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

Fertility biomarkers predict differential survival in a long-term follow up study of male infertility. Capturing and treating heterogeneity

Meeting Abstract

  • Ronny Westerman - Philipps-Universität Marburg, Marburg
  • Kathrina Pyka - Philipps-Universität, Marburg
  • Hanna Seydel - Philipps-Universität, Marburg
  • Walter Krause - Philipps-Universität, Marburg
  • Ulrich Mueller - Philipps-University, Marburg

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. Doc09gmds125

doi: 10.3205/09gmds125, urn:nbn:de:0183-09gmds1254

Veröffentlicht: 2. September 2009

© 2009 Westerman 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.



Introduction: In this paper we want to prove the effect of heterogeneity in order to defective survival curves for fertile ans sufertile men. The intention of our research isn’t only focused on testing the effect of heterogeneity more over we want to implicate indicators for evaluating the intensities. A convenient way to demonstrate the intensity of heterogeneity on the population hazards could be done by using Frailty Models.

Methods: The use of a gamma distribution for the frailty variation have two essen-tial advantages: First the frailty distribution of the survivors at any given age follows a gamma distribution specified with the same shape parameter but a different scale parameter, second the frailty distribution among person dying at any age is also gamma distributed with an in-creasing shape parameter by one and a scale parameter, as a function for the age of death. The gamma distribution is one of the most flexible statistical distributions and can be used alternatively for any other distributions.

Data set: The data set includes all infertility patients who had attended the fertility and sterility office of the department of andrology at Marburg University Hospital for semen analysis between 1949 and 1998 who were born before 1942. Until now we have analyzed more than 2.000 medical records. After excluding cases for diseases which were identified that might be effect fertility, we have to distinguish between two subgroups.

Results and conclusions: In our analysis the intensity of unobserved heterogeneity is very low but therefore one have to consider for the estimations. It has to be mention that age-specific effects and within-group correlation in cohorts can be assert as the major reason for the disparity for azoospermic and oligospermic men and might be better predictors for the population hazards.


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