A multi-state model for joint modelling of terminal and non-terminal events with application to Whitehall II
Serious coronary heart disease (CHD) is a primary outcome in the Whitehall II study, a large epidemiological study of British civil servants. Both fatal (F) and non‐fatal (NF) CHD events are of interest and while essentially complete information is available on F events, the observation of NF events...
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| Published in | Statistics in medicine Vol. 26; no. 2; pp. 426 - 442 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Chichester, UK
John Wiley & Sons, Ltd
30.01.2007
Wiley Subscription Services, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0277-6715 1097-0258 |
| DOI | 10.1002/sim.2342 |
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| Abstract | Serious coronary heart disease (CHD) is a primary outcome in the Whitehall II study, a large epidemiological study of British civil servants. Both fatal (F) and non‐fatal (NF) CHD events are of interest and while essentially complete information is available on F events, the observation of NF events is subject to potentially informative censoring. A multi‐state model with an unobserved state is introduced for the joint modelling of F and NF events. Two model‐based assumptions ensure identifiability of the model and a parameter is introduced to allow sensitivity analyses concerning the assumption linked to informative censoring. Weibull transition rates, which include dependence on explanatory variables, are used in the analysis of Whitehall II data with a particular focus on the relationship between civil service grade and CHD events. Copyright © 2005 John Wiley & Sons, Ltd. |
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| AbstractList | Serious coronary heart disease (CHD) is a primary outcome in the Whitehall II study, a large epidemiological study of British civil servants. Both fatal (F) and non‐fatal (NF) CHD events are of interest and while essentially complete information is available on F events, the observation of NF events is subject to potentially informative censoring. A multi‐state model with an unobserved state is introduced for the joint modelling of F and NF events. Two model‐based assumptions ensure identifiability of the model and a parameter is introduced to allow sensitivity analyses concerning the assumption linked to informative censoring. Weibull transition rates, which include dependence on explanatory variables, are used in the analysis of Whitehall II data with a particular focus on the relationship between civil service grade and CHD events. Copyright © 2005 John Wiley & Sons, Ltd. Serious coronary heart disease (CHD) is a primary outcome in the Whitehall II study, a large epidemiological study of British civil servants. Both fatal (F) and non-fatal (NF) CHD events are of interest and while essentially complete information is available on F events, the observation of NF events is subject to potentially informative censoring. A multi-state model with an unobserved state is introduced for the joint modelling of F and NF events. Two model-based assumptions ensure identifiability of the model and a parameter is introduced to allow sensitivity analyses concerning the assumption linked to informative censoring. Weibull transition rates, which include dependence on explanatory variables, are used in the analysis of Whitehall II data with a particular focus on the relationship between civil service grade and CHD events.Serious coronary heart disease (CHD) is a primary outcome in the Whitehall II study, a large epidemiological study of British civil servants. Both fatal (F) and non-fatal (NF) CHD events are of interest and while essentially complete information is available on F events, the observation of NF events is subject to potentially informative censoring. A multi-state model with an unobserved state is introduced for the joint modelling of F and NF events. Two model-based assumptions ensure identifiability of the model and a parameter is introduced to allow sensitivity analyses concerning the assumption linked to informative censoring. Weibull transition rates, which include dependence on explanatory variables, are used in the analysis of Whitehall II data with a particular focus on the relationship between civil service grade and CHD events. Serious coronary heart disease (CHD) is a primary outcome in the Whitehall II study, a large epidemiological study of British civil servants. Both fatal (F) and non-fatal (NF) CHD events are of interest and while essentially complete information is available on F events, the observation of NF events is subject to potentially informative censoring. A multi-state model with an unobserved state is introduced for the joint modelling of F and NF events. Two model-based assumptions ensure identifiability of the model and a parameter is introduced to allow sensitivity analyses concerning the assumption linked to informative censoring. Weibull transition rates, which include dependence on explanatory