The added value of health indicators to mortality predictions in old age: A systematic review

Research output: Contribution to journalReviewResearchpeer-review

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The added value of health indicators to mortality predictions in old age : A systematic review. / Kusumastuti, Sasmita; Rozing, Maarten Pieter; Lund, Rikke; Mortensen, Erik Lykke; Westendorp, Rudi G J.

In: European Journal of Internal Medicine, Vol. 57, 2018, p. 7-18.

Research output: Contribution to journalReviewResearchpeer-review

Harvard

Kusumastuti, S, Rozing, MP, Lund, R, Mortensen, EL & Westendorp, RGJ 2018, 'The added value of health indicators to mortality predictions in old age: A systematic review', European Journal of Internal Medicine, vol. 57, pp. 7-18. https://doi.org/10.1016/j.ejim.2018.06.019

APA

Kusumastuti, S., Rozing, M. P., Lund, R., Mortensen, E. L., & Westendorp, R. G. J. (2018). The added value of health indicators to mortality predictions in old age: A systematic review. European Journal of Internal Medicine, 57, 7-18. https://doi.org/10.1016/j.ejim.2018.06.019

Vancouver

Kusumastuti S, Rozing MP, Lund R, Mortensen EL, Westendorp RGJ. The added value of health indicators to mortality predictions in old age: A systematic review. European Journal of Internal Medicine. 2018;57:7-18. https://doi.org/10.1016/j.ejim.2018.06.019

Author

Kusumastuti, Sasmita ; Rozing, Maarten Pieter ; Lund, Rikke ; Mortensen, Erik Lykke ; Westendorp, Rudi G J. / The added value of health indicators to mortality predictions in old age : A systematic review. In: European Journal of Internal Medicine. 2018 ; Vol. 57. pp. 7-18.

Bibtex

@article{7679465e97a64db99fdbe838b99eb968,
title = "The added value of health indicators to mortality predictions in old age: A systematic review",
abstract = "BACKGROUND: Numerous risk prediction models use indicators of health to predict mortality in old age. The added value to mortality predictions based on demographic variables is unknown.OBJECTIVE: To evaluate the accuracy of health indicators in predicting all-cause mortality among individuals aged 50+ using area under receiver operating characteristic curve (AUC). Specifically, to assess the added value of health indicators relative to demographic variables.METHODS: We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. There were no restrictions on study designs, follow-up duration, language, or publication dates. We also examined the quality of studies using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies.RESULTS: Out of 804 studies investigating all-cause mortality in older persons, 16 studies were eligible. In community-dwelling populations, the accuracy of demographic variables and health indicators combined ranged from AUC 0.71 to 0.82, indicating modest ability to predict mortality. Age contributed the most to mortality prediction (AUC 0.65 to 0.78) and compared to age and sex, the added values of genetics, physiology, functioning, mood, cognition, nutritional status, subjective health, disease, frailty, and lifestyle ranged from AUC 0.01 to 0.10. The lack of validation samples made it difficult to assess their true added value. Findings were similar in institutionalized populations. Heterogeneity of the studies prevented us from performing a meta-analysis.CONCLUSION: Age and sex contributed the most to mortality predictions in old age while the added value of health indicators is likely to be limited.",
author = "Sasmita Kusumastuti and Rozing, {Maarten Pieter} and Rikke Lund and Mortensen, {Erik Lykke} and Westendorp, {Rudi G J}",
note = "Copyright {\circledC} 2018 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.",
year = "2018",
doi = "10.1016/j.ejim.2018.06.019",
language = "English",
volume = "57",
pages = "7--18",
journal = "European Journal of Internal Medicine",
issn = "0953-6205",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - The added value of health indicators to mortality predictions in old age

T2 - A systematic review

AU - Kusumastuti, Sasmita

AU - Rozing, Maarten Pieter

AU - Lund, Rikke

AU - Mortensen, Erik Lykke

AU - Westendorp, Rudi G J

N1 - Copyright © 2018 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

PY - 2018

Y1 - 2018

N2 - BACKGROUND: Numerous risk prediction models use indicators of health to predict mortality in old age. The added value to mortality predictions based on demographic variables is unknown.OBJECTIVE: To evaluate the accuracy of health indicators in predicting all-cause mortality among individuals aged 50+ using area under receiver operating characteristic curve (AUC). Specifically, to assess the added value of health indicators relative to demographic variables.METHODS: We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. There were no restrictions on study designs, follow-up duration, language, or publication dates. We also examined the quality of studies using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies.RESULTS: Out of 804 studies investigating all-cause mortality in older persons, 16 studies were eligible. In community-dwelling populations, the accuracy of demographic variables and health indicators combined ranged from AUC 0.71 to 0.82, indicating modest ability to predict mortality. Age contributed the most to mortality prediction (AUC 0.65 to 0.78) and compared to age and sex, the added values of genetics, physiology, functioning, mood, cognition, nutritional status, subjective health, disease, frailty, and lifestyle ranged from AUC 0.01 to 0.10. The lack of validation samples made it difficult to assess their true added value. Findings were similar in institutionalized populations. Heterogeneity of the studies prevented us from performing a meta-analysis.CONCLUSION: Age and sex contributed the most to mortality predictions in old age while the added value of health indicators is likely to be limited.

AB - BACKGROUND: Numerous risk prediction models use indicators of health to predict mortality in old age. The added value to mortality predictions based on demographic variables is unknown.OBJECTIVE: To evaluate the accuracy of health indicators in predicting all-cause mortality among individuals aged 50+ using area under receiver operating characteristic curve (AUC). Specifically, to assess the added value of health indicators relative to demographic variables.METHODS: We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. There were no restrictions on study designs, follow-up duration, language, or publication dates. We also examined the quality of studies using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies.RESULTS: Out of 804 studies investigating all-cause mortality in older persons, 16 studies were eligible. In community-dwelling populations, the accuracy of demographic variables and health indicators combined ranged from AUC 0.71 to 0.82, indicating modest ability to predict mortality. Age contributed the most to mortality prediction (AUC 0.65 to 0.78) and compared to age and sex, the added values of genetics, physiology, functioning, mood, cognition, nutritional status, subjective health, disease, frailty, and lifestyle ranged from AUC 0.01 to 0.10. The lack of validation samples made it difficult to assess their true added value. Findings were similar in institutionalized populations. Heterogeneity of the studies prevented us from performing a meta-analysis.CONCLUSION: Age and sex contributed the most to mortality predictions in old age while the added value of health indicators is likely to be limited.

U2 - 10.1016/j.ejim.2018.06.019

DO - 10.1016/j.ejim.2018.06.019

M3 - Review

VL - 57

SP - 7

EP - 18

JO - European Journal of Internal Medicine

JF - European Journal of Internal Medicine

SN - 0953-6205

ER -

ID: 203559763