FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3011751388> ?p ?o ?g. }

• W3011751388 endingPage "1393" @default.
• W3011751388 startingPage "1371" @default.
• W3011751388 abstract "Abstract In clinical research and practice, landmark models are commonly used to predict the risk of an adverse future event, using patients' longitudinal biomarker data as predictors. However, these data are often observable only at intermittent visits, making their measurement times irregularly spaced and unsynchronized across different subjects. This poses challenges to conducting dynamic prediction at any post‐baseline time. A simple solution is the last‐value‐carry‐forward method, but this may result in bias for the risk model estimation and prediction. Another option is to jointly model the longitudinal and survival processes with a shared random effects model. However, when dealing with multiple biomarkers, this approach often results in high‐dimensional integrals without a closed‐form solution, and thus the computational burden limits its software development and practical use. In this article, we propose to process the longitudinal data by functional principal component analysis techniques, and then use the processed information as predictors in a class of flexible linear transformation models to predict the distribution of residual time‐to‐event occurrence. The measurement schemes for multiple biomarkers are allowed to be different within subject and across subjects. Dynamic prediction can be performed in a real‐time fashion. The advantages of our proposed method are demonstrated by simulation studies. We apply our approach to the African American Study of Kidney Disease and Hypertension, predicting patients' risk of kidney failure or death by using four important longitudinal biomarkers for renal functions." @default.
• W3011751388 created "2020-03-23" @default.
• W3011751388 creator A5057822243 @default.
• W3011751388 creator A5064564309 @default.
• W3011751388 creator A5082223383 @default.
• W3011751388 date "2020-03-20" @default.
• W3011751388 modified "2023-10-15" @default.
• W3011751388 title "Dynamic prediction of time to a clinical event with sparse and irregularly measured longitudinal biomarkers" @default.
• W3011751388 cites W1556637198 @default.
• W3011751388 cites W1846287826 @default.
• W3011751388 cites W1875949582 @default.
• W3011751388 cites W1920526183 @default.
• W3011751388 cites W1965165969 @default.
• W3011751388 cites W1985533409 @default.
• W3011751388 cites W1986546598 @default.
• W3011751388 cites W1995496685 @default.
• W3011751388 cites W1999142863 @default.
• W3011751388 cites W2001496329 @default.
• W3011751388 cites W2004655916 @default.
• W3011751388 cites W2007022861 @default.
• W3011751388 cites W2012222551 @default.
• W3011751388 cites W2012515680 @default.
• W3011751388 cites W2029697998 @default.
• W3011751388 cites W2030840862 @default.
• W3011751388 cites W2031511512 @default.
• W3011751388 cites W2032758468 @default.
• W3011751388 cites W2034945547 @default.
• W3011751388 cites W2037681041 @default.
• W3011751388 cites W2040669081 @default.
• W3011751388 cites W2045516356 @default.
• W3011751388 cites W2050850754 @default.
• W3011751388 cites W2050912805 @default.
• W3011751388 cites W2066555826 @default.
• W3011751388 cites W206706296 @default.
• W3011751388 cites W2078455576 @default.
• W3011751388 cites W2079272324 @default.
• W3011751388 cites W2081056762 @default.
• W3011751388 cites W2082174016 @default.
• W3011751388 cites W2083855756 @default.
• W3011751388 cites W2085579733 @default.
• W3011751388 cites W2086904567 @default.
• W3011751388 cites W2091083714 @default.
• W3011751388 cites W2103040281 @default.
• W3011751388 cites W2117653440 @default.
• W3011751388 cites W2121199907 @default.
• W3011751388 cites W2122095984 @default.
• W3011751388 cites W2122156348 @default.
• W3011751388 cites W2123664981 @default.
• W3011751388 cites W2129336294 @default.
• W3011751388 cites W2130043538 @default.
• W3011751388 cites W2132911252 @default.
• W3011751388 cites W2133097426 @default.
• W3011751388 cites W2134413432 @default.
• W3011751388 cites W2144148350 @default.
• W3011751388 cites W2145997692 @default.
• W3011751388 cites W2147243255 @default.
• W3011751388 cites W2147263187 @default.
• W3011751388 cites W2152445234 @default.
• W3011751388 cites W2156004795 @default.
• W3011751388 cites W2160283547 @default.
• W3011751388 cites W2165817472 @default.
• W3011751388 cites W2224874975 @default.
• W3011751388 cites W2230970864 @default.
• W3011751388 cites W2346110032 @default.
• W3011751388 cites W2497318341 @default.
• W3011751388 cites W2512685240 @default.
• W3011751388 cites W2552447100 @default.
• W3011751388 cites W2559278413 @default.
• W3011751388 cites W2581175278 @default.
• W3011751388 cites W2741235538 @default.
• W3011751388 cites W2762411923 @default.
• W3011751388 cites W2783438409 @default.
• W3011751388 cites W2806456507 @default.
• W3011751388 cites W2901213706 @default.
• W3011751388 cites W2902552024 @default.
• W3011751388 cites W2906421128 @default.
• W3011751388 cites W2949537047 @default.
• W3011751388 cites W298486776 @default.
• W3011751388 cites W3103855587 @default.
• W3011751388 cites W4205685297 @default.
• W3011751388 cites W4239330499 @default.
• W3011751388 cites W628731042 @default.
• W3011751388 cites W636916345 @default.
• W3011751388 doi "https://doi.org/10.1002/bimj.201900112" @default.
• W3011751388 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7502505" @default.
• W3011751388 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32196728" @default.
• W3011751388 hasPublicationYear "2020" @default.
• W3011751388 type Work @default.
• W3011751388 sameAs 3011751388 @default.
• W3011751388 citedByCount "4" @default.
• W3011751388 countsByYear W30117513882021 @default.
• W3011751388 countsByYear W30117513882022 @default.
• W3011751388 countsByYear W30117513882023 @default.
• W3011751388 crossrefType "journal-article" @default.
• W3011751388 hasAuthorship W3011751388A5057822243 @default.
• W3011751388 hasAuthorship W3011751388A5064564309 @default.
• W3011751388 hasAuthorship W3011751388A5082223383 @default.
• W3011751388 hasBestOaLocation W30117513881 @default.

• next