Prediction of disability-free survival in healthy older people

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, ASPREE investigators

Abstract

Prolonging 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 registration Clinicaltrials.gov (NCT01038583).

Keywords: Disability; Elderly; Healthy; Public Health; Risk prediction; Survival.

Conflict of interest statement

The authors declare no competing interests.

© 2022. The Author(s).

Figures

Figure 1
Figure 1
Discrimination of each selected predictor, of their combination when added sequentially in order of their AUC, and of the final models. Orange dots show the AUC at 5 years of models made with each predictor of not maintaining disability-free survival individually. Green dots show the AUC of models made by incrementally adding each predictor along the x-axis. The percentages show the added value of the current model against the previous model. Predictors are arranged by their inclusion frequency. Abbreviation: AUC, area under the curve
Figure 2
Figure 2
Calibration graph comparing the observed risk (based on Kaplan-Meier estimates) and the predicted risk with the final models, by tenths of the predicted probability. The red asterisk represents the bias-corrected predicted risks

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