Interplay between demographic, clinical and polygenic risk factors for severe COVID-19.

BACKGROUND: We aimed to identify clinical, socio-demographic and genetic risk factors for severe COVID-19 (hospitalization, critical care admission or death) in the general population. METHODS: In this observational study, we identified 9560 UK Biobank participants diagnosed with COVID-19 during 2020. A polygenic risk score (PRS) for severe COVID-19 was derived and optimized using publicly available European and trans-ethnic COVID-19 genome-wide summary statistics. We estimated the risk of hospital or critical care admission within 28 days or death within 100 days following COVID-19 diagnosis, and assessed associations with socio-demographic factors, immunosuppressant use and morbidities reported at UK Biobank enrolment (2006-2010) and the PRS. To improve biological understanding, pathway analysis was performed using genetic variants comprising the PRS. RESULTS: We included 9560 patients followed for a median of 61 (interquartile range = 34-88) days since COVID-19 diagnosis. The risk of severe COVID-19 increased with age and obesity, and was higher in men, current smokers, those living in socio-economically deprived areas, those with historic immunosuppressant use and individuals with morbidities and higher co-morbidity count. An optimized PRS, enriched for single-nucleotide polymorphisms in multiple immune-related pathways, including the 'oligoadenylate synthetase antiviral response' and 'interleukin-10 signalling' pathways, was associated with severe COVID-19 (adjusted odds ratio 1.32, 95% CI 1.11-1.58 for the highest compared with the lowest PRS quintile). CONCLUSION: This study conducted in the pre-SARS-CoV-2-vaccination era, emphasizes the novel insights to be gained from using genetic data alongside commonly considered clinical and socio-demographic factors to develop greater biological understanding of severe COVID-19 outcomes.

Collection of cancer Patient Reported Outcome Measures (PROMS) to link with primary and secondary electronic care records to understand and improve long term cancer outcomes: A protocol paper.

INTRODUCTION: More people are living with and beyond a cancer diagnosis. There is limited understanding of the long-term effects of cancer and cancer treatment on quality of life and personal and household finances when compared to people without cancer. In a separate protocol we have proposed to link de-identified data from electronic primary care and hospital records for a large population of cancer survivors and matched controls. In this current protocol, we propose the linkage of Patient Reported Outcomes Measures data to the above data for a subset of this population. The aim of this study is to investigate the full impact of living with and beyond a cancer diagnosis compared to age and gender matched controls. A secondary aim is to test the feasibility of the collection of Patient Reported Outcomes Measures (PROMS) data and the linkage procedures of the PROMs data to electronic health records data. MATERIALS AND METHODS: This is a cross-sectional study, aiming to recruit participants treated at the Leeds Teaching Hospitals National Health Service Trust. Eligible patients will be cancer survivors at around 5 years post-diagnosis (breast, colorectal and ovarian cancer) and non-cancer patient matched controls attending dermatology out-patient clinics. They will be identified by running a query on the Leeds Teaching Hospitals Trust patient records system. Approximately 6000 patients (2000 cases and 4000 controls) will be invited to participate via post. Participants will be invited to complete PROMs assessing factors such as quality of life and finances, which can be completed on paper or online (surveys includes established instruments, and bespoke instruments (demographics, financial costs). This PROMs data will then be linked to routinely collected de-identified data from patient's electronic primary care and hospital records. DISCUSSION: This innovative work aims to create a truly 'comprehensive patient record' to provide a broad picture of what happens to cancer patients across their cancer pathway, and the long-term impact of cancer treatment. Comparisons can be made between the cases and controls, to identify the aspects of life that has had the greatest impact following a cancer diagnosis. The feasibility of linking PROMs data to electronic health records can also be assessed. This work can inform future support offered to people living with and beyond a cancer diagnosis, clinical practice, and future research methodologies.

A data flow process for confidential data and its application in a health research project.

BACKGROUND: The use of linked healthcare data in research has the potential to make major contributions to knowledge generation and service improvement. However, using healthcare data for secondary purposes raises legal and ethical concerns relating to confidentiality, privacy and data protection rights. Using a linkage and anonymisation approach that processes data lawfully and in line with ethical best practice to create an anonymous (non-personal) dataset can address these concerns, yet there is no set approach for defining all of the steps involved in such data flow end-to-end. We aimed to define such an approach with clear steps for dataset creation, and to describe its utilisation in a case study linking healthcare data. METHODS: We developed a data flow protocol that generates pseudonymous datasets that can be reversibly linked, or irreversibly linked to form an anonymous research dataset. It was designed and implemented by the Comprehensive Patient Records (CPR) study in Leeds, UK. RESULTS: We defined a clear approach that received ethico-legal approval for use in creating an anonymous research dataset. Our approach used individual-level linkage through a mechanism that is not computer-intensive and was rendered irreversible to both data providers and processors. We successfully applied it in the CPR study to hospital and general practice and community electronic health record data from two providers, along with patient reported outcomes, for 365,193 patients. The resultant anonymous research dataset is available via DATA-CAN, the Health Data Research Hub for Cancer in the UK. CONCLUSIONS: Through ethical, legal and academic review, we believe that we contribute a defined approach that represents a framework that exceeds current minimum standards for effective pseudonymisation and anonymisation. This paper describes our methods and provides supporting information to facilitate the use of this approach in research.

