title: Risk factors and predictive models of giant cell arteritis in polymyalgia rheumatica.
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).
  
  
  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.
authors.affiliation: Rheumatology Division, Hospital Universitario M. Valdecilla, Santander, Spain.
authors.forename: V
authors.initials: V
authors.lastname: Rodriguez-Valverde
authors.forename: J M
authors.initials: JM
authors.lastname: Sarabia
authors.forename: M A
authors.initials: MA
authors.lastname: González-Gay
authors.forename: M
authors.initials: M
authors.lastname: Figueroa
authors.forename: J
authors.initials: J
authors.lastname: Armona
authors.forename: R
authors.initials: R
authors.lastname: Blanco
authors.forename: J L
authors.initials: JL
authors.lastname: Fernández-Sueiro
authors.forename: V M
authors.initials: VM
authors.lastname: Martínez-Taboada
mesh_terms: D000368:Aged; D001706:Biopsy; D005260:Female; D013700:Giant Cell Arteritis / Q000150:complications / Q000175:diagnosis* / Q000473:pathology; D006261:Headache / Q000150:complications; D006801:Humans; D007571:Jaw Diseases / Q000150:complications; D016015:Logistic Models; D008297:Male; D015233:Models, Statistical; D011111:Polymyalgia Rheumatica / Q000150:complications*; D011237:Predictive Value of Tests; D012372:ROC Curve; D012189:Retrospective Studies; D012307:Risk Factors; D012680:Sensitivity and Specificity; D013699:Temporal Arteries / Q000473:pathology