gms | German Medical Science

54. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

07. bis 10.09.2009, Essen

Evaluating clinical validity in single affected offspring trio families

Meeting Abstract

  • Andreas Ziegler - Universität zu Lübeck, Lübeck
  • Jerome Carayol - IntegraGen SA, Evry, Frankreich
  • Frédéric Tores - IntegraGen SA, Evry, Frankreich
  • Francis Rousseau - IntegraGen SA, Evry, Frankreich
  • Patrick Lindenbaum - IntegraGen SA, Evry, Frankreich
  • Inke R. König - Universität zu Lübeck, Lübeck
  • Jörg Hager - IntegraGen SA, Evry, Frankreich

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 54. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds). Essen, 07.-10.09.2009. Düsseldorf: German Medical Science GMS Publishing House; 2009. Doc09gmds139

doi: 10.3205/09gmds139, urn:nbn:de:0183-09gmds1395

Veröffentlicht: 2. September 2009

© 2009 Ziegler et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen ( Er darf vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.



Purpose: Diagnostic accuracy of a genetic test involving multiple disease genes is evaluated using sensitivity and specificity. For estimation data from affected and unaffected subjects are required. For early onset diseases such as autism spectrum disorder (ASD) only data from families with affected offspring is available. We developed a novel approach for evaluating clinical validity in affected offspring families based on a risk score (RS) and illustrate it by combining information from four genes for risk assessment of ASD. We compare the new RS with standard approaches.

Methods: A Monte-Carlo simulation study was conducted for demonstrating the validity of the novel method for specificity, positive and negative likelihood ratios and the area under the curve. A varying number of single nucleotide polymorphisms (SNPs) was used in the genetic profile and two different scenarios for the genetic model. The approach is illustrated using families from the Autism Genetic Resource Exchange repository involving four SNPs from four genes.

Results: The novel approach for estimating specificity and the ROC curve from affected offspring families is valid. Analogously to other approaches utilizing pseudocontrols, estimates were slightly conservative. In the application, the increase per risk allele was 1.35 (95% confidence interval (CI): 1.16-1.58) for autism spectrum disorder, and the AUC was 0.59 (95% CI: 0.57-0.61).

Conclusions: The novel approach is appropriate for estimating measures of diagnostic accuracy from affected offspring families. Slightly conservative results can be expected.