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Ankylosing spondylitis is the second most common cause of inflammatory arthritis. However, a successful diagnosis can take a decade to confirm from symptom onset (via x-rays). The aim of this study was to use machine learning methods to develop a profile of the characteristics of people who are likely to be given a diagnosis of AS in future. The Secure Anonymised Information Linkage databank was used. Patients with ankylosing spondylitis were identified using their routine data and matched with controls who had no record of a diagnosis of ankylosing spondylitis or axial spondyloarthritis. Data was analysed separately for men and women. The model was developed using feature/variable selection and principal component analysis to develop decision trees. The decision tree with the highest average F value was selected and validated with a test dataset. The model for men indicated that lower back pain, uveitis, and NSAID use under age 20 is associated with AS development. The model for women showed an older age of symptom presentation compared to men with back pain and multiple pain relief medications. The models showed good prediction (positive predictive value 70%-80%) in test data but in the general population where prevalence is very low (0.09% of the population in this dataset) the positive predictive value would be very low (0.33%-0.25%). Machine learning can be used to help profile and understand the characteristics of people who will develop AS, and in test datasets with artificially high prevalence, will perform well. However, when applied to a general population with low prevalence rates, such as that in primary care, the positive predictive value for even the best model would be 1.4%. Multiple models may be needed to narrow down the population over time to improve the predictive value and therefore reduce the time to diagnosis of ankylosing spondylitis. [ABSTRACT FROM AUTHOR]

Abstract Background Today, health care is patient-centred with patients more involved in medical decision making and taking an active role in managing their disease. It is important that patients are appropriately informed about their condition and that their health care needs are met. We examine the information utilisation, sources and needs of people with Ankylosing Spondylitis (AS). Methods Participants in an existing AS cohort study were asked to complete a postal or online questionnaire containing closed and open-ended questions, regarding their information access and needs. Participants were stratified by age and descriptive statistics were performed using STATA 11, while thematic analysis was performed on open-ended question narratives. Qualitative data was handled in Microsoft Access and explored for emerging themes and patterns of experiences. Results Despite 73% of respondents having internet access, only 49% used the internet to access information regarding AS. Even then, this was only infrequently. Only 50% of respondents reported accessing written information about AS, which was obtained mainly in specialist clinics. Women were more likely than men to access information (63% (women) 46% (men)) regardless of the source, while younger patients were more likely to use online sources. The main source of non-written information was the rheumatologist. Overall, the respondents felt there was sufficient information available, but there was a perception that the tone was often too negative. The majority (95%) of people would like to receive a regular newsletter about AS, containing positive practical and local information. Suggestions were also made for more information about AS to be made available to non-specialist medical professionals and the general public. Conclusions There appears to be sufficient information available for people with AS in the UK and this is mostly accessed by younger AS patients. Many patients, particularly men, choose not to access AS information and concerns were raised about its negative tone. Patients still rely on written and verbal information from their specialists. Future initiatives should focus on the delivery of more positive information, targeting younger participants in particular and increasing the awareness in the general population and wider non-specialist medical community.

Objectives PsA and AS are chronic diseases associated with significant morbidities. National and international management guidelines include treatment with biologic therapies to improve outcomes and quality of life. There are limited real-world data on the patients' journey from symptom onset to diagnosis and treatment in the UK. We use real-life, linked health data to explore patient pathways and the impact of biologics on patient outcomes. Methods Data from the Secure Anonymised Information Linkage databank in Wales were used to assess diagnosis and treatment of patients ≥18 years of age with at least one International Classification of Diseases, Tenth Revision code present for PsA/AS in rheumatology clinic data and at least one Read code present in primary care records. We investigated the use of biologics while exploring demographics, comorbidities and surgical procedures of 641 AS patients and 1312 PsA patients. Results AS patients were significantly younger at diagnosis and were predominantly male. The average time from presenting symptoms to diagnosis of AS and PsA was 7.9 (s. d. 5.5) and 9.3 (s. d. 5.5) years, respectively. The proportion of patients receiving biologic treatment was significantly higher in AS (46%) compared with PsA patients (28.8%); of these, 23.1% of AS and 22.2% of PsA patients stopped/switched a biologic. There was a significant reduction in primary care involvement, sick notes and disability living allowance for both AS and PsA patients following biologic initiation. Conclusion This real-world descriptive study confirms that patients treated with biologics have reduced disability and time off work despite being initiated ∼13 years after the first symptoms and 6 years after diagnosis. [ABSTRACT FROM AUTHOR]

