Format

Send to

Choose Destination
Eur J Intern Med. 2018 Nov;57:7-18. doi: 10.1016/j.ejim.2018.06.019. Epub 2018 Jul 14.

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

Author information

1
Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark; Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark. Electronic address: saku@sund.ku.dk.
2
Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark; Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark.
3
Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark; Section of Social Medicine, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
4
Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark; Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.

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.

KEYWORDS:

Mortality; Old age; Prognosis; Survival analysis; Systematic review

PMID:
30017559
DOI:
10.1016/j.ejim.2018.06.019
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center