variables, are used in the analysis of Whitehall II data with a particular focus on the relationship between civil service grade and CHD events. [PUBLICATION ABSTRACT] Serious coronary heart disease (CHD) is a primary outcome in the Whitehall II study, a large epidemiological study of British civil servants. Both fatal (F) and non-fatal (NF) CHD events are of interest and while essentially complete information is available on F events, the observation of NF events is subject to potentially informative censoring. A multi-state model with an unobserved state is introduced for the joint modelling of F and NF events. Two model-based assumptions ensure identifiability of the model and a parameter is introduced to allow sensitivity analyses concerning the assumption linked to informative censoring. Weibull transition rates, which include dependence on explanatory variables, are used in the analysis of Whitehall II data with a particular focus on the relationship between civil service grade and CHD events. |
| Author | Siannis, F. Head, J. Farewell, V. T. |
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| Cites_doi | 10.1093/biomet/65.1.141 10.1093/biomet/88.4.907 10.1023/A:1009636125294 10.1161/01.CIR.90.1.583 10.1046/j.1369-7412.2003.00423.x 10.1016/0140-6736(91)93068-K 10.1093/biomet/84.1.45 |
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| References_xml | – reference: Day R, Bryant J, Lefkopoulou M. Adaptation of bivariate frailty models for prediction, with application to biological markers as prognostic indicators. Biometrika 1997; 84:45-56. – reference: Rose G, Blackburn H, Gillum R, Prineas R. Cardiovascular Survey Methods (2nd edn). World Health Organization: Geneva, 1982. – reference: Fine JP, Jiang H, Chappell R. On semi-competing risks data. Biometrika 2001; 88:907-919. – reference: Marmot M, Smith GD, Stansfeld S, Patel C, North F, Head J, White I, Brunner E, Feeney A. Health inequalities among British civil servants: the Whitehall II study. The Lancet 1991; 337:1387-1393. – reference: Clayton D. A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika 1978; 65:141-151. – reference: Commenges D. Multi-state models in epidemiology. Lifetime Data Analysis 1999; 5:315-327. – reference: Tunstall-Pedoe H, Kuulasmaa K, Amouyel P, Aiveiler D, Rajakangas A, Pajak A. Myocardial infarction and coronary deaths in the World Health Organization MONICA project: registration procedures, event rates and case fatality rates in 38 populations in four continents. Circulation 1994; 90:583-612. – reference: Wang W. Nonparametric estimation of the sojourn time distributions for a multipath model. Journal of the Royal Statistical Society, Series B 2003; 65:921-935. – volume: 337 start-page: 1387 year: 1991 end-page: 1393 article-title: Health inequalities among British civil servants: the Whitehall II study publication-title: The Lancet – volume: 65 start-page: 141 year: 1978 end-page: 151 article-title: A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence publication-title: Biometrika – volume: 65 start-page: 921 year: 2003 end-page: 935 article-title: Nonparametric estimation of the sojourn time distributions for a multipath model publication-title: Journal of the Royal Statistical Society, Series B – volume: 84 start-page: 45 year: 1997 end-page: 56 article-title: Adaptation of bivariate frailty models for prediction, with application to biological markers as prognostic indicators publication-title: Biometrika – year: 1982 – volume: 90 start-page: 583 year: 1994 end-page: 612 article-title: Myocardial infarction and coronary deaths in the World Health Organization MONICA project: registration procedures, event rates and case fatality rates in 38 populations in four continents publication-title: Circulation – volume: 5 start-page: 315 year: 1999 end-page: 327 article-title: Multi‐state models in epidemiology publication-title: Lifetime Data Analysis – volume: 88 start-page: 907 year: 2001 end-page: 919 article-title: On semi‐competing risks data publication-title: Biometrika – ident: e_1_2_1_6_2 doi: 10.1093/biomet/65.1.141 – ident: e_1_2_1_5_2 doi: 10.1093/biomet/88.4.907 – ident: e_1_2_1_9_2 doi: 10.1023/A:1009636125294 – volume-title: Cardiovascular Survey Methods year: 1982 ident: e_1_2_1_3_2 – ident: e_1_2_1_4_2 doi: 10.1161/01.CIR.90.1.583 – ident: e_1_2_1_8_2 doi: 10.1046/j.1369-7412.2003.00423.x – ident: e_1_2_1_2_2 doi: 10.1016/0140-6736(91)93068-K – ident: e_1_2_1_7_2 doi: 10.1093/biomet/84.1.45 |
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| SubjectTerms | Adult Age Factors Cardiovascular disease Coronary Disease - epidemiology Coronary Disease - mortality Employment Female Humans Male Markov Chains Medical statistics Middle Aged Models, Biological Models, Statistical multi-state models semi-competing risks Sex Factors Statistical analysis United Kingdom - epidemiology Weibull models |
| Title | A multi-state model for joint modelling of terminal and non-terminal events with application to Whitehall II |
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