Predicting 6-Year Mortality Risk in Patients With Type 2 Diabetes
Response to Paul et al.
- Brian J. Wells, MD1,
- Anil Jain, MD2,
- Susana Arrigain, MA1,
- Changhong Yu, MS1,
- Wayne A. Rosenkrans, Jr., PHD3,4,5 and
- Michael W. Kattan, PHD1
- 1Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio;
- 2Information Technology, Cleveland Clinic, Cleveland, Ohio;
- 3Center for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, Massachusetts;
- 4Personalized Medicine Coalition, Washington, DC;
- 5SciTech Strategies, Berwyn, Pennsylvania.
- Corresponding author: Michael W. Kattan, kattanm{at}ccf.org
We welcome the comments by Paul et al. (1) and the opportunity to clarify aspects of our study (2). Many of our decisions appear counterintuitive upon initial reading.
As described, several variables had considerable levels of missing values. We chose to impute missing values before making our prediction model. When applied to future patients with complete data, a model based on an imputed dataset should predict more accurately than one based on complete cases only. Relying on complete cases actually introduces more bias than imputing missing values.
Our goal was a prediction tool for counseling a patient at baseline. We avoided explicit assumptions regarding future patient behavior (e.g., adherence) or response (e.g., …
