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BACKGROUND: Recessive dystrophic epidermolysis bullosa (RDEB) is an inherited genetic disorder characterized by recurrent and chronic open wounds with significant morbidity, impaired quality of life, and early mortality. RDEB patients demonstrate reduction or structural alteration type VII collagen (C7) owing to mutations in the gene COL7A1, the main component of anchoring fibrils (AF) necessary to maintain epidermal-dermal cohesion. While over 700 alterations in COL7A1 have been reported to cause dystrophic epidermolysis bullosa (DEB), which may be inherited in an autosomal dominant (DDEB) or autosomal recessive pattern (RDEB), the incidence and prevalence of RDEB is not well defined. To date, the widely estimated incidence (0.2-6.65 per million births) and prevalence (3.5-20.4 per million people) of RDEB has been primarily characterized by limited analyses of clinical databases or registries. METHODS: Using a genetic modelling approach, we use whole exome and genome sequencing data to estimate the allele frequency of pathogenic variants. Through the ClinVar and NCBI database of human genome variants and phenotypes, DEB Register, and analyzing premature COL7A1 termination variants we built a model to predict the pathogenicity of previously unclassified variants. We applied the model to publicly available sequences from the Exome Aggregation Consortium (ExAC) and Genome Aggregation Database (gnomAD) and identified variants which were classified as pathogenic for RDEB from which we estimate disease incidence and prevalence. RESULTS: Genetic modelling applied to the whole exome and genome sequencing data resulted in the identification of predicted RDEB pathogenic alleles, from which our estimate of the incidence of RDEB is 95 per million live births, 30 times the 3.05 per million live birth incidence estimated by the National Epidermolysis Bullosa Registry (NEBR). Using a simulation approach, we estimate a mean of approximately 3,850 patients in the US who may benefit from COL7A1-mediated treatments in the US. CONCLUSION: We conclude that genetic allele frequency estimation may enhance the underdiagnosis of rare genetic diseases generally, and RDEB specifically, which may improve incidence and prevalence estimates of patients who may benefit from treatment.
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OBJECTIVES: It is often vital to identify, prioritize, and select quality improvement projects in a hospital. Yet, a methodology, which utilizes experts' opinions with different points of view, is needed for better decision making. METHODS: The proposed methodology utilizes the cause-and-effect diagram to identify improvement projects and construct a project hierarchy for a problem. The right improvement projects are then prioritized and selected using a weighting scheme of analytical hierarchy process by aggregating experts' opinions. An approach for collecting data from experts and a graphical display for summarizing the obtained information are also provided. RESULTS: The methodology is implemented for improving a hospital appointment system. The top-ranked 2 major project categories for improvements were identified to be system- and accessibility-related causes (45%) and capacity-related causes (28%), respectively. For each of the major project category, subprojects were then ranked for selecting the improvement needs. CONCLUSION: The methodology is useful in cases where an aggregate decision based on experts' opinions is expected. Some suggestions for practical implementations are provided.
