COPD exacerbation incidence rates are often ascertained retrospectively through patient recall and self-reports. We compared exacerbation ascertainment through patient self-reports and single-physician chart review to central adjudication by a committee and explored determinants and consequences of misclassification.
Self-reported exacerbations (event-based definition) in 409 primary care patients with COPD participating in the International Collaborative Effort on Chronic Obstructive Lung Disease: Exacerbation Risk Index Cohorts (ICE COLD ERIC) cohort were ascertained every 6 months over 3 years. Exacerbations were adjudicated by single experienced physicians and an adjudication committee who had information from patient charts. We assessed the accuracy (sensitivities and specificities) of self-reports and single-physician chart review against a central adjudication committee (AC) (reference standard). We used multinomial logistic regression and bootstrap stability analyses to explore determinants of misclassifications.
The AC identified 648 exacerbations, corresponding to an incidence rate of 0.60 ± 0.83 exacerbations/patient-year and a cumulative incidence proportion of 58.9%. Patients self-reported 841 exacerbations (incidence rate, 0.75 ± 1.01; incidence proportion, 59.7%). The sensitivity and specificity of self-reports were 84% and 76%, respectively, those of single-physician chart review were between 89% and 96% and 87% and 99%, respectively. The multinomial regression model and bootstrap selection showed that having experienced more exacerbations was the only factor consistently associated with underreporting and overreporting of exacerbations (underreporters: relative risk ratio [RRR], 2.16; 95% CI, 1.76-2.65 and overreporters: RRR, 1.67; 95% CI, 1.39-2.00).
Patient 6-month recall of exacerbation events are inaccurate. This may lead to inaccurate estimates of incidence measures and underestimation of treatment effects. The use of multiple data sources combined with event adjudication could substantially reduce sample size requirements and possibly cost of studies.
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