Prognostic/Clinical Prediction Models: Using Observational Data to Estimate Prognosis: An Example Using a Coronary Artery Disease Registry

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© 2004 John Wiley & Sons Ltd. All Rights Reserved. With the proliferation of clinical data registries and the rising expense of clinical trials, observational data sources are increasingly providing evidence for clinical decision making. These data are viewed as complementary to randomized clinical trials (RCT). While not as rigorous a methodological design, observational studies yield important information about effectiveness of treatment, as compared with the efficacy results of RCTs. In addition, these studies often have the advantage of providing longer-term follow-up, beyond that of clinical trials. Hence, they are useful for assessing and comparing patients' long-term prognosis under different treatment strategies. For patients with coronary artery disease, many observational comparisons have focused on medical therapy versus interventional procedures. In addition to the well-studied problem of treatment selection bias (which is not the focus of the present study), three significant methodological problems must be addressed in the analysis of these data: (i) designation of the therapeutic arms in the presence of early deaths, withdrawals, and treatment cross-overs; (ii) identification of an equitable starting point for attributing survival time; (iii) site to site variability in short-term mortality. This paper discusses these issues and suggests strategies to deal with them. A proposed methodology is developed, applied and evaluated on a large observational database that has long-term follow-up on nearly 10 000 patients.

Full Text

Duke Authors

Cited Authors

  • Delong, ER; Nelson, CL; Wong, JB; Pryor, DB; Peterson, ED; Lee, KL; Mark, DB; Califf, RM; Pauker, SG

Published Date

  • August 24, 2005

Volume / Issue

  • 1 /

Book Title

  • Tutorials in Biostatistics, Statistical Methods in Clinical Studies

Start / End Page

  • 287 - 314

International Standard Book Number 10 (ISBN-10)

  • 0470023651

International Standard Book Number 13 (ISBN-13)

  • 9780470023655

Digital Object Identifier (DOI)

  • 10.1002/0470023678.ch2b(iii)

Citation Source

  • Scopus