South Australian Health and Medical Research Institute (SAHMRI), Registry of Senior Australians (ROSA), Adelaide, Australia.
Healthy Ageing Research Consortium and Registry of Senior Australians, South Australian Health and Medical Research Institute, Adelaide, Australia.
J Am Med Inform Assoc. 2020 Mar 1;27(3):419-428. doi: 10.1093/jamia/ocz210.
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.
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.
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).
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.
(1)利用弹性网络(EN)算法从国家老年护理资格评估计划中得出衰弱测量值;(2)比较基于 EN 和传统累积缺陷(CD)的衰弱测量值预测死亡率和进入永久性居住护理的能力;(3)评估通过使用加权衰弱测量值是否可以提高预测能力。
对 2003-2013 年 903996 名参与者的队列应用基于 Cox 比例风险模型的 EN 算法,以选择进入基于 EN 的衰弱测量的项目。通过在 80%的训练样本上拟合 Cox 模型并在 20%的测试样本上验证来测量样本外预测准确性。
EN 方法产生了一个包含从 44 项 CD 为基础的方法中排除的项目的 178 项衰弱测量值。基于 EN 的方法在预测死亡率方面与基于 CD 的方法没有统计学差异(AUC 0.641,95%CI:0.637-0.644 与 AUC 0.637,95%CI:0.634-0.641)和永久性护理进入(AUC 0.626,95%CI:0.624-0.629 与 AUC 0.627,95%CI:0.625-0.63)。然而,加权基于 EN 的方法在预测死亡率方面优于加权 CD 方法(AUC 0.774,95%CI:0.771-0.777 与 AUC 0.757,95%CI:0.754-0.760)和永久性护理进入(AUC 0.676,95%CI:0.673-0.678 与 AUC 0.671,95%CI:0.668-0.674)。
加权基于 EN 和 CD 的方法表现出相似的预测性能。基于 CD 的方法的项目与衰弱测量相关,更容易解释。我们建议使用加权和非加权基于 CD 的衰弱测量值。