Objective. To explore severe flare and constant disease pattern (no periods of remission) in AS as predictors of poor outcomes [impaired function, unemployment/early retirement, work impairment, anti-TNF, surgery, frequent general practitioner (GP) visits, depression and anxiety]. Methods. Three hundred and forty-eight AS patients completed questionnaires about their experience with disease flares. Questionnaire data were linked to electronic medical records to examine visits to GPs and hospital admission data. Outcomes were stratified in two ways: self-reported experience of severe flare and constant disease pattern using the flare illustration tool. Results. The majority of patients (72%, 208/289) experienced flare pre-diagnosis. Severe flares were reported by 58% (202/348) of participants (self-report); of these, 195 responded about earliest flares and 69% (135/195) of severe flare patients experienced flares pre-diagnosis. Patients who self-reported severe flares had worse function, disease activity, work impairment and symptoms of anxiety and depression, were less likely to be employed and had more GP encounters per year compared with those who never reported severe flares. Participants who reported constant unremitting disease on the flare illustration tool had worse disease activity, impaired function and work impairment and were more likely to smoke compared with those with intermittent disease. Analysis showed a relationship between self-report of severe flare and subsequent depression, impaired function, increased disease activity and work limitations. Conclusion. Severe flare is associated with poor outcomes such as work impairment and impaired function. The onset of severe flare early in the disease course may be a risk factor for later poor outcome and this group could benefit from targeted early aggressive treatment to improve prognosis. [ABSTRACT FROM AUTHOR]

Background: Fatigue is a major component of living with ankylosing spondylitis (AS), though it has been largely over-looked, and currently there are no specific agreed management strategies. Methods: This qualitative exploratory study involved participants who are members of an existing populationbased ankylosing spondylitis (PAS) cohort. Participants residing in South West Wales were invited to participate in a focus group to discuss; (1) effects of fatigue, (2) self-management strategies and (3) potential future interventions. The focus groups were audio-recorded and the transcripts were analysed using thematic analysis. Results: Participants consisted of 3 males/4 females (group 1) and 4 males/3 females (group 2), aged between 35 and 73 years (mean age 53 years). Three main themes were identified: (1) The effects of fatigue were multidimensional with participants expressing feelings of being 'drained' (physical), 'upset' (emotional) and experiencing 'low-mood' (psychological); (2) The most commonly reported self-management strategy for fatigue was a balanced combination of activity (exercise) and rest. Medication was reluctantly taken due to side-effects and worries over dependency; (3) Participants expressed a preference for psychological therapies rather than pharmacological for managing fatigue. Information on Mindfulness-Based Stress Reduction (MBSR) was received with interest, with recommendations for delivery in a group format with the option of distance-based delivery for people who were not able to attend a group course. Conclusions: Patients frequently try and manage their fatigue without any formal guidance or support. Our research indicates there is a need for future research to focus on psychological interventions to address the multi-faceted aspects of fatigue in AS. [ABSTRACT FROM AUTHOR]

Objectives: Exercise is reported to improve function for people with ankylosing spondylitis (AS) but it is not clear if this effect is causal or if patients with milder disease find it easier to exercise. This study examines the effect of exercise and motivation to exercise on function, while controlling for disease severity. Methods: Participants who were members of an existing AS cohort were asked about physical activity, motivation to exercise, function, and disease severity. Path analysis on STATA was used to examine the correlation between factors associated with function at time of exercise and with function after 3 months of follow-up. Results: The response rate to the questionnaire was 88% (326/371). Improvement in function was greatest for people with higher physical activity levels and those who were more motivated to exercise—this was especially the case for patients with the most severe disease activity. The effect of motivation to exercise not only had a direct effect on function, but also an indirect effect of improving activity levels thereby improving both current and future function. People with high intrinsic motivation (driven by pleasure) had the greatest benefit to activity and function. Conclusions: Exercise does improve function, especially for those with severe disease. In addition, motivation alone improves function as much as exercising itself. Therefore, interventions targeting motivation to exercise would have as much effect on improving function as interventions offering exercise opportunities. In addition, any intervention that both improves motivation and increases opportunities to exercise would have a 2-fold influence on function. [Copyright &y& Elsevier]

