Improving accuracy of self-reported diagnoses of rheumatoid arthritis in the French prospective E3N-EPIC cohort: A validation study

Abstract

Objectives The French E3N-EPIC (Etude Epidémiologique auprès des femmes de la Mutuelle générale de l'Education Nationale-European Prospective Investigation into Cancer and Nutrition) cohort enrolled 98 995 women aged 40 to 65 years at inclusion since 1990 to study the main risk factors for cancer and severe chronic conditions in women. They were prospectively followed with biennially self-Administered questionnaires collecting self-reported medical, environmental and lifestyle data. Our objective was to assess the accuracy of self-reported diagnoses of rheumatoid arthritis (RA) and to devise algorithms to improve the ascertainment of RA cases in our cohort. Design A validation study. Participants Women who self-reported an inflammatory rheumatic disease (IRD) were asked to provide access to their medical record, and to answer an IRD questionnaire. Medical records were independently reviewed. Primary and secondary outcome measures Positive predictive values (PPV) of self-reported RA alone, then coupled with the IRD questionnaire, and with a medication reimbursement database were assessed. These algorithms were then applied to the whole cohort to ascertain RA cases. Results Of the 98 995 participants, 2692 self-reported RA. Medical records were available for a sample of 399 participants, including 305 who self-reported RA. Self-reported RA was accurate only for 42% participants. Combining self-reported diagnoses to answers to a specific IRD questionnaire or to the medication reimbursement database improved the PPV (75.6% and 90.1%, respectively). Using the devised algorithms, we could identify 964 RA cases in our cohort. Conclusion Accuracy of self-reported RA is poor but adding answers to a specific questionnaire or data from a medication reimbursement database performed satisfactorily to identify RA cases in our cohort. It will subsequently allow investigating many potential risk factors of RA in women.