Average weighted accuracy: Pragmatic analysis for a rapid diagnostics in categorizing acute lung infections (RADICAL) study

Ying Liu, Ephraim L. Tsalik, Yunyun Jiang, Emily R. Ko, Christopher W. Woods, Ricardo Henao, Scott R. Evans

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Patient management relies on diagnostic information to identify appropriate treatment. Standard evaluations of diagnostic tests consist of estimating sensitivity, specificity, positive/negative predictive values, likelihood ratios, and accuracy. Although useful, these metrics do not convey the tests' clinical value, which is critical to informing decision-making. Full appreciation of the clinical impact of a diagnostic test requires analyses that integrate sensitivity and specificity, account for the disease prevalence within the population of test application, and account for the relative importance of specificity vs sensitivity by considering the clinical implications of false-positive and false-negative results. We developed average weighted accuracy (AWA), representing a pragmatic metric of diagnostic yield or global utility of a diagnostic test. AWA can be used to compare test alternatives, even across different studies. We apply the AWA methodology to evaluate a new diagnostic test developed in the Rapid Diagnostics in Categorizing Acute Lung Infections (RADICAL) study.
Original languageEnglish (US)
Pages (from-to)2736-2742
Number of pages7
JournalClinical Infectious Diseases
Volume70
Issue number12
DOIs
StatePublished - Jun 10 2020
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15

ASJC Scopus subject areas

  • Infectious Diseases
  • Microbiology (medical)

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