Objectives: Fatigue is an important symptom associated with ankylosing spondylitis (AS). This study examines patients'' perspectives and clinical associations of fatigue to help inform potential strategies to alleviate fatigue in AS. Methods: A mixed methods approach was taken to examine fatigue in a cohort of people with AS. Fatigue levels were evaluated from 3 consecutive monthly questionnaires. Open-ended questions on fatigue were analyzed using thematic analysis and logistic regression was used to examine quantitative data. In addition, fatigue levels were examined before and after treatment with anti-tumor necrosis factor (TNF) compared to nontreated controls. Results: Three hundred forty-eight of 385 participants completed a fatigue questionnaire. Fatigue was reported to have significant physical, social, and psychological effects. A third of the participants reported that there was nothing they could do to reduce their fatigue, whereas other participants reported that medication, exercise, and resting helped. The main factor associated with fatigue was pain [β-coefficient: 0.74 (95% CI: 0.66 to 0.81)], whereas depression was much less strongly associated. However, these factors only explained 40% of the variation in fatigue levels. Starting anti-TNF therapy reduced fatigue and pain levels compared to the period of time before taking anti-TNF [difference: 14.4 (95% CI: 5.3 to 23.5) on a scale of 0-100] and this reduction was not seen in controls over the same period. Conclusions: Fatigue is not strongly associated with anxiety, motivation, and depression; instead the factor most associated with fatigue is pain. This suggests that in addition to treatments to reduce disease activity, strategies for alleviating fatigue in AS should focus on pain management techniques and actively treating inflammation. [Copyright &y& Elsevier]

Objectives: To examine if people with ankylosing spondylitis (AS) are at higher risk of acute myocardial infarction (MI) or stroke compared to those without AS. Methods: Primary care records were linked with all hospital admissions and deaths caused by MI or stroke in Wales for the years 1999-2010. The linked data were then stratified by AS diagnosis and survival analysis was used to obtain the incidence rate of MI and separately cerebrovascular disease (CVD)/stroke. Cox regression was used to adjust for gender and age. Logistic regression was used to examine prevalence of diabetes, hypertension, or hyperlipidemia for those with AS compared to those without. Results: There were 1686 AS patients (75.9% male, average age 46.1 years) compared to 1,206,621 controls (48.9% male, average age 35.9 years). Age- and gender-adjusted hazard ratios for MI were 1.28 (95% CI: 0.93 to 1.74) P = 0.12, and for CVD/stroke 1.0 (95% CI: 0.73 to 1.39) P = 0.9, in AS compared to controls. The prevalence of diabetes and hypertension, but not hyperlipidemia/hypercholesterolemia, was higher in AS. Conclusions: There is no increase in the MI or CVD/stroke rates in patients with AS compared to those without AS, despite higher rates of hypertension, which may be related to nonsteroidal anti-inflammatory drug use. [Copyright &y& Elsevier]

Objective. To examine the characteristics and frequency of disease flares in a cohort of people with AS. [ABSTRACT FROM PUBLISHER]

Background: To develop a population-based cohort of people with ankylosing spondylitis (AS) in Wales using (1) secondary care clinical datasets, (2) patient-derived questionnaire data and (3) routinely-collected information in order to examine disease history and the health economic cost of AS. Methods: This data model will include and link (1) secondary care clinician datasets (i.e. electronic patient notes from the rheumatologist) (2) patient completed questionnaires (giving information on disease activity, medication, function, quality of life, work limitations and health service utilisation) and (3) a broad range of routinely collected data (including; GP records, in-patient hospital admission data, emergency department data, laboratory/pathology data and social services databases). The protocol involves the use of a unique and powerful data linkage system which allows datasets to be interlinked and to complement each other. Discussion: This cohort can integrate patient supplied, primary and secondary care data into a unified data model. This can be used to study a range of issues such as; the true economic costs to the health care system and the patient, factors associated with the development of severe disease, long term adverse events of new and existing medication and to understand the disease history of this condition. It will benefit patients, clinicians and health care managers. This study forms a pilot project for the use of routine data/patient data linked cohorts for other chronic conditions. [ABSTRACT FROM AUTHOR]

