Self-perceived quality of life predicts mortality risk better than a multi-biomarker panel, but the combination of both does best

Research output: Journal contributionsJournal articlesResearchpeer-review

Authors

  • Robin Haring
  • You-Shan Feng
  • Jörn Moock
  • Henry Völzke
  • Marcus Dörr
  • Matthias Nauck
  • Henri Wallaschofski
  • Thomas Kohlmann

Background: Associations between measures of subjective health and mortality risk have previously been shown. We assessed the impact and comparative predictive performance of a multi-biomarker panel on this association. Methods. Data from 4,261 individuals aged 20-79 years recruited for the population-based Study of Health in Pomerania was used. During an average 9.7 year follow-up, 456 deaths (10.7%) occurred. Subjective health was assessed by SF-12 derived physical (PCS-12) and mental component summaries (MCS-12), and a single-item self-rated health (SRH) question. We implemented Cox proportional-hazards regression models to investigate the association of subjective health with mortality and to assess the impact of a combination of 10 biomarkers on this association. Variable selection procedures were used to identify a parsimonious set of subjective health measures and biomarkers, whose predictive ability was compared using receiver operating characteristic (ROC) curves, C-statistics, and reclassification methods. Results: In age- and gender-adjusted Cox models, poor SRH (hazard ratio (HR), 2.07; 95% CI, 1.34-3.20) and low PCS-12 scores (lowest vs. highest quartile: HR, 1.75; 95% CI, 1.31-2.33) were significantly associated with increased risk of all-cause mortality; an association independent of various covariates and biomarkers. Furthermore, selected subjective health measures yielded a significantly higher C-statistic (0.883) compared to the selected biomarker panel (0.872), whereas a combined assessment showed the highest C-statistic (0.887) with a highly significant integrated discrimination improvement of 1.5% (p < 0.01). Conclusion: Adding biomarker information did not affect the association of subjective health measures with mortality, but significantly improved risk stratification. Thus, a combined assessment of self-reported subjective health and measured biomarkers may be useful to identify high-risk individuals for intensified monitoring.

Original languageEnglish
Article number103
JournalBMC Medical Research Methodology
Volume11
Issue number103
Number of pages10
DOIs
Publication statusPublished - 12.07.2011

Bibliographical note

Funding Information:
Statistical analysis were supported by the Community Medicine Research net (CMR) of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research, the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania. The CMR encompasses several research projects which are sharing data of the population-based Study of Health in Pomerania (SHIP; http://www.community-medicine.de). This work is part of the research project Greifswald Approach to Individualized Medicine (GANI_MED). The GANI_MED consortium is funded by the Federal Ministry of Education and Research and the Ministry of Cultural Affairs of the Federal State of Mecklenburg -West Pomerania (03IS2061A).

    Research areas

  • Health sciences - Adult, Aged, Biological Markers, Cluster Analysis, Diagnostic Self Evaluation, Female, Germany, Humans, Kaplan-Meier Estimate, Male, Middle Aged, Mortality, Proportional Hazards Models, Quality of Life, ROC Curve, Risk Factors, Self Report, Young Adult

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