ArticleAnnals of epidemiology2015
Quantifying the value of biomarkers for predicting mortality.
Article in Annals of epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Reconsidering the Clinical Utility of a Body Shape Index for Abdominal Aortic Calcification in Hypertension: From Association to Clinical Applicability.Clinical cardiology · 2026Article
- Reconsidering the Prognostic Role of the HALP Score in Rheumatic Mitral Stenosis.Clinical cardiology · 2026Article
- Article
- Serum tyrosine increases all-cause mortality in an older population.Frontiers in endocrinology · 2025Article
- Superior predictive value of estimated pulse wave velocity for all-cause and cardiovascular disease mortality risk in U.S. general adults.BMC public health · 2024Article
- Article
- Multisystem Trajectories Over the Adult Life Course and Relations to Cardiovascular Disease and Death.The journals of gerontology. Series A, Biological sciences and medical sciences · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
purposeIn light of widespread interest in the prognostic value of biomarkers, we apply three discrimination measures to evaluate the incremental value of biomarkers--beyond self-reported measures--for predicting all-cause mortality. We assess whether all three measures--area under the receiver-operating characteristic curve, continuous net reclassification improvement, and integrated discrimination improvement--lead to the same conclusions.
methodsWe use longitudinal data from a nationally representative sample of older Taiwanese (n = 639, aged 54 or older in 2000, examined in 2000 and 2006, with mortality follow-up through 2011). We estimate age-specific mortality using a Gompertz hazard model.
resultsThe broad conclusions are consistent across the three discrimination measures and support the inclusion of biomarkers, particularly inflammatory markers, in household surveys. Although the rank ordering of individual biomarkers varies across discrimination measures, the following is true for all three: interleukin-6 is the strongest predictor, the other three inflammatory markers make the top 10, and homocysteine ranks second or third.
conclusionsThe consistency of most of our findings across metrics should provide comfort to researchers using discrimination measures to evaluate the prognostic value of biomarkers. However, because the degree of consistency varies with the level of detail inherent in the research question, we recommend that researchers confirm results with multiple discrimination measures.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.