(1) Background: We aimed to develop a transparent machine-learning (ML) framework to automatically identify patients with a condition from electronic health records (EHRs) via a parsimonious set of features. (2) Methods: We linked multiple sources of EHRs, including 917,496,869 primary care records and 40,656,805 secondary care records and 694,954 records from specialist surgeries between 2002 and 2012, to generate a unique dataset. Then, we treated patient identification as a problem of text classification and proposed a transparent disease-phenotyping framework. This framework comprises a generation of patient representation, feature selection, and optimal phenotyping algorithm development to tackle the imbalanced nature of the data. This framework was extensively evaluated by identifying rheumatoid arthritis (RA) and ankylosing spondylitis (AS). (3) Results: Being applied to the linked dataset of 9657 patients with 1484 cases of rheumatoid arthritis (RA) and 204 cases of ankylosing spondylitis (AS), this framework achieved accuracy and positive predictive values of 86.19% and 88.46%, respectively, for RA and 99.23% and 97.75% for AS, comparable with expert knowledge-driven methods. (4) Conclusions: This framework could potentially be used as an efficient tool for identifying patients with a condition of interest from EHRs, helping clinicians in clinical decision-support process. [ABSTRACT FROM AUTHOR]

Summary BackgroundAnkylosing spondylitis is a genetically determined and commonly familial disorder. Men and women differ in their susceptibility to ankylosing spondylitis, with about 2.5 men affected for every woman with the disease. We investigated the influence of the sex of the index case on disease penetrance within families.MethodsThe ages at which 50% and 75% of patients were diagnosed with ankylosing spondylitis were ascertained from a database of 4400 cases. Index patients with children or siblings who were old enough to have obtained a diagnosis (50% and 75% rates) were assessed for prevalence of disease among relatives. Confirmation of diagnosis for affected relatives was sought for all offspring and a random 25% selection of siblings.FindingsAnkylosing spondylitis was more prevalent among children (odds ratio 1.9 [95% CI 1.2-3.0], p<0.005) and siblings (1.5 [1.2-1.9], p<0.0001) of female index cases than among those of male cases. Analyses restricted to index cases with a young age at onset ([≤ OR =]21 years) indicated that children of women had an even higher incidence of ankylosing spondylitis (7.2 [1.5-34], p=0.013) than did children of men at similar age at onset. 38% of children of female cases had disease compared with 8% of male cases. There was no difference in sex distribution among affected children or siblings of female patients with ankylosing spondylitis. By contrast, the sons and brothers of male patients had a higher prevalence of the disease (odds ratio 2.6 [1.4-5.2], p=0.003) than did daughters and sisters (1.7 [1.3-2.2], p<0.0001).InterpretationThe influence of female sex is greater than that of male sex in determining increased susceptibility to ankylosing spondylitis in children. The striking maternal effect is greatest for women with young age at onset, which is not seen in men. The sex ratio of affected children depends on the sex of the affected parent.Lancet 1999; 354: 1687-90 [ABSTRACT FROM AUTHOR]

Objectives Cost-effectiveness analyses of technologies for patients with ankylosing spondylitis frequently require estimates of health utilities as a function of the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and the Bath Ankylosing Spondylitis Functional Index (BASFI). Methods Linear regression, bespoke mixture models, and generalized ordered probit models were used to model the EuroQol five-dimensional questionnaire as a function of BASDAI and BASFI. Data were drawn from a large UK cohort study (n = 516 with up to five observations) spanning the full range of disease severity. Results Linear regression was systematically biased. Three- and four-component mixture models and generalized probit models exhibit no such bias and improved fit to the data. The mean, median, mean error, and mean absolute error favored the mixture model approach. Root mean square error favored the generalized ordered probit model approach for the data as a whole. Model fit assessed using these same measures by disease severity quartiles tended to be best using the mixture models. The value of moving from good to poor health may differ substantially according to the chosen method. Simulated data from the mixture and probit models yield a very similar distribution to the original data set. Conclusions These results add to a body of evidence that the statistical model used to estimate health utilities matters. Linear models are not appropriate. The four-class bespoke mixture model approach provides the best performing method to estimate the EuroQol five-dimensional questionnaire values from BASDAI and BASFI. [ABSTRACT FROM AUTHOR]