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Title:

Accommodating heterogeneous missing data patterns for prostate cancer risk prediction.

Document type:
Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.
Author(s):
Neumair, Matthias; Kattan, Michael W; Freedland, Stephen J; Haese, Alexander; Guerrios-Rivera, Lourdes; De Hoedt, Amanda M; Liss, Michael A; Leach, Robin J; Boorjian, Stephen A; Cooperberg, Matthew R; Poyet, Cedric; Saba, Karim; Herkommer, Kathleen; Meissner, Valentin H; Vickers, Andrew J; Ankerst, Donna P
Abstract:
BACKGROUND: We compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts, in which some cohorts do not collect some risk factors at all, and developed an online risk prediction tool that accommodates missing risk factors from the end-user. METHODS: Ten North American and European cohorts from the Prostate Biopsy Collaborative Group (PBCG) were used for fitting a risk prediction tool for clinically significant prostate ca...     »
Journal title abbreviation:
BMC Med Res Methodol
Year:
2022
Journal volume:
22
Journal issue:
1
Fulltext / DOI:
doi:10.1186/s12874-022-01674-x
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/35864460
Print-ISSN:
1471-2288
TUM Institution:
Klinik und Poliklinik für Urologie
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