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Prediction of disability-free survival in healthy older people
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AbstractProlonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people.Trial registrationClinicaltrials.gov (NCT01038583)
Springer Science and Business Media LLC
Johannes Tobias Neumann
Le T. P. Thao
Anne M. Murray
Emily Callander
Prudence R. Carr
Mark R. Nelson
Rory Wolfe
Robyn L. Woods
Christopher M. Reid
Raj C. Shah
Anne B. Newman
Jeff D. Williamson
Andrew M. Tonkin
John J. McNeil
John McNeil
Anne Murray
Lawrie Beilin
Andrew Chan
Jamehl Demons
Michael Ernst
Sara Espinoza
Matthew Goetz
Colin Johnston
Brenda Kirpach
Danny Liew
Karen Margolis
Frank Meyskens
Mark Nelson
Chris Reid
Raj Shah
Elsdon Storey
Andrew Tonkin
Rory Wolfe
Robyn Woods
John Zalcberg
Mark Nelson
Diane Ives
Michael Berk
Wendy Bernstein
Donna Brauer
Christine Burns
Trevor Chong
Geoff Cloud
Jamehl Demons
Geoffrey Donnan
Charles Eaton
Paul Fitzgerald
Peter Gibbs
Andrew Haydon
Michael Jelinek
Finlay Macrae
Suzanne Mahady
Mobin Malik
Karen Margolis
Catriona McLean
Anne Murray
Anne Newman
Luz Rodriguez
Suzanne Satterfield
Raj Shah
Elsdon Storey
Jeanne Tie
Andrew Tonkin
Gijsberta van Londen
Stephanie Ward
Jeff Williamson
Erica Wood
John Zalcberg
Jay Mohr
Garnet Anderson
Stuart Connolly
Larry Friedman
JoAnn Manson
Mary Sano
Sean Morrison
Erik Magnus Ohman
John McNeil
Robyn Woods
Walter Abhayaratna
Lawrie Beilin
Geoffrey Donnan
Peter Gibbs
Colin Johnston
Danny Liew
Trevor Lockett
Mark Nelson
Chris Reid
Nigel Stocks
Elsdon Storey
Andrew Tonkin
Rory Wolfe
John Zalcberg
Anne Murray
Chris Reid
Walter Abhayaratna
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Colin Johnston
Beth Lewis
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Title: Prediction of disability-free survival in healthy older people
Description:
AbstractProlonging survival in good health is a fundamental societal goal.
However, the leading determinants of disability-free survival in healthy older people have not been well established.
Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.
7 years median follow-up, was analysed.
At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability.
Disability-free survival outcome was defined as absence of dementia, persistent disability or death.
Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach.
Separate models were developed for men and women.
The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping.
We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.
6–77.
7).
Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index.
Additional risk factors for men included current smoking, and abnormal eGFR.
In women, diabetes and depression were additional predictors.
The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.
72 for men and 0.
75 for women.
Final models showed good calibration between the observed and predicted risks.
We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people.
Trial registrationClinicaltrials.
gov (NCT01038583).
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