Tanja Högg

TL;DR: More frequent use of health care in patients with multiple sclerosis than in controls in the 5 years before a first demyelinating event, according to health administrative data, suggests the existence of a measurable multiple sclerosis prodrome.

TL;DR: Findings provide insight into the clinical characteristics of the MS prodrome using data mining analytics in the healthcare setting and Adjusted odds ratios and Area under the Curve metrics for the models' predictive performance were reported.

TL;DR: The overrepresentation of specific medications in MS cases, which was not fully explained by the physician diagnoses, may represent a signature of the MS prodrome.

TL;DR: A Bayesian model is proposed that relies on access to a validation subgroup with confirmed outcome status for all case-control pairs as well as prior knowledge about the positive and negative predictive value of the classification mechanism to adjust estimates for misclassification bias.

TL;DR: An approach to adjust exposure‐disease association estimates for disease misclassification, without the need of simplifying non‐differentiality assumptions, or prior information about a complicated classification mechanism is developed.