Evaluation of incomplete multiple diagnostic tests, with an application in the colon cancer family registry study

Yi Zhang, Haitao Chu, Donglin Zeng

Research output: Contribution to journalArticlepeer-review


Accurate diagnosis of a molecularly defined subtype of cancer is often an important step toward its effective control and treatment. For the diagnosis of some subtypes of a cancer, a gold standard with perfect sensitivity and specificity may be unavailable. In those scenarios, tumor subtype status is commonly measured by multiple imperfect diagnostic markers. Additionally, in many such studies, some subjects are only measured by a subset of diagnostic tests and the missing probabilities may depend on the unknown disease status. In this paper, we present statistical methods based on the EM algorithm to evaluate incomplete multiple imperfect diagnostic tests under a missing at random assumption and one missing not at random scenario. We apply the proposed methods to a real data set from the National Cancer Institute (NCI) colon cancer family registry on diagnosing microsatellite instability for hereditary non-polyposis colorectal cancer to estimate diagnostic accuracy parameters (i.e. sensitivities and specificities), prevalence, and potential differential missing probabilities for 11 biomarker tests. Simulations are also conducted to evaluate the small-sample performance of our methods.

Original languageEnglish (US)
Pages (from-to)688-700
Number of pages13
JournalJournal of Applied Statistics
Issue number3
StatePublished - Mar 2014

Bibliographical note

Copyright 2013 Elsevier B.V., All rights reserved.


  • EM algorithm
  • colon cancer family registry study
  • diagnostic test
  • microsatellite instability
  • missing at random
  • missing not at random


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