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Table 3 Key factors influencing success of screening studies for ultra-rare IEMs

From: Recommendations for patient screening in ultra-rare inherited metabolic diseases: what have we learned from Niemann-Pick disease type C?

Factor Recommendation
Team Ensure patient detection and data quality through use of multidisciplinary investigator teams
Cohort size Bear in mind that larger cohorts, possibly recruited via expert consortia/registries in at-risk cohorts, help capture the full phenotype range and prevalence data
Inclusion Consider the impact of inclusion criteria that are neither too restrictive nor too broad
Methods Employ methods based on associated advantages/limitations, minimally invasive sampling, formal requirements, and possible confounding factors
Genetics Consider that large NGS gene panels/WES allow screening for multiple diseases in whole cohorts, and factor in the sensitivity and specificity of genetic profiling methods
Biomarkers Choose biomarkers bearing in mind their sensitivity, specificity, validation, sample stability and ease of transport, and assay turnaround times
Clinical assessment Use available simple clinical tools that allow quick analyses of relevant symptom clusters
Laboratories Select reference laboratories with well-established infrastructure for selected, validated diagnostic method(s)
Consent Take patient consent limits into account, particularly for retrospective chart reviews/biobanks
Sustainability Preserve awareness and knowledge from screening studies in local diagnostic procedures and/or follow-up processes
Increased awareness Raise awareness of rare disorders as a group represent a significant healthcare problem: this can aid referral to appropriate specialist clinics in time