Journal of Universal Computer Science (Nov 2023)

Towards a Traceable Data Model Accommodating Bounded Uncertainty for DST Based Computation of BRCA1/2 Mutation Probability With Age

  • Lorenz Gillner,
  • Ekaterina Auer

DOI
https://doi.org/10.3897/jucs.112797
Journal volume & issue
Vol. 29, no. 11
pp. 1361 – 1384

Abstract

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In this paper, we describe the requirements for traceable open-source data retrieval in the context of computation of BRCA1/2 mutation probabilities (mutations in two tumor-suppressor genes responsible for hereditary BReast or/and ovarian CAncer). We show how such data can be used to develop a Dempster-Shafer model for computing the probability of BRCA1/2 mutations enhanced by taking into account the actual age of a patient or a family member in an appropriate way even if it is not known exactly. The model is compared with PENN II and BOADICEA (based on undisclosed data), two established platforms for this purpose accessible online, as well as with our own previous models. A proof-of-concept implementation shows that set-based techniques are able to provide better information about mutation probabilities, simultaneously highlighting the necessity for ground truth data of high quality.

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