Abstract
ObjectivesTo assess the accuracy of self-reported giant cell arteritis (GCA) and polymyalgia rheumatica (PMR) diagnoses in a large French population-based prospective cohort, and to devise algorithms to improve their accuracy. MethodsThe E3N-EPIC cohort study (Etude Epidémiologique auprès des femmes de la Mutuelle Générale de l'Education Nationale) includes 98,995 French women born between 1925 and 1950, recruited in 1990 to study risk factors of cancer and chronic diseases. They completed biennially mailed questionnaires to update their health-related information and lifestyle characteristics. In three questionnaires, women could self-report a diagnosis of GCA/PMR. Those women were additionally sent a specific questionnaire, designed to ascertain self-reported diagnoses of GCA/PMR. Four algorithms were then devised to improve their identification. Accuracies of self-reported diagnoses and of each algorithm were calculated by comparing the diagnoses with a blinded medical chart review. ResultsAmong 98,995 participants, 1,392 women self-reported GCA/PMR. 830 women sent back the specific questionnaire, and 202 women provided medical charts. After independent review of the 202 medical charts, 87.6 % of the self-reported diagnoses of GCA/PMR were accurate. Using additional data from a specific questionnaire (diagnosis confirmation by a physician, and self-report of >3-month of glucocorticoids), and from a reimbursement database (at least two deliveries of glucocorticoids in less than 3 consecutive months) improved their accuracy (91.8 % to 92.8 %). ConclusionThe accuracy of self-reported diagnosis of GCA/PMR was high in the E3N-cohort but using additional data as a specific GCA/PMR questionnaire and/or corticosteroid reimbursement database further improved this accuracy. With nearly 600 detected cases of GCA/PMR, we will be able to investigate risk factors for GCA/PMR in women.
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