Early clinical features in Systemic Lupus Erythematosus: can they be used to achieve earlier diagnosis? A risk prediction model.

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Rees, F ; Doherty, M ; Lanyon, P ; Davenport, G ; Riley, RD ; Zhang, W ; Grainge, MJ (2016)
  • Publisher: Wiley
  • Related identifiers: doi: 10.1002/acr.23021
  • Subject: early diagnosis | Systemic Lupus Erythematosus | risk prediction | Clinical Practice Research Datalink | RA
    mesheuropmc: skin and connective tissue diseases

OBJECTIVES: 1) To compare the primary care consulting behaviour prior to diagnosis of people with Systemic Lupus Erythematosus (SLE) with controls, 2) to develop and validate a risk prediction model to aid earlier SLE diagnosis. \ud \ud METHODS: 1,739 incident SLE cases practice-matched to 6,956 controls from the UK Clinical Practice Research Datalink. Odds ratios were calculated for age, gender, consultation rates, selected presenting clinical features and previous diagnoses in the 5 years preceding diagnosis date using logistic regression. A risk prediction model was developed from pre-selected variables using backward stepwise logistic regression. Model discrimination and calibration were tested in an independent validation cohort of 1,831,747 patients. \ud \ud RESULTS: People with SLE had a significantly higher consultation rate than controls (median 9.2 vs 3.8/year) which was in part attributable to clinical features that occur in SLE. The final risk prediction model included the variables age, gender, consultation rate, arthralgia or arthritis, rash, alopecia, sicca, Raynaud's, serositis and fatigue. The model discrimination and calibration in the validation sample was good (Receiver operator characteristic curve: 0.75, 95% CI 0.73-0.78). However, absolute risk predictions for SLE were typically less than 1% due to the rare nature of SLE. \ud \ud CONCLUSIONS: People with SLE consult their GP more frequently and with clinical features attributable to SLE in the five years preceding diagnosis, suggesting that there are potential opportunities to reduce diagnostic delay in primary care. A risk prediction model was developed and validated which may be used to identify people at risk of SLE in future clinical practice. This article is protected by copyright. All rights reserved.
  • References (24)
    24 references, page 1 of 3

    1. Lupus UK. Lupus UK: National Survey. News and Views. 2011.

    2. Ozbek S, Sert M, Paydas S, Soy M. Delay in the diagnosis of SLE: the importance of arthritis/arthralgia as the initial symptom. Acta Med Okayama. 2003;57(4):187-90.

    3. Faurschou M, Dreyer L, Kamper AL, Starklint H, Jacobsen S. Long-term mortality and renal outcome in a cohort of 100 patients with lupus nephritis. Arthritis Care Res 2010;62(6):873-80.

    4. Oglesby A, Korves C, Laliberté F, Dennis G, Rao S, Suthoff E, et al. Impact of Early Versus Late Systemic Lupus Erythematosus Diagnosis on Clinical and Economic Outcomes. Appl Health Econ Health Policy. 2014;12(2):179-90.

    5. Walley T, Mantgani A. The UK General Practice Research Database. Lancet. 1997;350(9084):1097-9.

    6. Rees F, Doherty M, Grainge MJ, Davenport G, Lanyon P, Zhang W. The incidence and prevalence of systemic lupus erythematosus in the UK, 1999-2012. Ann Rheum Dis. 2014.

    7. Williams T, van Staa T, Puri S, Eaton S. Recent advances in the utility and use of the General Practice Research Database as an example of a UK Primary Care Data resource. Ther Adv Drug Saf. 2012;3(2):89-99.

    8. Watts RA, Al-Taiar A, Scott DG, Macgregor AJ. Prevalence and incidence of Wegener's granulomatosis in the UK general practice research database. Arthritis and rheumatism. 2009;61(10):1412-6.

    9. Schoonen WM, Kucera G, Coalson J, Li L, Rutstein M, Mowat F, et al. Epidemiology of immune thrombocytopenic purpura in the General Practice Research Database. British journal of haematology. 2009;145(2):235-44.

    10. Royston P, Ambler G, Sauerbrei W. The use of fractional polynomials to model continuous risk variables in epidemiology. International journal of epidemiology. 1999;28(5):964-74.

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