Protocol for a population-based Ankylosing Spondylitis (PAS) cohort in Wales

Ankylosing Spondylitis (AS) is a chronic inflammatory arthritis affecting between 1 in 400 and 1 in 270 people [1, 2]. AS is characterised by inflammation of the spine, resulting in progressive and irreversible fusion of the spine. Peripheral joints, particularly the hips [3] can also be involved, often requiring hip replacement surgery. In a significant number of patients, AS is also associated with inflammation of other organs such as the heart [4, 5], eyes [6], bowel [7] and skin [8]. In common with most chronic inflammatory conditions, AS is heterogeneous, having a variable course and unpredictable episodes of exacerbation [9].

AS typically strikes people in their late teens or early adult life and runs for the remainder of the life-course. It therefore has a significant impact on employment and function and on the use of health and social care resources. Over 80% of patients report daily pain, 60% report daily use of drugs 20 years after diagnosis [10] and in a Dutch study only 54.2% of the AS cohort were participating in the labour work force [11].

Our study proposes to collect and link a range of complementary sets of data; including, robust clinical data from rheumatologists (diagnosis, MRI/radiograph images), existing routinely collected datasets such as the GP records, out-patients clinical data, in-patient activity, emergency department, laboratory/pathology data and social services databases and finally data collected directly from the patients themselves (disease activity, function, quality of life, work limitations).

Re-use of routine data is problematic and requires detailed knowledge of the datasets and their idiosyncracies. Information Governance challenges can also be a problem in such distributed datasets. These problems have been surmounted by the establishment of the Health Information Research Unit (HIRU) at the School of Medicine at Swansea University as part of the Welsh Assembly Government's commitment to the UK Clinical Research Collaboration (UKCRC). Its remit is to realise the potential of electronically held, person-based, routinely collected information to conduct and support health-related research. HIRU has set up the Secure Anonymised Information Linkage (SAIL) databank to bring together, link and anonymise the widest possible range of person-based data, and has done this using a split-file approach to anonymisation to overcome issues of confidentiality and disclosure in health-related data warehousing [12]. The SAIL databank operates within a robust series of guidelines in line with the Caldicott principles and the National Information Governance Board for Health and Social Care. [13].

The collection and linkage of data proposed here is unique and not currently feasible elsewhere. Due to the existing routine data linkages [12] and a new rheumatology network incorporating all rheumatologists in Wales, it is now possible to undertake a national AS cohort study identifying a well defined and characterised group, with the intention of expanding this strategy to other rheumatological conditions in the future.

This cohort takes its participants from GPs (primary care practitioners) and rheumatologists. The study is supplemented by patient-supplied information in the form of a series of questionnaires. Patient consent is required to include patients in the cohort. In addition, consent is sought to link cohort participants to the existing databank of routinely collected data currently in the SAIL system. The ability to link cohort members anonymously to routinely collected data is one of the unique features of this cohort. GP data is widely used in research, and can give a wide range of information about treatment and associated conditions, but one must be aware of the various issues of data quality and completeness concerning primary care records [26]. Other sources of routine data such as in-patient and out-patient records can also be linked to the cohort and can help to enhance the data held on each patient.

The cohort will have immediate impact on giving an objective estimate of the cost of AS at each stage of the disease which will help inform the use of anti-TNF agents. This is of immediate importance to many patients who could benefit from these agents, once approved by NICE. Patients who potentially meet the NICE criteria for the anti-TNF agents could be easily identified as part of this cohort.

The existing routine data from the previous 10 years will enable retrospective cohort studies to identify early risk factors (such as early hip involvement [27]) for progression to severe AS (as defined by the need for surgery or disability benefit). These patients could then be selected for aggressive early treatment with anti-TNF agents.

The cohort can be used to rapidly identify potential patients for RCTs of anti-TNF agents and other new drugs. This cohort can be used to screen for specified inclusion criteria and estimate the numbers eligible for new trials in the area. This will facilitate recruitment as the individuals can be identified remotely and invited by their local rheumatologists or GP to participate in these studies. The process of screening and recruitment of participants to trials can then be significantly speeded up reducing the risk and cost to pharmaceutical companies, thereby leading to more efficient and cost-effective trials.

The collection of AS patients can inform the development of genetic work in this field and facilitate the development of potential vaccines and other targeted therapies as a follow on from this work. Therefore it will facilitate the UK participation within international consortiums on genetic research of inflammatory autoimmune conditions. Once established and phenotyped, it is intended that this cohort will be used for studies in conjunction with the rheumatology research networks established by the Arthritis Research Campaign (ARC). These future studies include the potential to link the data from this cohort with biological and genetic sample banks from consenting patients. There has been a long history of work looking at the genetics of AS in the UK. However, there is a bottle-neck in terms of identifying enough people to conduct repeat validation studies to confirm the importance of new regions of interest for susceptibility and severity genes. By far the largest study in AS genetics to date involved 1000 patients with AS and 1500 controls [28], while no genome-wide association study has yet been done in AS [29]. Historically, these studies have not tended to use patients from Wales for logistical reasons as it has previously been difficult to identify these patients. Therefore this well characterised cohort, together with the collection of newly diagnosed AS patients, would enhance the ability of researchers in the UK to conduct these validation studies. Linking genetic and biological samples with the routinely collected clinical data would also allow the investigation and identification of associations not possible by other means.

Phenotyping patients would include collecting measures that reflect the expression of the disease without describing the actual genetic make-up of the patient. In the case of AS, this would include; medically held data such as first symptoms, disease history and development, areas affected, co-disorders, severity, family history, age at onset, environmental data such as socio-economic status, physical activity levels, medications, inherent modifiers such as sex, ethnicity and finally biochemical/immunological measures from the laboratory such as markers for inflammation. Much of this data can be obtained from existing routine data and from the patient.

The cohort can be used to work with family members of AS patients in order to identify individuals at high risk of developing AS (such as the children of AS-affected women with a young age at onset [30]) to examine the early disease history of AS pre-diagnosis (using MRI scans) in order to examine interventions which may switch off or prevent AS.

This study therefore builds on and enhances existing UK resources and infrastructure. The methods used in this study are also relevant to other chronic conditions, and the PAS cohort is seen as a pilot for this strategy of phenotyping cohorts using the linkage of routine, clinical and patient-entered data.

This cohort will also allow easy collection of post-RCT and post-marketing surveillance data, which is crucial for new biologic agents whose long-term effects are unknown. The British Society for Rheumatology (BSR) is currently piloting measures and data collection for the development of a Disease Management Register for AS, including a biologics register [31] The PAS cohort could be used to directly contribute to and enhance this national register.

Thus, in conclusion the cohort can be used for a wide variety of research studies (burden/cost of disease, disease history, trial recruitment, genetic research, basic research of biological markers, and post trial surveillance). This is a pilot for undertaking the same method of cohort development in other chronic conditions.