File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1111/j.1541-0420.2009.01340.x
- Scopus: eid_2-s2.0-77956798454
- PMID: 19912171
- WOS: WOS:000281950000006
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Statistical Analysis of Illness–Death Processes and Semicompeting Risks Data
Title | Statistical Analysis of Illness–Death Processes and Semicompeting Risks Data |
---|---|
Authors | |
Keywords | Copula Dependent Censoring Frailty Illness–death Model Proportional Hazards Semicompeting Risks Data Terminal Event |
Issue Date | 2010 |
Publisher | Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/BIOM |
Citation | Biometrics, 2010, v. 66, p. 716-725 How to Cite? |
Abstract | In many instances, a subject can experience both a nonterminal and terminal event where the terminal event (e.g., death) censors the nonterminal event (e.g., relapse) but not vice versa. Typically, the two events are correlated. This situation has been termed semicompeting risks (e.g., Fine, Jiang, and Chappell, 2001, 907–939 Wang, 2003, 257–273), and analysis has been based on a joint survival function of two event times over the positive quadrant but with observation restricted to the upper wedge. Implicitly, this approach entertains the idea of latent failure times and leads to discussion of a marginal distribution of the nonterminal event that is not grounded in reality. We argue that, similar to models for competing risks, latent failure times should generally be avoided in modeling such data. We note that semicompeting risks have more classically been described as an illness–death model and this formulation avoids any reference to latent times. We consider an illness–death model with shared frailty, which in its most restrictive form is identical to the semicompeting risks model that has been proposed and analyzed, but that allows for many generalizations and the simple incorporation of covariates. Nonparametric maximum likelihood estimation is used for inference and resulting estimates for the correlation parameter are compared with other proposed approaches. Asymptotic properties, simulations studies, and application to a randomized clinical trial in nasopharyngeal cancer evaluate and illustrate the methods. A simple and fast algorithm is developed for its numerical implementation. |
Persistent Identifier | http://hdl.handle.net/10722/221685 |
ISSN | 2023 Impact Factor: 1.4 2023 SCImago Journal Rankings: 1.480 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Xu, J | - |
dc.contributor.author | Kalbfleisch, JD | - |
dc.contributor.author | Tai, B | - |
dc.date.accessioned | 2015-12-04T15:29:06Z | - |
dc.date.available | 2015-12-04T15:29:06Z | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | Biometrics, 2010, v. 66, p. 716-725 | - |
dc.identifier.issn | 0006-341X | - |
dc.identifier.uri | http://hdl.handle.net/10722/221685 | - |
dc.description.abstract | In many instances, a subject can experience both a nonterminal and terminal event where the terminal event (e.g., death) censors the nonterminal event (e.g., relapse) but not vice versa. Typically, the two events are correlated. This situation has been termed semicompeting risks (e.g., Fine, Jiang, and Chappell, 2001, 907–939 Wang, 2003, 257–273), and analysis has been based on a joint survival function of two event times over the positive quadrant but with observation restricted to the upper wedge. Implicitly, this approach entertains the idea of latent failure times and leads to discussion of a marginal distribution of the nonterminal event that is not grounded in reality. We argue that, similar to models for competing risks, latent failure times should generally be avoided in modeling such data. We note that semicompeting risks have more classically been described as an illness–death model and this formulation avoids any reference to latent times. We consider an illness–death model with shared frailty, which in its most restrictive form is identical to the semicompeting risks model that has been proposed and analyzed, but that allows for many generalizations and the simple incorporation of covariates. Nonparametric maximum likelihood estimation is used for inference and resulting estimates for the correlation parameter are compared with other proposed approaches. Asymptotic properties, simulations studies, and application to a randomized clinical trial in nasopharyngeal cancer evaluate and illustrate the methods. A simple and fast algorithm is developed for its numerical implementation. | - |
dc.language | eng | - |
dc.publisher | Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/BIOM | - |
dc.relation.ispartof | Biometrics | - |
dc.subject | Copula | - |
dc.subject | Dependent Censoring | - |
dc.subject | Frailty | - |
dc.subject | Illness–death Model | - |
dc.subject | Proportional Hazards | - |
dc.subject | Semicompeting Risks Data | - |
dc.subject | Terminal Event | - |
dc.title | Statistical Analysis of Illness–Death Processes and Semicompeting Risks Data | - |
dc.type | Article | - |
dc.identifier.email | Xu, J: xujf@hku.hk | - |
dc.identifier.authority | Xu, J=rp02086 | - |
dc.identifier.doi | 10.1111/j.1541-0420.2009.01340.x | - |
dc.identifier.pmid | 19912171 | - |
dc.identifier.scopus | eid_2-s2.0-77956798454 | - |
dc.identifier.volume | 66 | - |
dc.identifier.spage | 716 | - |
dc.identifier.epage | 725 | - |
dc.identifier.isi | WOS:000281950000006 | - |
dc.identifier.issnl | 0006-341X | - |