The contribution of longitudinal comorbidity measurements to survival analysis
Authors
Wang, C. Y.Baldwin, Laura-Mae
Saver, Barry G.
Dobie, Sharon A.
Green, Pamela K.
Cai, Yong
Klabunde, Carrie N.
UMass Chan Affiliations
Department of Family Medicine and Community HealthMeyers Primary Care Institute
Document Type
Journal ArticlePublication Date
2009-07-19Keywords
AgedCause of Death
*Comorbidity
Data Collection
Data Interpretation, Statistical
Female
Geriatric Assessment
Health Services Research
Health Status
Health Status Indicators
Humans
Likelihood Functions
*Longitudinal Studies
Male
Medicare
Multivariate Analysis
Predictive Value of Tests
*Proportional Hazards Models
Research Design
Retrospective Studies
SEER Program
*Survival Analysis
Time Factors
United States
Health Services Research
Primary Care
Metadata
Show full item recordAbstract
BACKGROUND: Many clinical and health services research studies are longitudinal, raising questions about how best to use an individual's comorbidity measurements over time to predict survival. OBJECTIVES: To evaluate the performance ofdifferent approaches to longitudinal comorbidity measurement in predicting survival, and to examine strategies for addressing the inevitable issue of missing data. RESEARCH DESIGN: Retrospective cohort study using Cox regression analysis to examine the association between various Romano-Charlson comorbidity measures and survival. SUBJECTS: Fifty thousand cancer-free individuals aged 66 or older enrolled in Medicare between 1991 and 1999 for at least 1 year. RESULTS: The best fitting model combined both time independent baseline comorbidity and the time dependent prior year comorbidity measure. The worst fitting model included baseline comorbidity only. Overall, the models fit best when using the "rolling" comorbidity measures that assumed chronic conditions persisted rather than measures using only prior year's recorded diagnoses. CONCLUSIONS: Longitudinal comorbidity is an important predictor of survival, and investigators should make use of individuals' longitudinal comorbidity data in their regression modeling.Source
Med Care. 2009 Jul;47(7):813-21. Link to article on publisher's siteDOI
10.1097/MLR.0b013e318197929cPermanent Link to this Item
http://hdl.handle.net/20.500.14038/37076PubMed ID
19536031Related Resources
Link to Article in PubMedae974a485f413a2113503eed53cd6c53
10.1097/MLR.0b013e318197929c