Diagnostic Prediction of Von Willebrand Disease using Multiple Bleeding Phenomics Datasets.

The rigorous assessment of bleeding symptoms is a key component in establishing a diagnosis in patients suspected of having von Willebrand disease (VWD) and other inherited bleeding disorders. Multiple bleeding questionnaires have been developed and validated to capture bleeding history phenotypes for assessing patients with bleeding disorders. In this study we developed a prediction model based on Naïve Bayes decision tree classifier by analyzing various phenotypic attributes derived from multiple bleeding questionnaires. We evaluated the classification effectiveness derived from the top 25 attributes with highest discriminations on prediction of VWD. We used data from 952 patients and the classifier achieved a precision of 95%, recall of 94%, and a Receiving Operating Curve (ROC) area under the curve of 0.97.

Development and evaluation of a study design typology for human research.

A systematic classification of study designs would be useful for researchers, systematic reviewers, readers, and research administrators, among others. As part of the Human Studies Database Project, we developed the Study Design Typology to standardize the classification of study designs in human research. We then performed a multiple observer masked evaluation of active research protocols in four institutions according to a standardized protocol. Thirty-five protocols were classified by three reviewers each into one of nine high-level study designs for interventional and observational research (e.g., N-of-1, Parallel Group, Case Crossover). Rater classification agreement was moderately high for the 35 protocols (Fleiss' kappa = 0.442) and higher still for the 23 quantitative studies (Fleiss' kappa = 0.463). We conclude that our typology shows initial promise for reliably distinguishing study design types for quantitative human research.

Creating an ontology-based human phenotyping system: The Rockefeller University bleeding history experience.

The lack of standardized methods for human phenotyping is a major obstacle in translational science. We have developed a bleeding history phenotyping system comprising an ontology, a questionnaire, a Web-based phenotype recording instrument (PRI), and a database. The ontology facilitates transparency, collaboration, aggregation of data, and data analysis. The integrated system allows investigators worldwide to use the PRI, add their de-identified data to the database, and query the aggregated data. Thus, this system can increase the power to detect genotype-phenotype-environment relationships and help new investigators begin their studies. We anticipate that this approach may be applicable to other disorders.