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Linear combination methods to improve diagnostic/prognostic accuracy on future observations

  • Le Kang
  • , Aiyi Liu
  • , Lili Tian
  • , Andrew B. Lawson
  • , Duncan Lee
  • , Ying MacNab
  • United States Food and Drug Administration
  • National Institutes of Health

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

Multiple diagnostic tests or biomarkers can be combined to improve diagnostic accuracy. The problem of finding the optimal linear combinations of biomarkers to maximise the area under the receiver operating characteristic curve has been extensively addressed in the literature. The purpose of this article is threefold: (1) to provide an extensive review of the existing methods for biomarker combination; (2) to propose a new combination method, namely, the nonparametric stepwise approach; (3) to use leave-one-pair-out cross-validation method, instead of re-substitution method, which is overoptimistic and hence might lead to wrong conclusion, to empirically evaluate and compare the performance of different linear combination methods in yielding the largest area under receiver operating characteristic curve. A data set of Duchenne muscular dystrophy was analysed to illustrate the applications of the discussed combination methods.

Original languageEnglish
Pages (from-to)1359-1380
Number of pages22
JournalStatistical Methods in Medical Research
Volume25
Issue number4
DOIs
StatePublished - Aug 1 2016

Keywords

  • area under the receiver operating characteristic curve
  • diagnostic/prognostic accuracy
  • linear combination
  • Multiple biomarkers
  • receiver operating characteristic curve

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