Literature DB >> 9217613

Risk factors and predictive models of giant cell arteritis in polymyalgia rheumatica.

V Rodriguez-Valverde1, J M Sarabia, M A González-Gay, M Figueroa, J Armona, R Blanco, J L Fernández-Sueiro, V M Martínez-Taboada.   

Abstract

OBJECTIVE: To identify in polymyalgia rheumatica the best set of predictors for a positive temporal artery biopsy and to define predictive models with either a high or low probability of giant cell arteritis (GCA). PATIENTS AND METHODS: Retrospective study of 227 patients, 137 with polymyalgia rheumatica unassociated with arteritis (group A) and 90 with polymyalgia associated with biopsy-proven giant cell arteritis (group B or training set). Data on demographic features, clinical and laboratory abnormalities were collected. Risk factors for arteritis were estimated by nonlinear logistic regressions. Simple predictive models were constructed with those predictors more related to arteritis by multivariable analysis. These models were then tested in group B and in 89 cases of arteritis without polymyalgia rheumatica (group C or test set).
RESULTS: The best predictors of arteritis were a new headache odds ratio (OR) 13.6 (95% confidence interval [CI] 4.7 to 39.3); age at onset < 70 years OR 0.11 (CI 0.04 to 0.35); abnormal temporal arteries OR 4.2 (CI 1.3 to 13.7); raised liver enzymes OR 2.9 (CI 1.1 to 7.8), and jaw claudication OR 4.8 (CI 1.0 to 22.7). Amaurosis was only observed in patients with arteritis. Three subsets had a very high risk of arteritis: (1) Patients with recent headache, abnormal arteries, and > or = 70 years at disease onset: sensitivity 44%, positive predictive value (PPV) 93%, likelihood ratio (LR) 20.3; (2) patients with a new headache, jaw claudication, and abnormal arteries: sensitivity 34.4%, PPV 96.9%, LR 47.2; and (3) those, that in addition to the last 3 features, were > or = 70 years of age at disease onset: sensitivity 26.7%, PPV 100%. We could also identify a subset with a very low risk of arteritis constituted by patients < 70 years, without headache, and with clinically normal temporal arteries: sensitivity 1.1%, PPV 1.7%, LR 0.03. In group C or the test set, these four predictive models correctly identified 57.3%, 29.2%, 23.6, and 3.4% of patients, respectively.
CONCLUSIONS: In polymyalgia rheumatica it is feasible to identify subsets with a very high likelihood of GCA. Although in some of these subsets the diagnosis of arteritis is almost certain, we suggest that even then it should be confirmed by temporal artery biopsy. By contrast, in those patients with polymyalgia < 70 years and without cranial features of giant cell arteritis, the risk of vasculitis is so low that the biopsy could be initially avoided and the patient treated with low-dose corticosteroids.

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Year:  1997        PMID: 9217613     DOI: 10.1016/s0002-9343(97)00117-4

Source DB:  PubMed          Journal:  Am J Med        ISSN: 0002-9343            Impact factor:   4.965


  16 in total

Review 1.  Giant cell arteritis.

Authors:  J M Calvo-Romero
Journal:  Postgrad Med J       Date:  2003-09       Impact factor: 2.401

Review 2.  Polymyalgia rheumatica and giant cell arteritis in older patients: diagnosis and pharmacological management.

Authors:  Jean Schmidt; Kenneth J Warrington
Journal:  Drugs Aging       Date:  2011-08-01       Impact factor: 3.923

3.  Granulomatous liver disease and giant-cell arteritis.

Authors:  M A Heneghan; K M Feeley; N DeFaoite; M P Little; T A O'Gorman
Journal:  Dig Dis Sci       Date:  1998-09       Impact factor: 3.199

4.  The Use of a Nomogram to Visually Interpret a Logistic Regression Prediction Model for Giant Cell Arteritis.

Authors:  Edsel B Ing; Royce Ing
Journal:  Neuroophthalmology       Date:  2018-02-05

5.  Liver involvement in ANCA-associated vasculitis.

Authors:  Peter Willeke; Bernhard Schlüter; Armend Limani; Heidemarie Becker; Heiko Schotte
Journal:  Clin Rheumatol       Date:  2015-01-30       Impact factor: 2.980

6.  Biopsy proven and biopsy negative temporal arteritis: differences in clinical spectrum at the onset of the disease. Groupe de Recherche sur l'Artérite à Cellules Géantes.

Authors:  P Duhaut; L Pinède; H Bornet; S Demolombe-Ragué; C Dumontet; J Ninet; R Loire; J Pasquier
Journal:  Ann Rheum Dis       Date:  1999-06       Impact factor: 19.103

7.  Predictive clinical and laboratory factors in the diagnosis of temporal arteritis.

Authors:  M S Mohamed; T Bates
Journal:  Ann R Coll Surg Engl       Date:  2002-01       Impact factor: 1.891

8.  Effect of prior steroid treatment on temporal artery biopsy findings in giant cell arteritis.

Authors:  N Ray-Chaudhuri; D Ah Kiné; S O Tijani; D V Parums; N Cartlidge; N P Strong; M R Dayan
Journal:  Br J Ophthalmol       Date:  2002-05       Impact factor: 4.638

9.  Selective T cell receptor decrease in peripheral blood T lymphocytes of patients with polymyalgia rheumatica and giant cell arteritis.

Authors:  M Lopez-Hoyos; M J Bartolome-Pacheco; R Blanco; V Rodriguez-Valverde; V M Martinez-Taboada
Journal:  Ann Rheum Dis       Date:  2004-01       Impact factor: 19.103

10.  Temporal artery biopsy: impact on the clinical management of patients.

Authors:  M Sintler; A Garnham; A Mahmood; D Rittoo; H S Khaira; R K Vohra
Journal:  Indian J Surg       Date:  2008-05-21       Impact factor: 0.656

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