Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/26303
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Rizopoulos, Dimitris | - |
dc.contributor.author | MOLENBERGHS, Geert | - |
dc.contributor.author | LESAFFRE, Emmanuel | - |
dc.date.accessioned | 2018-07-12T10:58:32Z | - |
dc.date.available | 2018-07-12T10:58:32Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | BIOMETRICAL JOURNAL, 59(6), p. 1261-1276 | - |
dc.identifier.issn | 0323-3847 | - |
dc.identifier.uri | http://hdl.handle.net/1942/26303 | - |
dc.description.abstract | A key question in clinical practice is accurate prediction of patient prognosis. To this end, nowadays, physicians have at their disposal a variety of tests and biomarkers to aid them in optimizing medical care. These tests are often performed on a regular basis in order to closely follow the progression of the disease. In this setting, it is of interest to optimally utilize the recorded information and provide medically relevant summary measures, such as survival probabilities, which will aid in decision making. In this work, we present and compare two statistical techniques that provide dynamically updated estimates of survival probabilities, namely landmark analysis and joint models for longitudinal and time-to-event data. Special attention is given to the functional form linking the longitudinal and event time processes, and to measures of discrimination and calibration in the context of dynamic prediction. | - |
dc.description.sponsorship | The first author would like to acknowledge support by the Netherlands Organization for Scientific Research VIDI (grant number 016.146.301). | - |
dc.language.iso | en | - |
dc.publisher | WILEY | - |
dc.rights | (c) 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim | - |
dc.subject.other | Calibration; Discrimination; Prognostic modeling; Random effects; Risk prediction | - |
dc.subject.other | calibration; discrimination; prognostic modeling; random effects; risk prediction | - |
dc.title | Dynamic predictions with time-dependent covariates in survival analysis using joint modeling and landmarking | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 1276 | - |
dc.identifier.issue | 6 | - |
dc.identifier.spage | 1261 | - |
dc.identifier.volume | 59 | - |
local.format.pages | 16 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | [Rizopoulos, Dimitris; Lesaffre, Emmanuel M. E. H.] Erasmus MC, Dept Biostat, Rotterdam, Netherlands. [Molenberghs, Geert; Lesaffre, Emmanuel M. E. H.] Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat, Leuven, Belgium. [Molenberghs, Geert; Lesaffre, Emmanuel M. E. H.] Univ Hasselt, Hasselt, Belgium. | - |
local.publisher.place | HOBOKEN | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1002/bimj.201600238 | - |
dc.identifier.isi | 000418746100011 | - |
item.validation | ecoom 2019 | - |
item.accessRights | Restricted Access | - |
item.fullcitation | Rizopoulos, Dimitris; MOLENBERGHS, Geert & LESAFFRE, Emmanuel (2017) Dynamic predictions with time-dependent covariates in survival analysis using joint modeling and landmarking. In: BIOMETRICAL JOURNAL, 59(6), p. 1261-1276. | - |
item.fulltext | With Fulltext | - |
item.contributor | Rizopoulos, Dimitris | - |
item.contributor | MOLENBERGHS, Geert | - |
item.contributor | LESAFFRE, Emmanuel | - |
crisitem.journal.issn | 0323-3847 | - |
crisitem.journal.eissn | 1521-4036 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
rizopoulos 1.pdf Restricted Access | Published version | 484.95 kB | Adobe PDF | View/Open Request a copy |
DynPreds_authorversion.pdf Restricted Access | Peer-reviewed author version | 341.62 kB | Adobe PDF | View/Open Request a copy |
SCOPUSTM
Citations
20
checked on Sep 7, 2020
WEB OF SCIENCETM
Citations
75
checked on Apr 24, 2024
Page view(s)
64
checked on Sep 7, 2022
Download(s)
50
checked on Sep 7, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.