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324678
Predicting 1-year Mortality in elderly Patients with Diabetes


Tuesday, November 3, 2015 : 8:30 a.m. - 8:50 a.m.

Yu-Kang Chang, Postdoc, Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan
Li-Feng Huang, MS, Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan
Jia-Sin Liu, MS, Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan
Chih-Cheng Hsu, MD, Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan
Audio (mp3) recording Recorded Presentation (mp4)
Background and purpose

Research focusing on diabetic outcomes for the elderly population is still lacking. The aim of this study was to identify predictors of one-year morality for the elderly diabetic patients.

Methods

We used the Adult Health Screening Program (AHSP) dataset (approximately three million participants) for the model development and a health screening dataset provided by the MJ Health Management Institution (462,293 participants) for the model validation. For the present analysis, we chose the diabetic patients >= 65 years as the study subjects and used multivariate Cox proportional hazards models to predict 1-year all-cause mortality for the selected subjects. Regression coefficients were then calculated into decimal risk score. A contrast point was set for each selected variable to reflect the increase in risk compared with that for a 10-year increase in age. The final model was constructed through selection of cross validation. The predictive accuracy was obtained by calculating the area under the receiver operating characteristic (AUC) curve.

Results

A total of 247,463 diabetic elderly patients were selected for statistical analyses. There are 25,847 (10.5%) patients died within one year after entry. The final prediction model contained thirteen predictors. The AUC curves of the development and validation models were 0.810 and 0.827, respectively. The internal validation showed a similar result (AUC curve=0.802).

Conclusions

We established a point-based model to predict 1-year mortality for elderly diabetic patients. The easy-to-use points-based system may be able to help health providers to accurately predict short-term mortality risk for the elderly with diabetes.

Learning Areas:

Epidemiology
Protection of the public in relation to communicable diseases including prevention or control
Systems thinking models (conceptual and theoretical models), applications related to public health

Learning Objectives:
Identify the dataset used for the model development. Name the type of model system used to predict 1-year mortality for elderly diabetic patients.

Keyword(s): Diabetes, Mortality

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have been the principal focusing on the epidemiology of diabetes and mortality of prediction models. Among my scientific interests has been the development of strategies and prediction models for preventing mortality in elderly patients with diabetes.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

Back to: 4016.0: Applications using Longitudinal Health Data