A Tool to Translate Intermediate Endpoints to Mortality in CE Studies

Many comparative effectiveness (CE) studies of 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. Instead, they measure the effect of the intervention on intermediate endpoints such as incidence or time to disease recurrence. CANTRANce, or CANcer TRANslation for Comparative Effectiveness, is a modeling tool that translates the results of these studies into projections of the impact on deaths due to the disease.

The CANTRANce framework will be developed for comparative effectiveness studies of interventions intended to control cancer at five decision points during the course of the disease: (1) Disease prevention, (2) Screening using tests with known diagnostic properties (sensitivity and specificity), (3) Screening using tests with known impact on stage-specific incidence of disease, (4) Diagnostic testing for treatment targeting, and (5) treatments with known impact on time to disease recurrence.  In each of these setting we will develop a mode to extrapolate results of the corresponding studies to disease-specific deaths. Investigators using the framework will be prompted to enter relevant information about their study and assumptions about the link between the intermediate and final outcomes via a web-based interactive too.

The tool will be publically available so that investigators can enter their comparative effectiveness study results, choose from a variety of assumptions concerning the mechanism by which the intervention affects cancer deaths, and set values for key input parameters. Model outputs will include disease-specific survival, other-cause survival, and years of life saved for the intervention of interest. 

This activity is supported by a grant from the National Cancer Institute (RC4 CA155806).

CANTRANce Publications

Birnbaum JK, Ademuyiwa FO, Carlson JJ, Mallinger L, Mason MW, Etzioni R. Comparative effectiveness of biomarkers to target cancer treatment: modeling implications for survival and costs. Med Decis Making. 2015 Aug 24.

Birnbaum JK, Feng Z, Gulati R, Fan J, Lotan Y, Wei JT, Etzioni R. Projecting benefits and harms of novel cancer screening biomarkers: a study of pca3 and prostate cancer. Cancer Epidemiol Biomarkers Prev. 2015 Apr;24(4):677-82.