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

Elizabeth R. Delong, Charlotte L. Nelson, John B. Wong, David B. Pryor, Eric D. Peterson, Kerry L. Lee, Daniel B. Mark, Robert M. Califf, Stephen G. Pauker

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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.

Original languageEnglish (US)
Title of host publicationTutorials in Biostatistics, Statistical Methods in Clinical Studies
Publisherwiley
Pages287-314
Number of pages28
Volume1
ISBN (Electronic)9780470023679
ISBN (Print)0470023651, 9780470023655
DOIs
StatePublished - Aug 24 2005
Externally publishedYes

ASJC Scopus subject areas

  • Mathematics(all)

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