'Quality in, quality out', a stepwise approach to evidence-based medicine for rare diseases promoted by multiple endocrine neoplasia type 1. Issue 11 (November 2018)

• Record Type: Journal Article
• Authors: van Beek, Dirk-Jan; van Leeuwaarde, Rachel S; Pieterman, Carolina R C; Vriens, Menno R; Valk, Gerlof D
• Other Names: author non-byline.; P H Bisschop author non-byline.; I H M Borel Rinkes author non-byline.; O M Dekkers author non-byline.; M L Drent author non-byline.; B Havekes author non-byline.; W W de Herder author non-byline.; A R M M Hermus author non-byline.; A N A van der Horst-Schrivers author non-byline.; J de Jong author non-byline.; H F A Vasen author non-byline.; B A Zonnenberg author non-byline.
• Is Part Of: Endocrine connections. Volume 7:Issue 11(2018)
• Page Start: R260
• Page End: R274
• Publication Date: 2018-11
• Subjects: multiple endocrine neoplasia type 1 -- hereditary tumor syndrome -- research strategies -- database -- observational studies; Endocrinology -- Periodicals; 616.4005
• DOI: 10.1530/EC-18-0359
• Languages: English
• ISSNs: 2049-3614

Abstract

Abstract : Rare diseases pose specific challenges in the field of medical research to provide physicians with evidence-based guidelines derived from studies with sufficient quality. An example of these rare diseases is multiple endocrine neoplasia type 1 (MEN1), which is an autosomal dominant endocrine tumor syndrome with an estimated occurrence rate of 2–3 per 100, 000. For this complex disease, characterized by multiple endocrine tumors, it proves difficult to perform both adequate and feasible studies. The opinion of patients themselves is of utmost importance to identify the gaps in the evidence-based medicine regarding clinical care. In the search for scientific answers to clinical research questions, the aim for best available evidence is obvious. Observational studies within patient cohorts, although prone to bias, seem the most feasible study design regarding the disease prevalence. Knowledge and adaptation to all types of bias is demanded in the strive for answers. Guided by our research on MEN1 patients, we elaborate on strategies to identify sufficient patients, to maximize and maintain patient enrolment and to standardize the data collection process. Preferably, data collection is performed prospectively, however, under certain conditions, data storage in a longitudinal retrospective database with a disease-specific framework is suitable. Considering the global challenges on observational research on rare diseases, we propose a stepwise approach from clinical research questions to scientific answers.