ePCR : an R-package for survival and time-to-event prediction in advanced prostate cancer, applied to real-world patient cohorts

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Laajala , T D , Murtojärvi , M , Virkki , A & Aittokallio , T 2018 , ' ePCR : an R-package for survival and time-to-event prediction in advanced prostate cancer, applied to real-world patient cohorts ' , Bioinformatics , vol. 34 , no. 22 , pp. 3957-3959 . https://doi.org/10.1093/bioinformatics/bty477

Title: ePCR : an R-package for survival and time-to-event prediction in advanced prostate cancer, applied to real-world patient cohorts
Author: Laajala, Teemu D.; Murtojärvi, Mika; Virkki, Arho; Aittokallio, Tero
Contributor organization: Institute for Molecular Medicine Finland
University of Helsinki
Tero Aittokallio / Principal Investigator
Bioinformatics
Date: 2018-11-15
Language: eng
Number of pages: 3
Belongs to series: Bioinformatics
ISSN: 1367-4803
DOI: https://doi.org/10.1093/bioinformatics/bty477
URI: http://hdl.handle.net/10138/268483
Abstract: Motivation: Prognostic models are widely used in clinical decision-making, such as risk stratification and tailoring treatment strategies, with the aim to improve patient outcomes while reducing overall healthcare costs. While prognostic models have been adopted into clinical use, benchmarking their performance has been difficult due to lack of open clinical datasets. The recent DREAM 9.5 Prostate Cancer Challenge carried out an extensive benchmarking of prognostic models for metastatic Castration-Resistant Prostate Cancer (mCRPC), based on multiple cohorts of open clinical trial data. Results: We make available an open-source implementation of the top-performing model, ePCR, along with an extended toolbox for its further re-use and development, and demonstrate how to best apply the implemented model to real-world data cohorts of advanced prostate cancer patients.
Subject: PROGNOSTIC MODEL
3111 Biomedicine
1182 Biochemistry, cell and molecular biology
3122 Cancers
Peer reviewed: Yes
Rights: cc_by_nc
Usage restriction: openAccess
Self-archived version: publishedVersion


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