OBJECTIVE: This scoping review will identify methodological guidance relevant to systematic reviews (SRs), clinical practice guidelines (CPGs), and health technology assessments (HTAs) for rare diseases, and examine methodological challenges associated with their development. INTRODUCTION: Rare diseases affect approximately 400 million people worldwide. However, individual rarity limits health care provider knowledge and awareness and, subsequently, management of rare diseases is hindered by diagnostic delays, limited treatment options, and high treatment costs. Heterogenous populations and sparse, low-quality evidence also impede research quality and render traditional evidence evaluation methods ill-suited to rare diseases. Consequently, existing methodological frameworks guiding evidence-based development of SRs, CPGs, and HTAs may not appropriately consider contextual nuances of rare diseases. ELIGIBILITY CRITERIA: This scoping review will consider both peer-reviewed and gray literature relevant to methodological guidance for SRs, CPGs, and HTAs. Eligible sources will focus on rare diseases collectively, or specific conditions that meet the criteria of a rare disease, and address at least 1 aspect of methodology used to develop SRs, CPGs, or HTAs relevant to rare disease contexts. METHODS: The 3-step search strategy began with an exploratory PubMed search to refine terms, which will be followed by comprehensive searches in MEDLINE, Embase, Scopus, and the Cochrane CENTRAL Library. Gray literature will be searched via Google Scholar, Orphanet, the World Health Organization Institutional Repository for Information Sharing, the International Network of Agencies for Health Technology Assessment, and the National Institute for Health and Care Excellence. Identified sources will be independently screened, selected, and extracted by multiple reviewers. Data will be analyzed using descriptive statistics and qualitative content analysis, then presented in summary tables and summarized descriptively. REVIEW REGISTRATION: OSF https://osf.io/mrfev.
