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What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study
Despite myriad efforts among social scientists, epidemiologists, and clinicians to identify variables with strong linkages to mortality, few researchers have evaluated statistically the relative strength of a comprehensive set of predictors of survival. Here, we determine the strongest predictors of...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4951106/ https://www.ncbi.nlm.nih.gov/pubmed/27434271 http://dx.doi.org/10.1371/journal.pone.0159273 |
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author | Goldman, Noreen Glei, Dana A Weinstein, Maxine |
author_facet | Goldman, Noreen Glei, Dana A Weinstein, Maxine |
author_sort | Goldman, Noreen |
collection | PubMed |
description | Despite myriad efforts among social scientists, epidemiologists, and clinicians to identify variables with strong linkages to mortality, few researchers have evaluated statistically the relative strength of a comprehensive set of predictors of survival. Here, we determine the strongest predictors of five-year mortality in four national, prospective studies of older adults. We analyze nationally representative surveys of older adults in four countries with similar levels of life expectancy: England (n = 6113, ages 52+), the US (n = 2023, ages 50+), Costa Rica (n = 2694, ages 60+), and Taiwan (n = 1032, ages 53+). Each survey includes a broad set of demographic, social, health, and biological variables that have been shown previously to predict mortality. We rank 57 predictors, 25 of which are available in all four countries, net of age and sex. We use the area under the receiver operating characteristic curve and assess robustness with additional discrimination measures. We demonstrate consistent findings across four countries with different cultural traditions, levels of economic development, and epidemiological transitions. Self-reported measures of instrumental activities of daily living limitations, mobility limitations, and overall self-assessed health are among the top predictors in all four samples. C-reactive protein, additional inflammatory markers, homocysteine, serum albumin, three performance assessments (gait speed, grip strength, and chair stands), and exercise frequency also discriminate well between decedents and survivors when these measures are available. We identify several promising candidates that could improve mortality prediction for both population-based and clinical populations. Better prognostic tools are likely to provide researchers with new insights into the behavioral and biological pathways that underlie social stratification in health and may allow physicians to have more informed discussions with patients about end-of-life treatment and priorities. |
format | Online Article Text |
id | pubmed-4951106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-49511062016-08-08 What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study Goldman, Noreen Glei, Dana A Weinstein, Maxine PLoS One Research Article Despite myriad efforts among social scientists, epidemiologists, and clinicians to identify variables with strong linkages to mortality, few researchers have evaluated statistically the relative strength of a comprehensive set of predictors of survival. Here, we determine the strongest predictors of five-year mortality in four national, prospective studies of older adults. We analyze nationally representative surveys of older adults in four countries with similar levels of life expectancy: England (n = 6113, ages 52+), the US (n = 2023, ages 50+), Costa Rica (n = 2694, ages 60+), and Taiwan (n = 1032, ages 53+). Each survey includes a broad set of demographic, social, health, and biological variables that have been shown previously to predict mortality. We rank 57 predictors, 25 of which are available in all four countries, net of age and sex. We use the area under the receiver operating characteristic curve and assess robustness with additional discrimination measures. We demonstrate consistent findings across four countries with different cultural traditions, levels of economic development, and epidemiological transitions. Self-reported measures of instrumental activities of daily living limitations, mobility limitations, and overall self-assessed health are among the top predictors in all four samples. C-reactive protein, additional inflammatory markers, homocysteine, serum albumin, three performance assessments (gait speed, grip strength, and chair stands), and exercise frequency also discriminate well between decedents and survivors when these measures are available. We identify several promising candidates that could improve mortality prediction for both population-based and clinical populations. Better prognostic tools are likely to provide researchers with new insights into the behavioral and biological pathways that underlie social stratification in health and may allow physicians to have more informed discussions with patients about end-of-life treatment and priorities. Public Library of Science 2016-07-19 /pmc/articles/PMC4951106/ /pubmed/27434271 http://dx.doi.org/10.1371/journal.pone.0159273 Text en © 2016 Goldman et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Goldman, Noreen Glei, Dana A Weinstein, Maxine What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study |
title | What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study |
title_full | What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study |
title_fullStr | What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study |
title_full_unstemmed | What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study |
title_short | What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study |
title_sort | what matters most for predicting survival? a multinational population-based cohort study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4951106/ https://www.ncbi.nlm.nih.gov/pubmed/27434271 http://dx.doi.org/10.1371/journal.pone.0159273 |
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