Changes in ankylosing spondylitis incidence, prevalence and time to diagnosis over two decades.

OBJECTIVES: To assess changes in ankylosing spondylitis (AS) incidence, prevalence and time to diagnosis, between 1998 and 2017. METHODS: Using UK GP data from the Clinical Practice Research Datalink, we identified patients diagnosed with AS between 1998 and 2017. We estimated the annual AS incidence, prevalence and length of time from first recorded symptom of back pain to rheumatology referral and diagnosis. RESULTS: We identified 12 333 patients with AS. The incidence declined from 0.72 (±0.14) per 10 000 patient-years in 1998 to 0.39 (±0.06) in 2007, with this decline significant only in men, then incidence rose to 0.57 (±0.11) in 2017. By contrast, prevalence increased between 1998 and 2017 (from 0.13%±0.006 to 0.18%±0.006), rising steeply among women (from 0.06%±0.05 to 0.10%±0.06) and patients aged ≥60 (from 0.14%±0.01 to 0.26%±0.01). The overall median time from first symptom to rheumatology referral was 4.87 years (IQR=1.42-10.23). The median time from first symptom to diagnosis rose between 1998 and 2017 (from 3.62 years (IQR=1.14-7.07) to 8.31 (IQR=3.77-15.89)) and was longer in women (6.71 (IQR=2.30-12.36)) than men (5.65 (IQR=1.66-11.20)). CONCLUSION: AS incidence declined significantly between 1998 and 2007, with an increase between 2007 and 2017 that may be explained by an improvement in the recognition of AS or confidence in diagnosing AS over time, stemming from increased awareness of inflammatory back pain and the importance of early treatment. The rising AS prevalence may indicate improved patient survival. The persisting delay in rheumatology referral and diagnosis remains of concern, particularly in women.

Changes in the pharmacological management of rheumatoid arthritis over two decades.

OBJECTIVES: To assess whether modern management of RA has reduced the prescription of oral corticosteroids and NSAIDs and to evaluate use of pharmacological prophylaxis strategies. METHODS: Using the Clinical Practice Research Datalink, we explored long-term (≥3/12 months; ≥6/12 in sub-analyses) DMARD, corticosteroid and NSAID prescribing (annually, in the year post-diagnosis and across the patient's life course to 15 years post-diagnosis), annual proportion with co-prescribing for prophylaxis of associated bone (corticosteroids, women only) and gastrointestinal (NSAIDs) comorbidity. RESULTS: Reported incidence of RA was 5.98 (0.37) per 10 000 person-years and prevalence was 0.91% (0.014) in 2017. In 71 411 RA patients, long-term DMARD prescribing initially rose post-diagnosis from 41.6% in 1998 to 67.9% in 2009. Corticosteroid prescribing changed little, overall [22.2% in 1998, 19.1% in 2016; incident risk ratio (IRR) 0.92, 95% CI: 0.82, 1.03] and across the life course from the first to fifteenth year (22.2% to 16.9%). NSAID prescribing declined from 57.7% in 1998, and significantly so from 2008, to 27.1% in 2016 (IRR 0.50, 95% CI: 0.44, 0.56). This continued across the life course (41.2% to 28.4%). Bone prophylaxis increased to 68.1% in 2008 before declining to 56.4% in 2017; gastrointestinal prophylaxis increased from 11.5% in 1998 to 62.6% in 2017. Sub-analyses showed consistent patterns. CONCLUSION: Despite modern treatment strategies, corticosteroid prescribing in RA patients remains substantial and persists beyond 6 months once initiated. Rheumatologists need to determine causes and develop strategies to reduce corticosteroid use to minimize adverse event occurrence.

Variation in methods, results and reporting in electronic health record-based studies evaluating routine care in gout: A systematic review.

OBJECTIVE: To perform a systematic review examining the variation in methods, results, reporting and risk of bias in electronic health record (EHR)-based studies evaluating management of a common musculoskeletal disease, gout. METHODS: Two reviewers systematically searched MEDLINE, Scopus, Web of Science, CINAHL, PubMed, EMBASE and Google Scholar for all EHR-based studies published by February 2019 investigating gout pharmacological treatment. Information was extracted on study design, eligibility criteria, definitions, medication usage, effectiveness and safety data, comprehensiveness of reporting (RECORD), and Cochrane risk of bias (registered PROSPERO CRD42017065195). RESULTS: We screened 5,603 titles/abstracts, 613 full-texts and selected 75 studies including 1.9M gout patients. Gout diagnosis was defined in 26 ways across the studies, most commonly using a single diagnostic code (n = 31, 41.3%). 48.4% did not specify a disease-free period before 'incident' diagnosis. Medication use was suboptimal and varied with disease definition while results regarding effectiveness and safety were broadly similar across studies despite variability in inclusion criteria. Comprehensiveness of reporting was variable, ranging from 73% (55/75) appropriately discussing the limitations of EHR data use, to 5% (4/75) reporting on key data cleaning steps. Risk of bias was generally low. CONCLUSION: The wide variation in case definitions and medication-related analysis among EHR-based studies has implications for reported medication use. This is amplified by variable reporting comprehensiveness and the limited consideration of EHR-relevant biases (e.g. data adequacy) in study assessment tools. We recommend accounting for these biases and performing a sensitivity analysis on case definitions, and suggest changes to assessment tools to foster this.