title: Development and application of a novel metric to assess effectiveness of biomedical data.
abstract: Design a metric to assess the comparative effectiveness of biomedical data elements within a study that incorporates their statistical relatedness to a given outcome variable as well as a measurement of the quality of their underlying data.
  
  
  
  The cohort consisted of 874 patients with adenocarcinoma of the lung, each with 47 clinical data elements. The p value for each element was calculated using the Cox proportional hazard univariable regression model with overall survival as the endpoint. An attribute or A-score was calculated by quantification of an element's four quality attributes; Completeness, Comprehensiveness, Consistency and Overall-cost. An effectiveness or E-score was obtained by calculating the conditional probabilities of the p-value and A-score within the given data set with their product equaling the effectiveness score (E-score).
  
  
  
  The E-score metric provided information about the utility of an element beyond an outcome-related p value ranking. E-scores for elements age-at-diagnosis, gender and tobacco-use showed utility above what their respective p values alone would indicate due to their relative ease of acquisition, that is, higher A-scores. Conversely, elements surgery-site, histologic-type and pathological-TNM stage were down-ranked in comparison to their p values based on lower A-scores caused by significantly higher acquisition costs.
  
  
  
  A novel metric termed E-score was developed which incorporates standard statistics with data quality metrics and was tested on elements from a large lung cohort. Results show that an element's underlying data quality is an important consideration in addition to p value correlation to outcome when determining the element's clinical or research utility in a study.
authors: Department of Biomedical Informatics, H Lee Moffitt Cancer and Research Institute, Tampa, Florida, USA.
authors: Gregory C
authors: GC
authors: Bloom
authors: Steven
authors: S
authors: Eschrich
authors: Gang
authors: G
authors: Han
authors: Gang
authors: G
authors: Hang
authors: Matthew B
authors: MB
authors: Schabath
authors: Neera
authors: N
authors: Bhansali
authors: Andrew M
authors: AM
authors: Hoerter
authors: Scott
authors: S
authors: Morgan
authors: David A
authors: DA
authors: Fenstermacher
keywords: Epidemiology; Oncology
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