomarkers and imaging outcomes from ancillary/cohort studies in this area, and development of surrogate clinical trial endpoints that shorten the duration of clinical trials and are acceptable to regulatory agencies.ConclusionsThese considerations represent the first international consensus on the conduct of interventional studies following acute knee joint trauma.

ObjectivesTo investigate changes in cartilage damage and bone marrow lesions (BMLs) on MRI in the patellofemoral and tibiofemoral joints (TFJs) over 7 years.MethodsThe Multicenter Osteoarthritis (MOST) Study is a cohort study of persons aged 50-79 years at baseline with or at high risk for knee osteoarthritis (OA). Knees were eligible for the current study if they had knee MRI (1.0T) assessed for cartilage damage and BMLs at the baseline and 84-month visits. Knees were categorized as having MRI-detected structural damage (cartilage and BMLs) isolated to the patellofemoral joint (PFJ), isolated to the TFJ, mixed or no damage at baseline and 84-months. We determined the changes in PFJ and TFJ structural damage over 7 years and used logistic regression to assess the relation of baseline compartment distribution to incident isolated PFJ, isolated TFJ and mixed damage.ResultsAmong 339 knees that had full-thickness cartilage loss isolated to the PFJ or TFJ at baseline, only 68 (20.1%) developed full-thickness cartilage loss in the other compartment while 271 (79.9%) continued to only have the initial compartment affected. Compared to knees without full-thickness cartilage damage (n = 582), those with isolated TFJ and PFJ full-thickness cartilage damage had 2.7 (1.5, 4.9) and 5.8 (3.6, 9.6) times the odds of incident mixed full-thickness cartilage damage, respectively. Similar results were seen when using other definitions of MRI-defined structural damage.ConclusionsMost knees with structural damage at baseline do not develop it in the other compartment. Knees that develop mixed structural damage are more likely to start with it isolated to the PFJ.

Introduction: Globally, back pain is the leading cause of years of disability. In the United Kingdom, over 20 million people live with musculoskeletal (MSK) pain, with low back pain being one of the most common causes. National strategies promote self‐management and the use of digital technologies to empower populations. Aims: To evaluate the uptake and impact of providing the SelfSTart approach (STarT Back and SelfBACK App) when delivered by a First Contact Physiotherapist (FCP) to people presenting with low back pain in primary care. Methods: Patients presenting with a new episode of low back pain underwent routine assessment and completion of a STarT Back questionnaire. Patients with low/medium scores were offered the SelfBACK App. A control population was provided by the MIDAS‐GP study. Patient Experience, outcome measures, healthcare utilisation and retention were captured through the app and clinical systems (EMIS). Interviews with five FCPs explored the experiences of using the SelfSTart approach. Results: SelfSTarT was taken up by almost half (48%) of those to whom it was offered. Compared to MIDAS‐GP, users were more likely to be younger, male, in work, and with higher health literacy. SelfSTarT users reported significant improved experiences relating to receiving an agreed care plan and receiving sufficient information. There were no significant differences in treatments offered. FCPs were positive about the app and felt it had value but wanted feedback on patient progress. They recognised that a digital solution would not be suitable for all. Conclusion: This approach offers an opportunity to empower and support self‐management, using robustly evaluated digital technology. [ABSTRACT FROM AUTHOR]