Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

ACC 2024 Congress

Catch up on all the top stories and latest evidence in cardiology research with our ACC 2024 Congress hub page.
ADVANCED SEARCH
Log in
Top
BMC Medical Research Methodology
Published in: BMC Medical Research Methodology 1/2011

Open Access 01-12-2011 | Research article

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

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

Published in: BMC Medical Research Methodology | Issue 1/2011

Login to get access

Abstract

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.
Appendix
Available only for authorised users
Literature
1.
Raczek AE, Ware JE, Bjorner JB, Gandek B, Haley SM, Aaronson NK, Apolone G, Bech P, Brazier JE, Bullinger M, Sullivan M: Comparison of Rasch and summated rating scales constructed from SF-36 physical functioning items in seven countries: results from the IQOLA Project. International Quality of Life Assessment. JClinEpidemiol. 1998, 51 (11): 1203-1214.
2.
Ware J, Kosinski M, Keller SD: A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Medical care. 1996, 34 (3): 220-233. 10.1097/00005650-199603000-00003.CrossRefPubMed
3.
Ware JE, Kosinski M, Gandek B, Aaronson NK, Apolone G, Bech P, Brazier J, Bullinger M, Kaasa S, Leplege A, Prieto L, Sullivan M: The factor structure of the SF-36 Health Survey in 10 countries: results from the IQOLA Project. International Quality of Life Assessment. JClinEpidemiol. 1998, 51 (11): 1159-1165.
4.
Kontodimopoulos N, Pappa E, Niakas D, Tountas Y: Validity of SF-12 summary scores in a Greek general population. Health and quality of life outcomes. 2007, 5: 55-10.1186/1477-7525-5-55.CrossRefPubMedPubMedCentral
5.
Burstrom B, Fredlund P: Self rated health: Is it as good a predictor of subsequent mortality among adults in lower as well as in higher social classes?. JEpidemiolCommunity Health. 2001, 55 (11): 836-840.
6.
Heidrich J, Liese AD, Lowel H, Keil U: Self-rated health and its relation to all-cause and cardiovascular mortality in southern Germany. Results from the MONICA Augsburg cohort study 1984-1995. AnnEpidemiol. 2002, 12 (5): 338-345.
7.
Idler EL, Benyamini Y: Self-rated health and mortality: a review of twenty-seven community studies. JHealth SocBehav. 1997, 38 (1): 21-37.
8.
Singh-Manoux A, Gueguen A, Martikainen P, Ferrie J, Marmot M, Shipley M: Self-rated health and mortality: short- and long-term associations in the Whitehall II study. PsychosomMed. 2007, 69 (2): 138-143.
9.
Farkas J, Nabb S, Zaletel-Kragelj L, Cleland JG, Lainscak M: Self-rated health and mortality in patients with chronic heart failure. EurJHeart Fail. 2009, 11 (5): 518-524.
10.
Dorr DA, Jones SS, Burns L, Donnelly SM, Brunker CP, Wilcox A, Clayton PD: Use of health-related, quality-of-life metrics to predict mortality and hospitalizations in community-dwelling seniors. JAmGeriatrSoc. 2006, 54 (4): 667-673.
11.
Otero-Rodriguez A, Leon-Munoz LM, Balboa-Castillo T, Banegas JR, Rodriguez-Artalejo F, Guallar-Castillon P: Change in health-related quality of life as a predictor of mortality in the older adults. QualLife Res. 19 (1): 15-23.
12.
Tsai SY, Chi LY, Lee CH, Chou P: Health-related quality of life as a predictor of mortality among community-dwelling older persons. EurJEpidemiol. 2007, 22 (1): 19-26.
13.
Gotay CC, Kawamoto CT, Bottomley A, Efficace F: The prognostic significance of patient-reported outcomes in cancer clinical trials. JClinOncol. 2008, 26 (8): 1355-1363.CrossRef
14.
Quinten C, Coens C, Mauer M, Comte S, Sprangers MA, Cleeland C, Osoba D, Bjordal K, Bottomley A: Baseline quality of life as a prognostic indicator of survival: a meta-analysis of individual patient data from EORTC clinical trials. Lancet Oncol. 2009, 10 (9): 865-871. 10.1016/S1470-2045(09)70200-1.CrossRefPubMed
15.
McEwen LN, Kim C, Haan MN, Ghosh D, Lantz PM, Thompson TJ, Herman WH: Are health-related quality-of-life and self-rated health associated with mortality? Insights from Translating Research Into Action for Diabetes (TRIAD). PrimCare Diabetes. 2009, 3 (1): 37-42.
16.
Faller H, Stork S, Schowalter M, Steinbuchel T, Wollner V, Ertl G, Angermann CE: Is health-related quality of life an independent predictor of survival in patients with chronic heart failure?. JPsychosomRes. 2007, 63 (5): 533-538.
17.
Rodriguez-Artalejo F, Guallar-Castillon P, Pascual CR, Otero CM, Montes AO, Garcia AN, Conthe P, Chiva MO, Banegas JR, Herrera MC: Health-related quality of life as a predictor of hospital readmission and death among patients with heart failure. ArchInternMed. 2005, 165 (11): 1274-1279.
