Max Moldovan1, Jyoti Khadka2,3,4, Renuka Visvanathan5, Steve Wesselingh1, Maria C Inacio1. 1. South Australian Health and Medical Research Institute (SAHMRI), Registry of Senior Australians (ROSA), Adelaide, Australia. 2. Healthy Ageing Research Consortium and Registry of Senior Australians, South Australian Health and Medical Research Institute, Adelaide, Australia. 3. Health and Social Care Economics Group, College of Nursing and Health Science, Flinders University, Adelaide, Australia. 4. School of Business, University of South Australia, Adelaide, Australia. 5. University of Adelaide, The Queen Elizabeth Hospital, National Health and Medical Research Council of Australia Centre of Research Excellence in Frailty and Healthy Ageing, Registry of Senior Australians (ROSA), Adelaide, Australia.
Abstract
OBJECTIVES: To (1) use an elastic net (EN) algorithm to derive a frailty measure from a national aged care eligibility assessment program; (2) compare the ability of EN-based and a traditional cumulative deficit (CD) based frailty measures to predict mortality and entry into permanent residential care; (3) assess if the predictive ability can be improved by using weighted frailty measures. MATERIALS AND METHODS: A Cox proportional hazard model based EN algorithm was applied to the 2003-2013 cohort of 903 996 participants for selecting items to enter an EN based frailty measure. The out-of-sample predictive accuracy was measured by the area under the curve (AUC) from Cox models fitted to 80% training and validated on 20% testing samples. RESULTS: The EN approach resulted in a 178-item frailty measure including items excluded from the 44-item CD-based measure. The EN based measure was not statistically significantly different from the CD-based approach in terms of predicting mortality (AUC 0.641, 95% CI: 0.637-0.644 vs AUC 0.637, 95% CI: 0.634-0.641) and permanent care entry (AUC 0.626, 95% CI: 0.624-0.629 vs AUC 0.627, 95% CI: 0.625-0.63). However, the weighted EN based measure statistically outperforms the weighted CD measure for predicting mortality (AUC 0.774, 95% CI: 0.771-0.777 vs AUC 0.757, 95% CI: 0.754-0.760) and permanent care entry (AUC 0.676, 95% CI: 0.673-0.678 vs AUC 0.671, 95% CI: 0.668-0.674). CONCLUSIONS: The weighted EN and CD-based measures demonstrated similar prediction performance. The CD-based measure items are relevant to frailty measurement and easier to interpret. We recommend using the weighted and unweighted CD-based frailty measures.
OBJECTIVES: To (1) use an elastic net (EN) algorithm to derive a frailty measure from a national aged care eligibility assessment program; (2) compare the ability of EN-based and a traditional cumulative deficit (CD) based frailty measures to predict mortality and entry into permanent residential care; (3) assess if the predictive ability can be improved by using weighted frailty measures. MATERIALS AND METHODS: A Cox proportional hazard model based EN algorithm was applied to the 2003-2013 cohort of 903 996 participants for selecting items to enter an EN based frailty measure. The out-of-sample predictive accuracy was measured by the area under the curve (AUC) from Cox models fitted to 80% training and validated on 20% testing samples. RESULTS: The EN approach resulted in a 178-item frailty measure including items excluded from the 44-item CD-based measure. The EN based measure was not statistically significantly different from the CD-based approach in terms of predicting mortality (AUC 0.641, 95% CI: 0.637-0.644 vs AUC 0.637, 95% CI: 0.634-0.641) and permanent care entry (AUC 0.626, 95% CI: 0.624-0.629 vs AUC 0.627, 95% CI: 0.625-0.63). However, the weighted EN based measure statistically outperforms the weighted CD measure for predicting mortality (AUC 0.774, 95% CI: 0.771-0.777 vs AUC 0.757, 95% CI: 0.754-0.760) and permanent care entry (AUC 0.676, 95% CI: 0.673-0.678 vs AUC 0.671, 95% CI: 0.668-0.674). CONCLUSIONS: The weighted EN and CD-based measures demonstrated similar prediction performance. The CD-based measure items are relevant to frailty measurement and easier to interpret. We recommend using the weighted and unweighted CD-based frailty measures.
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