P244 Determining factors related to poor quality of life in patients with axSpA: results from the British Society for Rheumatology Biologics Register
Bibliographic record
Abstract
Abstract Background The aim when treating people with axial spondyloarthropathies (axSpA) is to maintain/improve their Quality of Life (QoL), traditionally through reducing disease activity. Previously, the Scotland Registry for Ankylosing Spondylitis (SIRAS) demonstrated, however, that although important, disease activity may not be the only factor influencing QoL. Indeed, function was a better predictor, with fatigue, chronic widespread pain and spinal mobility also important. The aim of the current study was to validate the previous findings in a large nationwide population, and determine if other factors, not collected in the previous study (such as mood and sleep) are also important. Methods The British Society for Rheumatology Biologics Register in Ankylosing Spondylitis (BSRBR-AS) is a prospective cohort of axSpA patients from 83 secondary care centres across Great Britain. Clinical data was collected during routine clinic visits and questionnaires provided patient reported outcomes including: the Ankylosing Spondylitis QoL questionnaire (ASQoL: scored 0 (best) to 18 (worst)), the Bath AS indices for disease & physical activity ((BASDAI/BASFI: scored 0 (best) - 10 (worst)), sleep disturbance (Jenkins: 0 (best) - 20 (worst)), depression (hospital anxiety & depression scales: scored 0 (best) - 21 (worst)) and the modification of the 2010 fibromyalgia criteria (widespread pain index (WPI): scored 0 (best) - 19 (worst) & symptom severity score (SSS): 0 (best) -12 (worst)). Using data collected at BSRBR-AS registration, multivariate linear regression models, predicting ASQoL, were used to validate the previous SIRAS model. Additionally, a de-novo forward stepwise model was developed to assess consistency across both populations and to determine if any additional factors (such as mood and sleep) predicted QoL. Results 1,810 BSRBR-AS participants were eligible for the current study, 67% of whom were male, median age 49 years (interquartile range 38-61). 80% of those tested were HLA-B27 positive and the majority of patients (67%) met the modified New York Criteria for AS. Of the five factors included in the SIRAS model; disease activity, physical function, fatigue and widespread pain remained significantly associated with QoL in the BSRBR-AS study. Spinal mobility was no longer significantly associated. Within the de-novo model eight independent factors predicted ASQoL score: disease activity (coefficient 0.31, 95% (confidence interval 0.14, 0.47)), physical function (0.59 (0.45, 0.73)), depression (HADS: 0.16 (0.09, 0.24)), sleep disturbance (0.08 (0.04, 0.13)), activity impairment (0.04 (0.02, 0.05)), fibromyalgia (SSS: 0.24 (0.13, 0.35), WPI: 0.10 (0.03, 0.17)) and tobacco smoking (vs. non-smoker: 0.66 (0.10, 1.21)). Conclusion Current EULAR guidelines for management of axSpA targeting disease activity and physical function are supported by the current findings which suggest both are consistently important predictors of QoL. However, additional factors such as fatigue, sleep disturbance and mood also contribute to QoL and should be considered additional targets within future axSpA management strategies. Disclosures L.E. Dean None. O. Rotariu None. G.T. Jones None. E. Pathan Other; E.P. has received salary funding from Jansen (2019) and Merck (2018). G.J. Macfarlane None.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".