Article type
Abstract
Background: Few systematic reviews (SRs) exist on prevalence of rare diseases. Conducting one is valuable as it provides an accurate and current assessment of prevalence of the condition; allows comparisons across countries; and, highlights areas of high or low prevalence. It enables targeting of resources and treatment and allows planning and prioritisation of future research.
Objective: To investigate challenges of conducting a SR on prevalence of rare diseases and make recommendations for future research.
Method: Comparisons were made between the methodologies applied in 4 SRs of rare diseases: Duchene Muscular Dystrophy (DMD), Phenylketonuria (PKU), Morquio A syndrome and Neuronal ceroid lipofuscinosis type 2 (CLN2 disease). Outcomes were defining the research question, information retrieval, screening, data extraction and data synthesis.
Results: When defining inclusion criteria, investigate recommendations for diagnoses. In the absence of guidelines consider clinical input. For information retrieval, consider terms for disease classification and historical nomenclature. Additional sources include rare-disease websites, patient databases, clinical experts and patient groups. Exercise caution at title and abstract screening as rare diseases are often reported under umbrella terms. When extracting data distinguish between types of prevalence and, beware, as prevalence is often mis-reported as incidence. Synthesis is typically narrative. Prevalence type, historical nomenclature and diagnosis method are useful to categorise data.
Conclusion: Similarities exist between SRs of prevalence of rare diseases but individual conditions present unique challenges. A good knowledge of disease classification and historical nomenclature is essential for effective searching and screening. Whether diagnosis is simple or complex, it should be clearly and fully reported, data extracted and compared with other studies reporting the same outcome. Definitions of prevalence should be clearly extracted and compared to similar studies. Limitations surrounding individual studies and their effect on prevalence should be carefully considered.
Objective: To investigate challenges of conducting a SR on prevalence of rare diseases and make recommendations for future research.
Method: Comparisons were made between the methodologies applied in 4 SRs of rare diseases: Duchene Muscular Dystrophy (DMD), Phenylketonuria (PKU), Morquio A syndrome and Neuronal ceroid lipofuscinosis type 2 (CLN2 disease). Outcomes were defining the research question, information retrieval, screening, data extraction and data synthesis.
Results: When defining inclusion criteria, investigate recommendations for diagnoses. In the absence of guidelines consider clinical input. For information retrieval, consider terms for disease classification and historical nomenclature. Additional sources include rare-disease websites, patient databases, clinical experts and patient groups. Exercise caution at title and abstract screening as rare diseases are often reported under umbrella terms. When extracting data distinguish between types of prevalence and, beware, as prevalence is often mis-reported as incidence. Synthesis is typically narrative. Prevalence type, historical nomenclature and diagnosis method are useful to categorise data.
Conclusion: Similarities exist between SRs of prevalence of rare diseases but individual conditions present unique challenges. A good knowledge of disease classification and historical nomenclature is essential for effective searching and screening. Whether diagnosis is simple or complex, it should be clearly and fully reported, data extracted and compared with other studies reporting the same outcome. Definitions of prevalence should be clearly extracted and compared to similar studies. Limitations surrounding individual studies and their effect on prevalence should be carefully considered.