18.
Budweiser S, Hitzl AP, Jorres RA, Schmidbauer K, Heinemann F, Pfeifer M: Health-related quality of life and long-term prognosis in chronic hypercapnic respiratory failure: a prospective survival analysis. RespirRes. 2007, 8: 92-CrossRef
19.
Sprenkle MD, Niewoehner DE, Nelson DB, Nichol KL: The Veterans Short Form 36 questionnaire is predictive of mortality and health-care utilization in a population of veterans with a self-reported diagnosis of asthma or COPD. Chest. 2004, 126 (1): 81-89. 10.1378/chest.126.1.81.CrossRefPubMed
20.
Hayashino Y, Fukuhara S, Akiba T, Akizawa T, Asano Y, Saito S, Kurokawa K: Low health-related quality of life is associated with all-cause mortality in patients with diabetes on haemodialysis: the Japan Dialysis Outcomes and Practice Pattern Study. DiabetMed. 2009, 26 (9): 921-927.
21.
Cunningham WE, Crystal S, Bozzette S, Hays RD: The association of health-related quality of life with survival among persons with HIV infection in the United States. JGenInternMed. 2005, 20 (1): 21-27.
22.
Salomaa V, Havulinna A, Saarela O, Zeller T, Jousilahti P, Jula A, Muenzel T, Aromaa A, Evans A, Kuulasmaa K, Blankenberg S: Thirty-one novel biomarkers as predictors for clinically incident diabetes. PloS one. 5 (4): e10100-
23.
Zethelius B, Berglund L, Sundstrom J, Ingelsson E, Basu S, Larsson A, Venge P, Arnlov J: Use of multiple biomarkers to improve the prediction of death from cardiovascular causes. The New England journal of medicine. 2008, 358 (20): 2107-2116. 10.1056/NEJMoa0707064.CrossRefPubMed
24.
Ingelsson E, Pencina MJ, Tofler GH, Benjamin EJ, Lanier KJ, Jacques PF, Fox CS, Meigs JB, Levy D, Larson MG, Selhub J, D'Agostino RB, Wang TJ, Vasan RS: Multimarker approach to evaluate the incidence of the metabolic syndrome and longitudinal changes in metabolic risk factors: the Framingham Offspring Study. Circulation. 2007, 116 (9): 984-992. 10.1161/CIRCULATIONAHA.107.708537.CrossRefPubMed
25.
Haring R, Alte D, Volzke H, Sauer S, Wallaschofski H, John U, Schmidt CO: Extended recruitment efforts minimize attrition but not necessarily bias. J Clin Epidemiol. 2009, 62 (3): 252-260. 10.1016/j.jclinepi.2008.06.010.CrossRefPubMed
26.
Volzke H, Alte D, Schmidt CO, Radke D, Lorbeer R, Friedrich N, Aumann N, Lau K, Piontek M, Born G, Havemann C, Ittermann T, Schipf S, Haring R, Baumeister SE, Wallaschofski H, Nauck M, Frick S, Arnold A, Junger M, Mayerle J, Kraft M, Lerch MM, Dorr M, Reffelmann T, Empen K, Felix SB, Obst A, Koch B, Glaser S, et al: Cohort profile: the study of health in pomerania. International journal of epidemiology. 2011, 40 (2): 294-307. 10.1093/ije/dyp394.CrossRefPubMed
27.
Alte D, Luedemann J, Rose HJ, John U: Laboratory markers carbohydrate-deficient transferrin, gamma-glutamyltransferase, and mean corpuscular volume are not useful as screening tools for high-risk drinking in the general population: results from the Study of Health in Pomerania (SHIP). Alcoholism, clinical and experimental research. 2004, 28 (6): 931-940. 10.1097/01.ALC.0000128383.34605.16.CrossRefPubMed
28.
Winkler G, Doring A: Validation of a short qualitative food frequency list used in several German large scale surveys. Zeitschrift fur Ernahrungswissenschaft. 1998, 37 (3): 234-241.PubMed
29.
Kawachi I, Kennedy BP: The relationship of income inequality to mortality: does the choice of indicator matter?. Social science & medicine (1982). 1997, 45 (7): 1121-1127. 10.1016/S0277-9536(97)00044-0.CrossRef
30.
Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D: A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999, 130 (6): 461-470.CrossRefPubMed
31.
Cook NR: Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation. 2007, 115 (7): 928-935. 10.1161/CIRCULATIONAHA.106.672402.CrossRefPubMed
32.
Pencina MJ, D'Agostino RB, D'Agostino RB, Vasan RS: Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008, 27 (2): 157-172. 10.1002/sim.2929. discussion 207-112CrossRefPubMed
33.
Afifi AA, Kotlerman JB, Ettner SL, Cowan M: Methods for improving regression analysis for skewed continuous or counted responses. Annual review of public health. 2007, 28: 95-111. 10.1146/annurev.publhealth.28.082206.094100.CrossRefPubMed
34.
Donders AR, van der Heijden GJ, Stijnen T, Moons KG: Review: a gentle introduction to imputation of missing values. Journal of clinical epidemiology. 2006, 59 (10): 1087-1091. 10.1016/j.jclinepi.2006.01.014.CrossRefPubMed
35.
