Grant Number:	1RC4CA155806-01 Interpret this number
Primary Investigator:	Etzioni, Ruth
Organization:	Fred Hutchinson Cancer Research Center
Project Title:	CANTRANCE: a Tool to Translate Intermediate Endpoints to Mortality in Ce Studies
Fiscal Year:	2010

DESCRIPTION (provided by applicant): One of the main challenges in Comparative Effectiveness (CE) research in cancer is that limitations in follow- up data often require investigators to use intermediate endpoints rather than the endpoint of most interest, namely, disease-specific mortality. This proposal aims to develop a flexible, portable, and efficient framework to translate cancer CE study results about intermediate endpoints into inferences about disease-specific deaths. The framework, CANTRANce (CANcer TRANslation for Comparative Effectiveness), will consist of a suite of computer micro simulation models corresponding to the main types of cancer control studies, namely, cancer prevention, biomarker development for early detection, screening, diagnostic testing for treatment selection, and primary treatment studies. The framework will be made publicly available via a user-friendly interface that will enable study investigators to input their CE study results, provide parameters necessary for the translation process, and specify outputs of interest. Our aims are as follows: (1) Develop five prototype models applicable across a broad range of cancers to translate the effects of interventions on intermediate endpoints commonly encountered in the main types of cancer control studies into projections of impacts on disease-specific deaths. The intermediate endpoints addressed by CANTRANce will consist of: (1) disease incidence, (2) sensitivity of biomarkers to detect latent disease, (3) stage distributions at diagnosis, (4) primary treatment frequencies, and (5) primary treatment failure times. (2) Demonstrate this methodology using Model (e) as a proof-of-principle based on disease recurrence results from the Scandinavian Prostate Cancer Group 4 clinical trial to project mortality differences between men randomized to radical prostatectomy or watchful waiting arms. Use the trial results on disease-specific mortality to validate the model and explore the implications of varying key user assumptions. (3) Design, implement, test, and release a web interface that will facilitate direct utilization of the modeling framework and make the underlying technology publicly available. As part of this aim we will provide a version of the interface to investigators doing CE research in cancer using the intermediate endpoints listed in Aim 1 and will solicit their feedback to improve the models and interface. The proposed framework represents both a method for addressing a pervasive problem in CE studies and a technology for implementation of the method. Given the large number of cancer CE studies that are either planned or ongoing, and given that many of these are likely to use intermediate endpoints, we expect that CANTRANce will become a highly useful and broadly applicable component of the methods toolbox for CE research in cancer. PUBLIC HEALTH RELEVANCE: Many studies comparing methods to prevent treat, or cure cancer do not have the time or the information to evaluate how the approaches being studied affect cancer deaths. This proposal will develop a software system to translate the results of these studies into projections of the effects of the methods being compared on deaths due to the disease.




Comparative Effectiveness of Biomarkers to Target Cancer Treatment: Modeling Implications for Survival and Costs.
Authors: Birnbaum J.K. , Ademuyiwa F.O. , Carlson J.J. , Mallinger L. , Mason M.W. , Etzioni R. .
Source: Medical decision making : an international journal of the Society for Medical Decision Making, 2016 Jul; 36(5), p. 594-603.
EPub date: 2015-08-24.
PMID: 26304062
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The Effect of Treatment Advances on the Mortality Results of Breast Cancer Screening Trials: A Microsimulation Model.
Authors: Birnbaum J. , Gadi V.K. , Markowitz E. , Etzioni R. .
Source: Annals of internal medicine, 2016-02-16; 164(4), p. 236-43.
EPub date: 2016-01-12.
PMID: 26756332
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