TY - JOUR
T1 - Semicompeting risks in aging research
T2 - methods, issues and needs
AU - Varadhan, Ravi
AU - Xue, Qian Li
AU - Bandeen-Roche, Karen
N1 - Funding Information:
Acknowledgements Ravi Varadhan is a Brookdale Leadership in Aging Fellow and would like to thank the Brookdale Foundation for their support. The authors would also like to thank the support from the Johns Hopkins Older Americans Independence Center under the NIA/NIH contract P30-AG02133 and the Johns Hopkins Alzheimer’s Disease Research Center, NIA P50 AG005146.
Publisher Copyright:
© 2014, Springer Science+Business Media New York.
PY - 2014/10
Y1 - 2014/10
N2 - A semicompeting risks problem involves two-types of events: a nonterminal and a terminal event (death). Typically, the nonterminal event is the focus of the study, but the terminal event can preclude the occurrence of the nonterminal event. Semicompeting risks are ubiquitous in studies of aging. Examples of semicompeting risk dyads include: dementia and death, frailty syndrome and death, disability and death, and nursing home placement and death. Semicompeting risk models can be divided into two broad classes: models based only on observables quantities (Formula presented.). This model is a special case of the multistate models, which has been an active area of methodology development. During the past decade and a half, there has also been a flurry of methodological activity on semicompeting risks based on latent failure times (Formula presented.) models. These advances notwithstanding, the semicompeting risks methodology has not penetrated biomedical research, in general, and gerontological research, in particular. Some possible reasons for this lack of uptake are: the methods are relatively new and sophisticated, conceptual problems associated with potential failure time models are difficult to overcome, paucity of expository articles aimed at educating practitioners, and non-availability of readily usable software. The main goals of this review article are: (i) to describe the major types of semicompeting risks problems arising in aging research, (ii) to provide a brief survey of the semicompeting risks methods, (iii) to suggest appropriate methods for addressing the problems in aging research, (iv) to highlight areas where more work is needed, and (v) to suggest ways to facilitate the uptake of the semicompeting risks methodology by the broader biomedical research community.
AB - A semicompeting risks problem involves two-types of events: a nonterminal and a terminal event (death). Typically, the nonterminal event is the focus of the study, but the terminal event can preclude the occurrence of the nonterminal event. Semicompeting risks are ubiquitous in studies of aging. Examples of semicompeting risk dyads include: dementia and death, frailty syndrome and death, disability and death, and nursing home placement and death. Semicompeting risk models can be divided into two broad classes: models based only on observables quantities (Formula presented.). This model is a special case of the multistate models, which has been an active area of methodology development. During the past decade and a half, there has also been a flurry of methodological activity on semicompeting risks based on latent failure times (Formula presented.) models. These advances notwithstanding, the semicompeting risks methodology has not penetrated biomedical research, in general, and gerontological research, in particular. Some possible reasons for this lack of uptake are: the methods are relatively new and sophisticated, conceptual problems associated with potential failure time models are difficult to overcome, paucity of expository articles aimed at educating practitioners, and non-availability of readily usable software. The main goals of this review article are: (i) to describe the major types of semicompeting risks problems arising in aging research, (ii) to provide a brief survey of the semicompeting risks methods, (iii) to suggest appropriate methods for addressing the problems in aging research, (iv) to highlight areas where more work is needed, and (v) to suggest ways to facilitate the uptake of the semicompeting risks methodology by the broader biomedical research community.
KW - Causal inference
KW - Competing risks
KW - Informative censoring
KW - Multi-state models
KW - Potential failure times
KW - Semicompeting processes
UR - http://www.scopus.com/inward/record.url?scp=84939897720&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84939897720&partnerID=8YFLogxK
U2 - 10.1007/s10985-014-9295-7
DO - 10.1007/s10985-014-9295-7
M3 - Article
C2 - 24729136
AN - SCOPUS:84939897720
SN - 1380-7870
VL - 20
SP - 538
EP - 562
JO - Lifetime Data Analysis
JF - Lifetime Data Analysis
IS - 4
ER -