Van Buuren S, Outshoorn K: Flexible multivariate imputation by mice. Technical report. 1999, Leiden: TNO prevention and Health
36.
von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007, 370 (9596): 1453-1457. 10.1016/S0140-6736(07)61602-X.CrossRefPubMed
37.
Domingo-Salvany A, Lamarca R, Ferrer M, Garcia-Aymerich J, Alonso J, Felez M, Khalaf A, Marrades RM, Monso E, Serra-Batlles J, Anto JM: Health-related quality of life and mortality in male patients with chronic obstructive pulmonary disease. AmJRespirCrit Care Med. 2002, 166 (5): 680-685.CrossRef
38.
Mapes DL, Lopes AA, Satayathum S, McCullough KP, Goodkin DA, Locatelli F, Fukuhara S, Young EW, Kurokawa K, Saito A, Bommer J, Wolfe RA, Held PJ, Port FK: Health-related quality of life as a predictor of mortality and hospitalization: the Dialysis Outcomes and Practice Patterns Study (DOPPS). Kidney Int. 2003, 64 (1): 339-349. 10.1046/j.1523-1755.2003.00072.x.CrossRefPubMed
39.
Rumsfeld JS, MaWhinney S, McCarthy M, Shroyer AL, VillaNueva CB, O'Brien M, Moritz TE, Henderson WG, Grover FL, Sethi GK, Hammermeister KE: Health-related quality of life as a predictor of mortality following coronary artery bypass graft surgery. Participants of the Department of Veterans Affairs Cooperative Study Group on Processes, Structures, and Outcomes of Care in Cardiac Surgery. JAMA. 1999, 281 (14): 1298-1303. 10.1001/jama.281.14.1298.CrossRefPubMed
40.
Dominick KL, Ahern FM, Gold CH, Heller DA: Relationship of health-related quality of life to health care utilization and mortality among older adults. Aging ClinExpRes. 2002, 14 (6): 499-508.
41.
Lee Y: The predictive value of self assessed general, physical, and mental health on functional decline and mortality in older adults. JEpidemiolCommunity Health. 2000, 54 (2): 123-129.
42.
Simon GE, Revicki DA, Grothaus L, Vonkorff M: SF-36 summary scores: are physical and mental health truly distinct?. MedCare. 1998, 36 (4): 567-572.
43.
DeSalvo KB, Fan VS, McDonell MB, Fihn SD: Predicting mortality and healthcare utilization with a single question. Health ServRes. 2005, 40 (4): 1234-1246. 10.1111/j.1475-6773.2005.00404.x.
44.
Kaplan MS, Berthelot JM, Feeny D, McFarland BH, Khan S, Orpana H: The predictive validity of health-related quality of life measures: mortality in a longitudinal population-based study. QualLife Res. 2007, 16 (9): 1539-1546.
45.
Idler EL, Kasl SV, Lemke JH: Self-evaluated health and mortality among the elderly in New Haven, Connecticut, and Iowa and Washington counties, Iowa, 1982-1986. AmJEpidemiol. 1990, 131 (1): 91-103.
46.
Strawbridge WJ, Wallhagen MI: Self-rated health and mortality over three decades - Results from a time-dependent covariate analysis. Research on Aging. 1999, 21 (3): 402-416. 10.1177/0164027599213003.CrossRef
47.
Jylha M, Volpato S, Guralnik JM: Self-rated health showed a graded association with frequently used biomarkers in a large population sample. J Clin Epidemiol. 2006, 59 (5): 465-471. 10.1016/j.jclinepi.2005.12.004.CrossRefPubMed
48.
Kroenke CH, Kubzansky LD, Adler N, Kawachi I: Prospective change in health-related quality of life and subsequent mortality among middle-aged and older women. AmJPublic Health. 2008, 98 (11): 2085-2091.
Metadata
Title
Self-perceived quality of life predicts mortality risk better than a multi-biomarker panel, but the combination of both does best
Authors
Robin Haring
You-Shan Feng
Jörn Moock
Henry Völzke
Marcus Dörr
Matthias Nauck
Henri Wallaschofski
Thomas Kohlmann
Publication date
01-12-2011
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2011
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/1471-2288-11-103

Other articles of this Issue 1/2011

BMC Medical Research Methodology 1/2011 Go to the issue

Research article

Bayesian adjustment for measurement error in continuous exposures in an individually matched case-control study

Commentary

The Australian 'FORM' approach to guideline development: The quest for the perfect system

Research article

A population study comparing screening performance of prototypes for depression and anxiety with standard scales

Research article

Development of a heart failure filter for Medline: an objective approach using evidence-based clinical practice guidelines as an alternative to hand searching

Research article

Instrumental variable meta-analysis of individual patient data: application to adjust for treatment non-compliance

Research article

Adjusting a cancer mortality-prediction model for disease status-related eligibility criteria